importance of chlorophyll in photosynthesis experiment

Chlorophyll Definition and Role in Photosynthesis

Understand the importance of chlorophyll in photosynthesis

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Chlorophyll is the name given to a group of green pigment molecules found in plants, algae, and cyanobacteria. The two most common types of chlorophyll are chlorophyll a, which is a blue-black ester with the chemical formula C 55 H 72 MgN 4 O 5 , and chlorophyll b, which is a dark green ester with the formula C 55 H 70 MgN 4 O 6 . Other forms of chlorophyll include chlorophyll c1, c2, d, and f. The forms of chlorophyll have different side chains and chemical bonds, but all are characterized by a chlorin pigment ring containing a magnesium ion at its center.

Key Takeaways: Chlorophyll

• Chlorophyll is a green pigment molecule that collects solar energy for photosynthesis. It's actually a family of related molecules, not just one.
• Chlorophyll is found in plants, algae, cyanobacteria, protists, and a few animals.
• Although chlorophyll is the most common photosynthetic pigment, there are several others, including the anthocyanins.

The word "chlorophyll" comes from the Greek words chloros , which means "green", and phyllon , which means "leaf". Joseph Bienaimé Caventou and Pierre Joseph Pelletier first isolated and named the molecule in 1817.

Chlorophyll is an essential pigment molecule for photosynthesis , the chemical process plants use to absorb and use energy from light. It's also used as a food coloring (E140) and as a deodorizing agent. As a food coloring, chlorophyll is used to add a green color to pasta, the spirit absinthe, and other foods and beverages. As a waxy organic compound, chlorophyll is not soluble in water. It is mixed with a small amount of oil when it's used in food.

Also Known As: The alternate spelling for chlorophyll is chlorophyl.

Role of Chlorophyll in Photosynthesis

The overall balanced equation for photosynthesis is:

6 CO 2 + 6 H 2 O → C 6 H 12 O 6 + 6 O 2

where carbon dioxide and water react to produce glucose and oxygen . However, the overall reaction doesn't indicate the complexity of the chemical reactions or the molecules that are involved.

Plants and other photosynthetic organisms use chlorophyll to absorb light (usually solar energy) and convert it into chemical energy. Chlorophyll strongly absorbs blue light and also some red light. It poorly absorbs green (reflects it), which is why chlorophyll-rich leaves and algae appear green .

In plants, chlorophyll surrounds photosystems in the thylakoid membrane of organelles called chloroplasts , which are concentrated in the leaves of plants. Chlorophyll absorbs light and uses resonance energy transfer to energize reaction centers in photosystem I and photosystem II. This happens when energy from a photon (light) removes an electron from chlorophyll in reaction center P680 of photosystem II. The high energy electron enters an electron transport chain. P700 of photosystem I works with photosystem II, although the source of electrons in this chlorophyll molecule can vary.

Electrons that enter the electron transport chain are used to pump hydrogen ions (H + ) across the thylakoid membrane of the chloroplast. The chemiosmotic potential is used to produce the energy molecule ATP and to reduce NADP + to NADPH. NADPH, in turn, is used to reduce carbon dioxide (CO 2 ) into sugars, such as glucose.

Other Pigments and Photosynthesis

Chlorophyll is the most widely recognized molecule used to collect light for photosynthesis, but it's not the only pigment that serves this function. Chlorophyll belongs to a larger class of molecules called anthocyanins. Some anthocyanins function in conjunction with chlorophyll, while others absorb light independently or at a different point of an organism's life cycle. These molecules may protect plants by changing their coloring to make them less attractive as food and less visible to pests. Other anthocyanins absorb light in the green portion of the spectrum, extending the range of light a plant can use.

Write an experiment to show that chlorophyll is necessary for photosynthesis.

Experiment: take a potted plant with variegated leaves like croton and keep it in a dark region, away from sunlight for 3 days. this will halt photosynthesis and de-starch the plant. then keep the plant facing the sunlight for 6 to 8 hours the plant can now carry out photosynthesis and produce starch. mark the green areas in the leaf and trace them on a sheet of paper. mark the regions as green and yellow. the green areas contain chlorophyll which is absent in the yellow areas. immerse the leaf in boiling alcohol to decolorize it. the leaf slowly loses its green color, which goes into the alcohol. dip this decolorized leaf in iodine solution. now remove the leaf from the iodine solution and rinse it in distilled water. remove the leaf from distilled water and keep it on a petri dish. observation two - color regions are visible in the leaf. they are reddish-brown and blue-black. conclusion it can be concluded that the earlier green parts of the leaf turn blue-black whereas the yellow parts have become reddish-brown. green parts of the leaf possess chlorophyll; hence they carry out photosynthesis and produce starch, which turns blue-black with iodine..

Is chlorophyll necessary for photosynthesis? How do we prove it with an experiment? [5 MARKS]

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Chlorophyll: the pigment that gives plants their green color and allows them to absorb sunlight...  more

Chloroplast: a part of a cell found in plants that converts light energy into energy plants can use (sugar). Other living organisms such as algae also have cells that contain chloroplasts.

Thylakoid: the disk-shaped parts of a plant cell where light-dependent reactions occur...  more

The Story of Chlorophyll and Chloroplasts

Round, green chloroplasts fill the middle of a plant cell. Image by Kristian Peters.

Chloroplasts are tiny factories inside the cells of plants. They are also found in the cells of other organisms that use photosynthesis. Chloroplasts take the energy from the sunlight and use it to make plant food. The food can be used immediately to give cells energy or it can be stored as sugar or starch. If stored, it can be used later when the plant needs to do work, like grow a new branch or make a flower.

Chloroplasts Up Close

Inside chloroplasts are special stacks of pancake-shaped structures called thylakoids (Greek thylakos = sack or pouch). Thylakoids have an outer membrane that surrounds an inner area called the lumen. The light-dependent reactions happen inside the thylakoid.

Our cells have mitochondria (Greek mitos = thread, and khondrion = little granule), our energy-producing structures. We don't have any chloroplasts. Plants have both mitochondria and chloroplasts.

This model of a chloroplast shows the stacked thylakoids. The space inside a thylakoid is called a lumen. Image via Guillermo Estefani (artinaid.com).

Both mitochondria and chloroplasts convert one form of energy into another form that cells can use. How did plants get chloroplasts? Chloroplasts were once free-living bacteria! Chloroplasts entered a symbiotic (Greek syn = together, and bios = life) relationship with another cell, which eventually led to the plant cells we have today.

Being Green

Chlorophyll, a green pigment found in chloroplasts, is an important part of the light-dependent reactions. Chlorophyll soaks up the energy from sunlight. It is also the reason why plants are green. You may remember that colors are different wavelengths of light. Chlorophyll captures red and blue wavelengths of light and reflects the green wavelengths. 

Plants that lose their leaves in the winter start breaking down chlorophyll in fall. This takes away the green color of leaves. Image by John Fowler.

Plants have different types of pigments besides chlorophyll. Some of them also assist in absorbing light energy. These different pigments are most noticeable during the fall. During that time, plants make less chlorophyll and the other colors are no longer hidden beneath green. 

But why don't plants have pigments that allow them to capture all wavelengths of light? If you've ever gotten a sunburn you know firsthand that sunlight can be damaging. Plants can also be damaged from excess light energy. Luckily, there are non-chlorophyll pigments in plants that provide a 'sunscreen'.

Additional images via Wikimedia Commons. Algae image by Leonardo Ré-Jorge.

Read more about: Snacking on Sunlight

View citation, bibliographic details:.

• Article: Chlorophyll and Chloroplasts
• Author(s): Heather Kropp, Angela Halasey
• Publisher: Arizona State University School of Life Sciences Ask A Biologist
• Site name: ASU - Ask A Biologist
• Date published: August 2, 2014
• Date accessed: August 28, 2024
• Link: https://askabiologist.asu.edu/chlorophyll-and-chloroplasts

Heather Kropp, Angela Halasey. (2014, August 02). Chlorophyll and Chloroplasts. ASU - Ask A Biologist. Retrieved August 28, 2024 from https://askabiologist.asu.edu/chlorophyll-and-chloroplasts

Chicago Manual of Style

Heather Kropp, Angela Halasey. "Chlorophyll and Chloroplasts". ASU - Ask A Biologist. 02 August, 2014. https://askabiologist.asu.edu/chlorophyll-and-chloroplasts

MLA 2017 Style

Heather Kropp, Angela Halasey. "Chlorophyll and Chloroplasts". ASU - Ask A Biologist. 02 Aug 2014. ASU - Ask A Biologist, Web. 28 Aug 2024. https://askabiologist.asu.edu/chlorophyll-and-chloroplasts

Chlorophyll isn't the only photosynthetic molecule. Red and brown algae often have the photosynthetic pigment fucoxanthin.

Snacking on Sunlight

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Practical Biology

A collection of experiments that demonstrate biological concepts and processes.

Observing earthworm locomotion

Practical Work for Learning

Published experiments

Investigating the light dependent reaction in photosynthesis.

It is fairly easy to show that plants produce oxygen and starch in photosynthesis . At age 14–16 students may have collected the gas given off by pond weed (for example Elodea ) and tested leaves for starch.

It is not quite so easy to demonstrate the other reactions in photosynthesis. For the reduction of carbon dioxide to carbohydrate there must be a source of electrons . In the cell, NADP is the electron acceptor which is reduced in the light-dependent reactions, and which provides electrons and hydrogen for the light-independent reactions.

In this investigation, DCPIP (2,6-dichlorophenol-indophenol), a blue dye, acts as an electron acceptor and becomes colourless when reduced, allowing any reducing agent produced by the chloroplasts to be detected.

Lesson organisation

This investigation depends on working quickly and keeping everything cool. Your students will need to understand all the instructions in advance to be sure that they know what they are doing.

Apparatus and Chemicals

Per student or group of students:.

Centrifuge – with RCF between 1500 and 1800g

Centrifuge tubes

Fresh green spinach, lettuce or cabbage, 3 leaves (discard the midribs)

Cold pestle and mortar (or blender or food mixer) which has been kept in a freezer compartment for 15–30 minutes (if left too long the extract will freeze)

Muslin or fine nylon mesh

Filter funnel

Ice-water-salt bath

Glass rod or Pasteur pipette

Measuring cylinder, 20 cm 3

Beaker, 100 cm 3

Pipettes, 5 cm 3 and 1 cm 3

Bench lamp with 100 W bulb

Test tubes, 5

Boiling tube

Pipette for 5 cm 3

Pipette for 0.5 cm 3

Pipette filler

Waterproof pen to label tubes

Colorimeter and tubes or light sensor and data logger

0.05 M phosphate buffer solution, pH 7.0: Store in a refrigerator at 0–4 °C ( Note 1 ).

Isolation medium (sucrose and KCl in phosphate buffer): Store in a refrigerator at 0–4 °C ( Note 2 ).

Potassium chloride (Low Hazard) ( Note 3 ).

DCPIP solution (Low Hazard): (1 x 10 - 4 M approx.) ( Note 4 )

Health & Safety and Technical notes

Although DCPIP presents minimal hazard apart from staining, it is best to avoid skin contact in case prolonged contact with the dye causes sensitisation. Do not handle electric light bulbs with wet hands. All solutions used are low hazard – refer to relevant CLEAPSS Hazcards and Recipe cards for more information.

Read our standard health & safety guidance

1 0.05 M phosphate buffer solution, pH 7.0. Na 2 HPO 4 .12H 2 O, 4.48 g (0.025 M) KH 2 PO 4 , 1.70 g (0.025 M). Make up to 500 cm 3 with distilled water and store in a refrigerator at 0–4 °C. Low hazard – refer to CLEAPSS Hazcard 72.

2 Isolation medium. Sucrose 34.23 g (0.4 M) KCl 0.19 g (0.01 M). Dissolve in phosphate buffer solution (pH 7.0) at room temperature and make up to 250 cm 3 with the buffer solution. Store in a refrigerator at 0–4 °C. Low hazard – refer to CLEAPSS Hazcard 40C.

3 Potassium chloride 0.05 M. Dissolve 0.93 g in phosphate buffer solution at room temperature and make up to 250 cm 3 . Store in a refrigerator at 0–4 °C. Use at room temperature.(Note that Potassium chloride is a cofactor for the Hill reaction.) Refer to CLEAPSS Hazcard 47B and Recipe card 51.

4 DCPIP solution DCPIP 0.007–0.01 g, made up to 100 cm 3 with phosphate buffer. Refer to CLEAPSS Hazcard 32 and Recipe card 46.

Keep solutions and apparatus cold during the extraction procedure, steps 1–8, to preserve enzyme activity. Carry out the extraction as quickly as possible.

Preparation

a Cut three small green spinach, lettuce or cabbage leaves into small pieces with scissors, but discard the tough midribs and leaf stalks. Place in a cold mortar or blender containing 20 cm 3 of cold isolation medium. (Scale up quantities for blender if necessary.)

b Grind vigorously and rapidly (or blend for about 10 seconds).

c Place four layers of muslin or nylon in a funnel and wet with cold isolation medium.

d Filter the mixture through the funnel into the beaker and pour the filtrate into pre-cooled centrifuge tubes supported in an ice-water-salt bath. Gather the edges of the muslin, wring thoroughly into the beaker, and add filtrate to the centrifuge tubes.

e Check that each centrifuge tube contains about the same volume of filtrate.

f Centrifuge the tubes for sufficient time to get a small pellet of chloroplasts. (10 minutes at high speed should be sufficient.)

g Pour off the liquid (supernatant) into a boiling tube being careful not to lose the pellet. Re-suspend the pellet with about 2 cm 3 of isolation medium, using a glass rod. Squirting in and out of a Pasteur pipette five or six times gives a uniform suspension.

h Store this leaf extract in an ice-water-salt bath and use as soon as possible.

Investigation using the chloroplasts

Read all the instructions before you start. Use the DCPIP solution at room temperature.

i Set up 5 labelled tubes as follows.

j When the DCPIP is added to the extract, shake the tube and note the time. Place tubes 1, 2 and 4 about 12–15 cm from a bright light (100 W). Place tube 3 in darkness.

k Time how long it takes to decolourise the DCPIP in each tube. If the extract is so active that it decolourises within seconds of mixing, dilute it 1:5 with isolation medium and try again.

Teaching notes

Traditionally the production of oxygen and starch are used as evidence for photosynthesis. The light-dependent reactions produce a reducing agent. This normally reduces NADP, but in this experiment the electrons are accepted by the blue dye DCPIP. Reduced DCPIP is colourless. The loss of colour in the DCPIP is due to reducing agent produced by light-dependent reactions in the extracted chloroplasts.

Students must develop a clear understanding of the link between the light-dependent and light-independent reactions to be able to interpret the results. Robert Hill originally completed this investigation in 1938; he concluded that water had been split into hydrogen and oxygen. This is now known as the Hill reaction.

You can examine a drop of the sediment extract with a microscope under high power to see chloroplasts. There will be fewer chloroplasts in the supernatant – which decolourises the DCPIP more slowly, reinforcing the idea that the reduction is the result of chloroplast activity.

Sample results

Using a bench centrifuge

The experimental procedure was followed. A standard lab centrifuge was used to spin down the chloroplasts (Clifton NE 010GT/I) at 2650 RPM, 95 X g for 10 minutes.

The experiment was started within 5 minutes of preparing the chloroplasts. The reaction was followed using an EEL colorimeter with a red filter – readings taken every minute.

Tube 3 (incubated in the dark) gave a reading of 5.4 absorption units after 20 minutes. Tube 2 (DCPIP with no leaf extract) was 6.2 absorption units.

Using a micro-centrifuge

The experiment was repeated using a micro-centrifuge.

Tube 3 (incubated in the dark) gave a reading of 4.9 absorption units after 10 minutes.

Tube 2 (DCPIP with no leaf extract) was 6.4 absorption Units.

The relative activity of the pellet was higher than when the bench centrifuge was used. The micro-centrifuge tubes were only 1.5 cm 3 capacity – not ideal for this practical. A higher speed bench centrifuge would be better.

In order to check for loss of chloroplast activity, the experiment was repeated using the same chloroplast suspension 1 and 2 hours after preparation. Chloroplast suspension was kept in a salt-ice bath. There was no loss of activity when the extract was kept in ice for up to 2 hours.

Student questions

1 Describe and explain the changes observed in the five tubes. Compare the results and make some concluding comments about what they show.

2 The rate of photosynthesis in intact leaves can be limited by several factors including light, temperature and carbon dioxide. Which of these factors will have little effect on the reducing capacity of the leaf extract?

3 Describe how you might extend this practical to investigate the effect of light intensity on the light-dependent reactions of photosynthesis.

1 Colour change and inferences that can made from the results: Tube 1 (leaf extract + DCPIP) colour changes until it is the same colour as tube 4 (leaf extract + distilled water). Tube 2 (isolation medium + DCPIP) no colour change. This shows that the DCPIP does not decolourise when exposed to light. Tube 3 (leaf extract + DCPIP in the dark) no colour change. It can therefore be inferred that the loss of colour in tube 1 is due to the effect of light on the extract. Tube 4 (leaf extract + distilled water) no colour change. This shows that the extract does not change colour in the light. It acts as a colour standard for the extract without DCPIP. Tube 5 (supernatant + DCPIP) no colour change if the supernatant is clear; if it is slightly green there may be some decolouring. The results should indicate that the light-dependent reactions of photosynthesis are restricted to the chloroplasts that have been extracted.

2 Carbon dioxide will have no effect, because it is not involved in the light-dependent reactions.

3 Students should describe a procedure in which light intensity is varied but temperature is controlled.

Health and safety checked, September 2008

Related experiment

Investigating photosynthesis using immobilised algae

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What Are the Roles of Chlorophyll A & B?

What Is the Role of Pigments in Photosynthesis?

Ever wonder why plants are green? The color is due to a specialized organic molecule found within plant cells called chlorophyll . Chlorophyll absorbs certain wavelengths of light and reflects green light. When that reflected light enters your eyes, you perceive plants as green.

You may be wondering, why does chlorophyll absorb and reflect light?

TL;DR (Too Long; Didn't Read)

Chlorophyll's role is to absorb light for photosynthesis. There are two main types of chlorophyll: A and B. Chlorophyll A's central role is as an electron donor in the electron transport chain. Chlorophyll B's role is to give organisms the ability to absorb higher frequency blue light for use in photosynthesis.

What Is Chlorophyll?

Chlorophyll is a pigment or a chemical compound that absorbs and reflects specific wavelengths of light. Chlorophyll is found within cells in the thylakoid membrane of an organelle called the chloroplast .

Pigments such as chlorophyll are useful for plants and other autotrophs , which are organisms that create their energy by converting light energy from the sun into chemical energy. The primary role of chlorophyll is to absorb light energy for use in a process called photosynthesis — the process by which plants, algae and some bacteria convert light energy from the sun into chemical energy.

Light is made up of bundles of energy called photons . Pigments like chlorophyll, through a complex process, pass photons from pigment to pigment until it reaches an area called the reaction center . After photons reach the reaction center, the energy is converted into chemical energy to be used by the cell.

The main pigment used by organisms for photosynthesis is chlorophyll. There are six distinct types of chlorophyll , but the main types are chlorophyll A and chlorophyll B .

Role of Chlorophyll A

The primary pigment of photosynthesis is chlorophyll A. Chlorophyll B is an accessory pigment because it is not necessary for photosynthesis to occur. All organisms that perform photosynthesis have chlorophyll A, but not all organisms contain chlorophyll B.

Chlorophyll A absorbs light from the orange-red and violet-blue areas of the electromagnetic spectrum. Chlorophyll A transfers energy to the reaction center and donates two excited electrons to the electron transport chain .

The central role of chlorophyll A is as a primary electron donor in the electron transport chain . From there on, the energy from the sun will ultimately become chemical energy that can be used by the organism for cellular processes.

Role of Chlorophyll B

One of the main distinctions between Chlorophyll A and B is in the color of the light that they absorb. Chlorophyll B absorbs blue light. Chlorophyll B’s central role is to expand the absorption spectrum of organisms.

That way, organisms can absorb more energy from the higher frequency blue light part of the spectrum. The presence of chlorophyll B in cells helps organisms convert a wider range of the energy from the sun into chemical energy.

Having more chlorophyll B in chloroplasts of cells is adaptive. Plants that receive less sunlight have more chlorophyll B in their chloroplasts. An increase in chlorophyll B is an adaption to the shade, as it allows the plant to absorb a broader range of wavelengths of light. Chlorophyll B transfers the extra energy it absorbs to chlorophyll A.

Structural Differences Between Chlorophyll A and B

Both Chlorophyll A and B have very similar structures. Both are “tadpole” shaped due to a hydrophobic tail and hydrophilic head. The head consists of a porphyrin ring, with magnesium in the center. The porphyrin ring of chlorophyll is where light energy is absorbed.

Chlorophyll A and B differ in only one atom in a side-chain on the third carbon. In A, the third carbon is attached to a methyl group whereas, in B, the third carbon is attached to an aldehyde group.

Outline of Differences Between Chlorophyll A and B

Chlorophyll A:

• The primary pigment of photosynthesis
• Absorbs violet-blue and orange-red light
• Blueish green in color
• Methyl group(-CH3) at the third carbon

Chlorophyll B:

• An accessory pigment of photosynthesis
• Absorbs blue light
• Olive green in color
• Aldehyde group (-CHO) at the third carbon

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Investigating the Need for Chlorophyll, Light & Carbon Dioxide ( Cambridge O Level Biology )

Revision note.

Investigating the Need for Chlorophyll

• The occurrence of photosynthesis can be demonstrated by observing the presence of its products
• Although plants make glucose in photosynthesis, leaves cannot be tested for its presence as the glucose is quickly used or converted into other substances
• Starch is stored in chloroplasts, where photosynthesis occurs, so testing a leaf for starch is a reliable indicatorthat photosynthesis is taking place
• A leaf is dropped in boiling water to kill the cells and break down cell membranes
• Care must be taken at this stage as ethanol is extremely flammable ; the Bunsen burner should be turned off before any ethanol is poured into the boiling tube
• A water bath could be used to avoid the need for naked flames
• The leaf is dipped in boiling water to soften it
• The leaf is spread out on a white tile and covered with iodine solution
• In a green leaf, the entire leaf will turn blue-black as photosynthesis is occurring in all areas of the leaf
• The areas that have no chlorophyll remain orange-brown as no photosynthesis is occurring here and so no starch is stored

Testing a leaf for starch diagram

Iodine can be used to test for the presence of starch in different parts of a leaf

Investigating the Need for Light

• This ensures that any starch already present in the leaves will be used up and will not affect the results of the experiment
• Partially cover a leaf of the plant with aluminium foil and place the plant in sunlight for a further 24 hours
• Remove the leaf and test for starch as shown above
• The area of the leaf covered with aluminium foil will remain orange-brown , as it did not receive any sunlight and could not photosynthesise, while the area exposed to sunlight will turn blue-black
• This demonstrates that light is necessary for photosynthesis and the production of starch

Investigating the Need for Carbon Dioxide

• Remove starch from two plants by placing them in the dark for 24 hours
• Sodium hydroxide will absorb carbon dioxide from the surrounding air
• Water here acts as an experimental control , demonstrating that it is the presence of the sodium hydroxide, and not any other factor, that is affecting the plant
• Place both plants in bright light for 24 hours
• Test both plants for starch using iodine, as shown above
• The leaf from the plant placed near sodium hydroxide will remain orange-brown , as a lack of carbon dioxide will prevent it from photosynthesising
• The leaf from the plant placed near water should turn blue-black as it had all necessary materials for photosynthesis

Experiment that demonstrates the need for carbon dioxide in photosynthesis diagram

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Experiments Related to Photosynthesis: Definition & Demonstration

Experiments Related to Photosynthesis : Green plants exhibit an autotrophic mode of nutrition. We all know that leaves are the site of photosynthesis. Leaves possess chlorophyll that traps the sunlight to synthesise food (glucose) by utilising inorganic raw materials, i.e., carbon dioxide and water. Oxygen is released as a by-product of photosynthesis. The glucose units combine and form a complex carbohydrate called the starch that remains stored in the plant cells for further utilisation.

Different experiments related to photosynthesis can be performed to demonstrate the utilisation of carbon dioxide, involvement of chlorophyll, presence of starch, and release of oxygen by the plant leaf subjected to perform photosynthesis. Let’s read the article to study the detailed procedure of different experiments related to photosynthesis.

What is Photosynthesis?

Photosynthesis is the process by which the chlorophyll-containing cells synthesise food (glucose) from carbon dioxide and water in the presence of sunlight. Photosynthesis is the process of conversion of solar energy into chemical energy.

Chloroplasts – The Site of Photosynthesis

The leaves are the parts of plants that participate in the process of photosynthesis. In herbaceous plants, green and flexible stems also perform photosynthesis. The mesophyll cells of leaves contain chloroplasts that possess a green coloured pigment called chlorophyll to trap the sunlight for photosynthesis. Thus, inside the mesophyll cells of leaves, chloroplasts are the site of photosynthesis.

Events Occuring During Photosynthesis

The following events occur during the process of photosynthesis:

• Absorption of water from the soil through root hairs.
• Diffusion of Carbon dioxide through stomata.
• Absorption of light energy by chlorophyll.
• Production of glucose.
• Conversion of glucose into starch.
• Release of oxygen

Conditions Necessary For Photosynthesis

The following conditions are necessary for photosynthesis:

• Chlorophyll
• Carbon dioxide

The effect of the presence and absence of these factors on the process of photosynthesis can be proved by performing certain experiments related to photosynthesis.

Experiments to Demonstrate the Requirement of Materials for Photosynthesis

1. theoretical demonstration for the requirement of chlorophyll during photosynthesis:.

I. Aim: Chlorophyll is a green coloured pigment that traps the sunlight to proceed with the synthesis of food by leaves by utilising carbon dioxide and water. To demonstrate the requirement of chlorophyll in photosynthesis, the following experiment is performed.

II. Materials required: Variegated leaf, water, alcohol, iodine solution.

III. Procedure: a). Take a plant with variegated leaves: The leaves of the Coleus, Croton plant can be taken. The leaves of these plants have yellow and green patches, and The green patches contain chlorophyll. b). Destarching the plant: The plant is placed in a dark room to prevent photosynthesis and thereby allows the plant to utilise the food that is stored in the form of starch. c). Removal of chlorophyll: The leaf is boiled in the water, followed by boiling of leaf in the alcohol (place the beaker containing alcohol and leaf in a water bath) till it becomes pale white, i.e., the chlorophyll is removed, and the alcohol turns green. The leaf is then washed with warm water so that it becomes soft. d). A few drops of iodine solution are poured over the leaf.

IV. Observation: The green coloured portion of the leaf that turns colourless in the alcohol now turns into blue-black patches after putting the iodine, while the yellow-coloured portion of the leaf does not show any colour change.

V. Conclusion: The results obtained from the iodine test prove that chlorophyll is necessary for the process of photosynthesis. The blue-black colour is due to the presence of starch. As in the yellow portion, no photosynthesis takes place, so there is no colour change due to the addition of iodine.

Fig: Experiment to demonstrate the necessity of chlorophyll for photosynthesis

2. Theoretical Demonstration for the Requirement of Sunlight During Photosynthesis:

I. Aim: All living beings utilise energy for several life processes. Likewise, plants utilise light energy for the process of photosynthesis. The requirement of sunlight can be demonstrated by following the below-mentioned steps:

II. Materials required: Green plant, black paper or aluminium foil, water, alcohol, iodine solution.

III. Procedure: a). Destarching the plant The plant can be destarched naturally by placing it in the complete dark for about 2-4 days so that all the stored starch is utilised by plants to fulfil its food and energy requirement in the absence of photosynthesis. b). Covering one of the leaves with black paper The destarched plant is then placed in the sunlight for about 2-4 days by covering any of its leaves with black paper or aluminium foil. Since the black colour absorbs the maximum amount of sunlight and therefore obstructs the pathway of light to the leaf surface, therefore black paper is used to cover the leaf. c). Boiling of covered leaf in water The covered and uncovered leaves are immersed in the boiled water before testing for the starch because immersing the leaf in boiled water breaks down the cell membranes of the mesophyll cells and makes the leaf more permeable to the iodine solution. d). Removal of chlorophyll Since chlorophyll interferes in the test for starch due to its green colour, therefore it is necessary to remove the chlorophyll to get the appropriate findings of the experiment. Chlorophyll removal involves the boiling of leaf in water then into alcohol and further washed with hot water to soften it. e). Test for the starch The covered and processed leaf is further tested for the presence of starch by adding 2-3 drops of iodine on the leaf surface.

III. Observation: It will be observed that the leaf does not show any colour change. However, an uncovered leaf gives a positive result for the presence of starch by changing its colour to blue-black.

IV. Conclusion: This shows that the leaves that are exposed to sunlight could only perform photosynthesis, while the covered leaf could not perform photosynthesis due to the absence of sunlight.

Fig: Experiment demonstrating the necessity of sunlight

3. Theoretical Demonstration for the Requirement of Carbon Dioxide During Photosynthesis

I. Aim: Carbon dioxide is the waste product of respiration that is utilised in the process of photosynthesis. To demonstrate the requirement of carbon dioxide the following steps are performed:

II. Material required: Two green potted plants, bell jar, alcohol, water, potassium hydroxide, iodine solution.

III. Procedure: a). Destarching of plant Plants can be destarched by keeping them in the dark for about 2 days. In this experiment, two destarched plants are taken. b). Designing the artificial boundaries for plant The two plants are individually placed on separate glass plates and are covered separately with a bell jar to restrict their boundaries within the surrounding area. c). Role of potassium hydroxide Potassium hydroxide is a carbon dioxide absorbent. It is placed with any of the potted and covered plants that absorb the carbon dioxide in its vicinity. The setup should be airtight to ensure to restrict the further entry of carbon dioxide in the jar. d). Removal of chlorophyll The chlorophyll interferes in the test for starch due to its green colour. Therefore it is necessary to remove the chlorophyll from the leaves of both plants to get the appropriate findings of the experiment. Chlorophyll removal involves the boiling of leaf in water then into alcohol and further washed with hot water to soften it. e). Test for the presence of starch Both the experimental setup are tested for the presence of starch by putting 2-3 drops of iodine solution on the leaf of both plants from which the chlorophyll has been removed.

III. Observation: It has been observed that the leaf of the plant that is placed in the bell jar along with potassium hydroxide will not show any colour change, while the other placed alone in the bell jar shows the presence of starch in its leaves by turning the colour into blue-black.

IV. Conclusion: Since the potassium hydroxide crystals absorb the available carbon dioxide present in one of its jars, therefore photosynthesis does not occur. This proves that carbon dioxide is necessary for photosynthesis.

Fig: Experiment demonstrating the necessity of carbon dioxide

Experiment to Demonstrate the Production of Substances in Photosynthesis

1. theoretical demonstration for the presence of starch.

I. Aim: Plants utilise inorganic raw materials, i.e., water and carbon dioxide, to synthesise organic materials called glucose. These glucose units combine to form a complex carbohydrate called starch that remains stored in the stroma of the chloroplast and in the cytoplasm of the leaves. The iodine test is prominently performed to test the presence of starch that is discussed as follows:

II. Material required: Green plant, iodine solution, dropper.

III. Procedure: a). The healthy plant is placed in the sunlight and left undisturbed for about one day before this experiment. b). Now, the chlorophyll is removed from the leaf by boiling the leaf in water then into alcohol and further washed with hot water to soften it. c). The leaf of the plant is then tested for the presence of starch by adding 2-3 drops of iodine solution with the help of a dropper to the leaf surface.

III. Observation: It will be observed that the colour of the leaf turns blue-black.

IV. Conclusion: The blue-black colour ensures the presence of starch and therefore ensures that photosynthesis takes place in the leaf.

2. Theoretical Demonstration for the release of oxygen during photosynthesis

I. Aim:  Plants release oxygen during photosynthesis that is utilised in the process of respiration. To ensure the release of oxygen, the following steps should be followed:

II. Material required: An aquatic plant, sodium bicarbonate, water, beaker, funnel.

III. Procedure: a). Design the experimental setup A beaker full of water is taken, and any aquatic plant such as Hydrilla is placed at the bottom of the beaker. The plant is further covered with the inverted funnel. An inverted test tube is placed over the funnel. b). Plant subjected to perform photosynthesis The experimental setup is then placed in the sunlight to facilitate the process of photosynthesis to occur in the plant. Sodium bicarbonate is added to the water to provide carbon dioxide that is needed for photosynthesis. c). Observation: A number of air bubbles can be observed at the top closed end of the test tube. Since there is no place for the oxygen to escape from the inverted test tube. IV. Conclusion: The presence of bubbles ensures that oxygen is released during photosynthesis. We can test for the presence of oxygen bubbles by taking a glowing splinter in contact with the air bubbles.

Fig: Experiment demonstrating the release of oxygen

Photosynthesis is the process of synthesising food by utilising carbon dioxide and water in the presence of sunlight. The leaves are the kitchen factories of the plant as they contain chlorophyll in their mesophyll cells to absorb the sunlight. The importance of chlorophyll can be tested by using variegated leaves that show only green patches of the leaves can absorb sunlight since they contain chlorophyll and perform photosynthesis. On the other hand, if a small portion of the entire green leaf is covered with black paper, it does not perform photosynthesis due to the absence of sunlight.

The presence of starch can be confirmed by performing an iodine test. The release of oxygen can be tested by taking an aquatic plant placed in a water-filled beaker along with the inverted funnel and test tube that are placed one after another over the plant and later tested for the release of oxygen. By studying these experiments, we came to know about the importance of carbon dioxide, sunlight, and water in a plant for photosynthesis. These experiments also ensure the type of food synthesised by plants and the release of life-supporting gas.

Frequently Asked Questions (FAQs) On Experiments Related to Photosynthesis

Q.1. Why only Hydrilla is used in photosynthesis experiments? Ans: Hydrilla is a small, aquatic plant that is easy to handle and able to breathe in the water, therefore used in the demonstration of the release of oxygen during photosynthesis.

Q.2. How can we destarch the plant? Ans: We can destarch the plant by keeping the plant in the dark for about one to two days.

Q.3. How do you decolourise the leaf? Ans: We can decolourise then placing it into a beaker containing alcohol and boiling the leaf in a water bath.

Q.4. How do you test the presence of starch in a leaf? Ans: The presence of starch can be tested by putting 2-3 drops of iodine on the leaf. If the colour turns blue-black, it ensures the presence of starch in the leaf.

Q.5. Which experiment proves that carbon dioxide is essential for photosynthesis? Ans: Moll’s half-leaf experiment proves that carbon dioxide is essential for photosynthesis.

We hope this detailed article on experiments related to photosynthesis helped you in your studies. If you have any doubts, queries or suggestions regarding this article, feel to ask us in the comment section and we will be more than happy to assist you. Happy learning!

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July 1, 1965

The Role of Chlorophyll in Photosynthesis

The pigments of plants trap light energy and store it as chemical energy. They do this by catalyzing an oxidation-reduction process in which hydrogen atoms are boosted from water to organic matter

By Eugene I. Rabinowitch & Govindjee

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• Published: 18 October 1958

Mechanism of Chlorophyll Action in Photosynthesis

• WOLF VISHNIAC 1 &
• IRWIN A. ROSE 1  

Nature volume  182 ,  pages 1089–1090 ( 1958 ) Cite this article

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THE use of tritiated water affords a sensitive means of answering at least one question about early photosynthetic events : Do any of the hydrogen atoms of the chlorophyll molecule intervene in the electron transport chain between water and oxidant ? It has already been established 1 that all the hydrogen–carbon bonds of the chlorophyll molecule are sufficiently stable to prevent hydrogen exchange in neutral organic solvents in the dark; a tracer experiment is therefore feasible. At least one current school of thought maintains that the participation of hydrogen of the chlorophyll molecule in a chemical reaction is a requisite step in the electron transfer which originates in photoactivated chlorophyll 2 . Experiments in which Chlorella or Scenedesmus cells were illuminated in tritiated water have led us to the conclusion that some hydrogen of chlorophyll is activated during photosynthesis. A similar light-dependent and heat-sensitive activation of chlorophyll a and bacteriochlorophyll has been observed in a variety of cell-free preparations. The position in the chlorophyll molecule which is photochemically labilized is tentatively concluded to be C 10 .

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Data from: Water controls the divergent responses of terrestrial plant photosynthesis under nitrogen enrichment

He, Yicheng 1 ; Geng, Yiyi 1 ; Han, Bing 1 ; Shi, Lina 1 ; Liu, Kesi 1 ; Shao, Xinqing 1

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• China Agricultural University

Cite this dataset

He, Yicheng et al. (2024). Data from: Water controls the divergent responses of terrestrial plant photosynthesis under nitrogen enrichment [Dataset]. Dryad. https://doi.org/10.5061/dryad.p5hqbzkz0

Quantifying leaf photosynthetic response to nitrogen (N) deposition under contrasting water conditions is important for reliably modeling terrestrial carbon and water cycles, a topic that has not been well understood.

Here, we analyzed 737 paired observations from 102 publications to assess the response of eleven leaf photosynthesis-related properties to N addition under different water conditions. Our research includes global experiments, with 19 conducted in the field and 83 in greenhouses. Treatments without water reduction were classified as 'no water change', while those with reduced water or precipitation causing physiological drought were categorized as 'drought'.

We found that, compared to the control group, N addition significantly increased leaf photosynthetic rate ( P n ; 20.9%), leaf transpiration ( E ; 8.3%), and stomatal conductance ( g s ; 14.1%). However, the decrease in P n (-11.6%), E (-24.7%), and g s (-23.9%) under the combination of N addition and drought indicated that N addition could not offset the negative effects of drought. Furthermore, N addition significantly enhanced water use efficiency (WUE) by 19.8% under no water change conditions and by 21.1% under drought conditions. Within plant functional groups, herbaceous species exhibited greater susceptibility to N addition than woody species, especially under drought conditions. The observed patterns of increase in P n with longer experimental duration and WUE with higher N rate under drought conditions showed that plants would gradually adapt to long-term water stress in the context of N deposition. Furthermore, our results showed that drought could strengthen the correlations between leaf photosynthetic properties. Lastly, our study demonstrated that N addition and drought significantly impacted leaf nitrogen content and SPAD, respectively, and further affected g s , P n , and WUE.

Synthesis : Our results emphasize the crucial role of water conditions in shaping the response of leaf photosynthesis to nitrogen (N) enrichment, and also acknowledge the significance of leaf functional traits in regulating the dynamics of leaf photosynthetic processes.

README: Data from: Water controls the divergent responses of terrestrial plant photosynthesis under nitrogen enrichment

https://doi.org/10.5061/dryad.p5hqbzkz0

Description of the data and file structure

The data of 7 leaf photosynthetic properties were extracted, including

• leaf photosynthetic rate ( Pn , µmol m−2 s−1),
• leaf transpiration ( E , µmol m−2 s−1),
• stomatal conductance ( gs , mol m−2 s−1),
• optimal photochemical efficiency of PSII ( Fv/Fm ),
• maximum rate of carboxylation by Rubisco ( Vcmax , µmol m−2 s−1),
• maximum electron transparent rate ( Jmax , µmol m−2 s−1),
• water use efficiency ( WUE , calculated from gas exchange measurement of A and gs/E).

Additionally, SPAD was not the only indicator of leaf chlorophyll, it also included data on actual leaf chlorophyll content . Considering the majority of the observations were SPAD-based, we used SPAD to represent chlorophyll in our study.Moreover, 4 leaf photosynthesis-related traits and 1 root trait that may indirectly impact leaf photosynthesis were complementally chosen, including 8. leaf nitrogen content ( LNC , g m-2), 9. Soil and Plant Analyzer Development ( SPAD,  a proxy for leaf chlorophyll content, no unit), 10. leaf area ( LA , cm2), 11. superoxide dismutase ( SOD , U h–1 mg–1 protein). 12. Root length ( RL , cm)

Files and variables

File: dataset_upload.csv.

Description

The dataset for Water controls the divergent responses of terrestrial plant photosynthesis under nitrogen enrichment . The list of all references was exhibited in the Supporting Information (Reference S1) .

Additionally, some unavailable values are replaced by "null" in this dataset. Data users can use the formulation: ln*RR*<-ln( Xtrt / Xck ) to calculate the response ratio. And the values of each variable under control and treatment conditions must be carefully recorded to ensure accurate calculations. This formulation assumes that the variables under treatment ( Xtrt ) and control ( Xck ) conditions are measured consistently and their ratio can be appropriately log-transformed to derive the response ratio, ln*RR*. To ensure reproducibility and clarity, data users should notice the conditions under which measurements were taken. Furthermore, appropriate statistical methods should be applied to analyze the data, including checking for normality of distributions and homogeneity of variance before applying the log transformation. This approach will help accurately interpret the treatment's effects relative to the control. And  X.cn  , X.tn , X.csd , and  X.tsd  could be calculated for the weight of each variable via two major methods (Tian et al., 2019; Wang et al., 2023).

Tian D, Reich PB, Chen HYH, Xiang Y, Luo Y, Shen Y, Meng C, Han W, Niu S. 2019. Global changes alter plant multi-element stoichiometric coupling. New Phytol 221 (2): 807-817.

Wang Z, Xing A, Shen H. 2023. Effects of nitrogen addition on the combined global warming potential of three major soil greenhouse gases: A global meta-analysis. Environmental Pollution 334 : 121848.

Variables

• number: The number of observation
• references: The abbreviation of the reference 
• num_reference: The number of the reference
• study: The number of the experiment
• map1: An index for map building
• latitude: The latitude of the experiment
• longitude: The longitude of the experiment
• TN: Soil total nitrogen
• Greenhouse.field: Experimental setting place
• plant.year: The age of a woody plant
• Growth.form: Plant growth form
• D.form: The drought setting form
• water: The change of water condition. Specificall, it represents the relative change in water conditions under a specific treatment compared to the control group. Formulation= ( Water trt - Water ck ) /  Water ck
• N.rate: The rate of N addition
• Duration..yr.: The experiment duration
• SPAD.ck: SPAD in control treatment
• SPAD.csd: The standard error of SPAD in control treatment
• SPAD.cn: The replication of SPAD in control treatment
• SPAD.treat: SPAD in experimental treatment
• SPAD.tsd: The standard error of SPAD in experimental treatment
• SPAD.tn: The replication of SPAD in experimental treatment
• Pn.ck: Leaf photosynthetic rate in control treatment
• Pn.csd: The standard error of leaf photosynthetic rate in control treatment
• Pn.cn: The replication of leaf photosynthetic rate in control treatment
• Pn.treat: Leaf photosynthetic rate in experimental treatment
• Pn.tsd: The standard error of leaf photosynthetic rate in experimental treatment
• Pn.tn: The replication of leaf photosynthetic rate in experimental treatment
• SOD.ck: SOD in experimental treatment
• SOD.csd: The standard error of SOD in control treatment
• SOD.cn: The replication of SOD in control treatment
• SOD.treat: SOD in experimental treatment
• SOD.tsd: The standard error of SOD in experimental treatment
• SOD.tn: The replication of SOD in experimental treatment
• Jmax.ck: Jmax in control treatment
• Jmax.csd: The standard error of Jmax in control treatment
• Jmax.cn: The replication of Jmax in control treatment
• Jmax.treat: Jmax in experimental treatment
• Jmax.tsd: The standard error of Jmax in experimental treatment
• Jmax.tn: The replication of Jmax in experimental treatment
• Vcmax.ck: Vcmax in control treatment
• Vcmax.csd: The standard error of Vcmax in control treatment
• Vcmax.cn: The replication of Vcmax in control treatment
• Vcmax.treat: Vcmax in experimental treatment
• Vcmax.tsd: The standard error of Vcmax in experimental treatment
• Vcmax.tn: The replication of Vcmaxin experimental treatment
• gs.ck: Stomatal conductance in control treatment
• gs.csd: The standard error of stomatal conductance in control treatment
• gs.cn: The replication of stomatal conductance in control treatment
• gs.treat: Stomatal conductance in experimental treatment
• gs.tsd: The standard error of stomatal conductance in experimental treatment
• gs.tn: The replication of stomatal conductance in experimental treatment
• LA.ck: LA in control treatment
• LA.csd: The standard error of LA in control treatment
• LA.cn: The replication of LA in control treatment
• LA.treat: LA in experimental treatment
• LA.tsd: The standard error of LA in experimental treatment
• LA.tn: The replication of LA in experimental treatment
• E.ck: E in control treatment
• E.csd: The standard error of E in control treatment
• E.cn: The replication of E in control treatment
• E.treat: E in experimental treatment
• E.tsd: The standard error of E in experimental treatment
• E.tn: The replication of E in experimental treatment
• WUE.ck: WUE in control treatment
• WUE.csd: The standard error of WUE in control treatment
• WUE.cn: The replication of WUE in control treatment
• WUE.treat: WUE  in experimental treatment
• WUE.tsd: The standard error of WUE in experimental treatment
• WUE.tn: The replication of WUE in experimental treatment
• LNC.ck: LNC in control treatment
• LNC.csd: The standard error of LNC in control treatment
• LNC.cn: The replication of LNC in control treatment
• LNC.treat: LNC in experimental treatment
• LNC.tsd: The standard error of LNC in experimental treatment
• LNC.tn: The replication of LNC in experimental treatment
• Fv.Fm.ck: Fv/Fm in control treatment
• Fv.Fm.csd: The standard error of Fv/Fm in control treatment
• Fv.Fm.cn: The replication of Fv/Fm in control treatment
• Fv.Fm.treat: Fv/Fm in experimental treatment
• Fv.Fm.tsd: The standard error of Fv/Fm in experimental treatment
• Fv.Fm.tn: The replication of Fv/Fm in experimental treatment
• RootLength.ck: Root length in control treatment
• RootLength.csd: The standard error of root length in control treatment
• RootLength.cn: The replication of root length in control treatment
• RootLength.treat: Root length in experimental treatment
• RootLength.tsd: The standard error of root length in experimental treatment
• RootLength.tn: The replication of root length in experimental treatment

Code/software

All meta-analyses were conducted in R software (version 4.0.5; R Core Team, 2023) and figures were generated using the ‘ ggplot2 ’ package (Ginestet, 2011).

Note: The code was also uploaded to Zenodo through this repository. See Software related works.

We systematically searched the journal articles via Web of Science, Google Scholar, and China National Knowledge Infrastructure, using the following keywords: “drought” or “water stress” or “water deficit” or “reduced precipitation” or “reduced rainfall” and “nitrogen addition” or “N addition” and “leaf photosynthesis” or “plant photosynthesis”. The preliminary screened articles were then refined based on the following criteria:

1) Studies that did not investigate both the individual and combined effects of drought and N addition on leaf photosynthesis were excluded.

2) Experiments that manipulated only water or N availability or warming and eCO 2 simultaneously were not considered.

3) Control and experimental plots should be established in the same location or soil condition to ensure consistency in microclimate and soil nutrient conditions.

4) The studies we selected contained at least one of the following target variables: leaf photosynthetic rate ( P n ), stomatal conductance ( g s ), water use efficiency (WUE), or optimal photochemical efficiency of PSII ( F v / F m ).

National Natural Science Foundation of China , Award: 32171685

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Evaluation of the Reliability of the CCM-300 Chlorophyll Content Meter in Measuring Chlorophyll Content for Various Plant Functional Types

Joelie m. van beek.

1 Department of Forest and Wildlife Ecology, University of Wisconsin-Madison, 1630 Linden Drive, Madison, WI 53706, USA; ude.csiw@2keebnavmj (J.M.V.B.); ude.csiw@698gnawz (Z.W.); [email protected] (K.R.K.); ude.csiw@dnesnwotp (P.A.T.)

Zhihui Wang

2 Guangdong Provincial Key Laboratory of Remote Sensing and Geographical Information System, Guangdong Open Laboratory of Geospatial Information Technology and Application, Guangzhou Institute of Geography, Guangdong Academy of Sciences, Guangzhou 510070, China

Kyle R. Kovach

Philip a. townsend, associated data.

Detailed sample information and chlorophyll content measurements are all available online at Zenodo: https://zenodo.org/doi/10.5281/zenodo.10581895 (accessed on 29 January 2024).

Chlorophyll fluorescence is a well-established method to estimate chlorophyll content in leaves. A popular fluorescence-based meter, the Opti-Sciences CCM-300 Chlorophyll Content Meter (CCM-300), utilizes the fluorescence ratio F735/F700 and equations derived from experiments using broadleaf species to provide a direct, rapid estimate of chlorophyll content used for many applications. We sought to quantify the performance of the CCM-300 relative to more intensive methods, both across plant functional types and years of use. We linked CCM-300 measurements of broadleaf, conifer, and graminoid samples in 2018 and 2019 to high-performance liquid chromatography (HPLC) and/or spectrophotometric (Spec) analysis of the same leaves. We observed a significant difference between the CCM-300 and HPLC/Spec, but not between HPLC and Spec. In comparison to HPLC, the CCM-300 performed better for broadleaves (r = 0.55, RMSE = 154.76) than conifers (r = 0.52, RMSE = 171.16) and graminoids (r = 0.32, RMSE = 127.12). We observed a slight deterioration in meter performance between years, potentially due to meter calibration. Our results show that the CCM-300 is reliable to demonstrate coarse variations in chlorophyll but may be limited for cross-plant functional type studies and comparisons across years.

1. Introduction

Chlorophyll is an essential compound within the chloroplast, the organelle responsible for housing the photosynthetic process that gives plants their green color. As a vital component of photosynthesis, chlorophyll captures light energy and converts it into chemical energy, which is used to yield glucose and oxygen [ 1 ]. Photosynthetic efficiency is impacted by pigment concentrations [ 2 , 3 , 4 ], thus quantification of chlorophyll content provides insights into plant growth [ 5 ] and photosynthetic functioning [ 6 , 7 ], as well as plant response to environmental [ 8 , 9 ] and climatic [ 10 ] interactions.

Increasingly, there is a demand for large volumes of rapidly collected chlorophyll measurements, particularly for agronomic applications requiring rapid assessments for nutrient or disease management [ 11 , 12 ]. However, laboratory methods for quantifying pigments, such as high-performance liquid chromatography, may be logistically infeasible for these applications due to both expense and the need for special handling of samples. Chlorophyll can also be estimated from remote sensing imagery [ 13 , 14 ], but calibration and validation of remote sensing maps require large sample sizes, often collected within a short time window to match remote sensing observations [ 15 ].

To meet these demands, various types of portable chlorophyll meters have been developed to non-destructively estimate leaf chlorophyll content in situ. Most of these meters infer the chlorophyll content by measuring leaf spectral characteristics, especially in wavelengths between 400 nm and 1000 nm that have distinct pigment absorption, reflectance, or fluorescence features.

Absorptance meters, such as the SPAD-502 chlorophyll meter (Konica Minolta Sensing, Tokyo, Japan) and Opti-Sciences CCM-200plus Chlorophyll Content Meter (Opti-Sciences, Hudson, NH, USA), measure leaf absorptance at light wavelengths near 650 nm and 940 nm (red and near-infrared, respectively). Absorptance meters do not provide a direct output of chlorophyll content, but instead utilize the ratio of transmittance (which yields a ‘chlorophyll content index’ or ‘SPAD unit’, for example) to produce a relative chlorophyll content measurement, which is the sole output of absorptance meters. Regression analyses can be the basis to convert these measurements to units of chlorophyll content [ 16 ]. Reflectance meters, like the UniSpec Spectral Analysis System (PP Systems, Amesbury, MA, USA), record leaf reflectance across many wavelengths (ultraviolet, visible, near-infrared). The output of reflectance meter measurements provides multiple data points, allowing for extensive analyses from a single leaf scan.

Chlorophyll meters based on leaf absorptance/reflectance features suffer from a few drawbacks. First, there is a documented decrease in the accuracy of chlorophyll estimations when leaf chlorophyll content increases due to saturation of absorption [ 17 ]. Additionally, the indices generated by such meters require careful evaluation through time (e.g., assessment of calibration consistency), and across species and phenology [ 18 ]. Finally, meter measurements are affected by factors other than chlorophyll content, such as differences in leaf structure [ 19 ] and structural materials of cell walls [ 20 ].

Leaf fluorescence measurements have emerged as an alternative to absorptance/reflectance for quantifying chlorophyll content in leaves. Light that is not absorbed by chlorophyll for photochemistry is re-emitted as heat or fluorescence. Fluorescence occurs during de-excitation after a fluorophore is transitioned into a state of excitement due to absorption of light [ 21 , 22 , 23 ]. Previous studies have shown that the strength of the fluorescence signal closely tracks the leaf chlorophyll content [ 24 , 25 , 26 ].

Unlike absorptance- and reflectance-based meters that measure light from an external source, fluorescence-based meters measure the light re-emitted from the leaf. Fluorescence meters, also referred to as fluorometers, measure peak wavelengths in the regions of 685–690 nm (red) and 730–740 nm (far-red, near-infrared). Fluorescence ratios of red and far-red regions [ 23 , 27 , 28 ] enable direct estimates of chlorophyll content based on regression equations. For example, the widely used Opti-Sciences CCM-300 Chlorophyll Content Meter (hereafter referred to as CCM-300) measures emission ratios of red light at 700 nm to far-red emission at 735 nm (chlorophyll fluorescence ratio F735/F700) and estimates chlorophyll content (mg/m 2 ) based on equations from Gitelson et al. [ 26 ]. To obtain consistent fluorescence measurements, the instrument is calibrated to a purple transparent fluorescent slide with a predetermined value (0.8 for our unit) before each measurement session.

The CCM-300, a portable, non-destructive device, has gained wide usage in field biology due to its ease of use and ability to provide rapid and repeatable measurements. Although the meter has been used to assess plant and ecosystem health in various studies [ 29 , 30 , 31 ], the accuracy of the instrument has rarely been tested. Additionally, Gitelson’s [ 26 ] equations used by the CCM-300 are based exclusively on broadleaf species, suggesting the need for testing on other leaf physiognomic types. Indeed, the Opti-Sciences CCM-300 Chlorophyll Content Meter Operation Manual [ 32 ] encourages users to develop unique calibration parameters for vegetation types not represented by the Gitelson [ 26 ] equations. However, despite its popularity, the validation of the CCM-300’s reliability across plant functional types is scarce, and we do not know of any published alternative equations for non-broadleaf species. As far as we are aware, our study is the first to evaluate the performance of the Opti-Sciences CCM-300 Chlorophyll Content Meter.

In this study, we assess the reliability of the Opti-Sciences CCM-300. We aim to (1) compare CCM-300 measurements against traditional laboratory chemistry analyses such as spectrophotometry and high-performance liquid chromatography (HPLC), (2) analyze meter consistency between plant functional types, and (3) determine meter reliability across years, assessing whether there is degradation in estimates as the instrument ages.

2. Materials and Methods

2.1. materials.

In this study, we used two datasets to assess the CCM-300 performance—one contains samples collected on the campus of the University of Wisconsin-Madison (UW-Madison) in 2018 purely for CCM-300 testing purposes, and the other is an opportunistic dataset with samples collected from 12 domains of the National Ecological Observatory Network (NEON) in 2018 and 2019 ( Figure 1 ). Although the NEON data were not gathered with our study in mind, they provided valuable and relevant information, enabling us to maximize the utility of available resources while producing meaningful insights.

Sample locations. D01–D019 stands for NEON Domain01–Domain019.

The UW-Madison dataset was collected in June 2018, right after the purchase of the CCM-300. We measured the chlorophyll content for 79 foliar samples (22 broadleaves and 57 conifers) using the CCM-300. For each sample, readings were taken from three different places on the leaf, and the average was recorded. After the measurements, the leaves were placed into zip-lock bags with a moist paper towel, sealed, and transported back to the laboratory in a cooler with ice. For conifer needles, we cut the middle section of each needle then scanned the area. For broadleaf species, we used hole punchers to collect 1 cm 2 leaf material. Following Zhang et al. [ 33 ], the sampled leaf material was immersed in a vial with N, N-dimethylformamide (DMF) and stored in a dark refrigerator (4 °C) until leaf chlorophylls were completely extracted. It took around five days to bleach most broadleaf samples. However, for all needles, but especially older ones, more time (~two weeks) was needed for complete extraction. The absorptance of the solvent at 663.8 nm and 646.8 nm was then measured using a Genesys 5 spectrophotometer (Thermo Electron Corp.: Waltham, MA, USA) and the chlorophyll content was estimated using the equations derived by Wellburn [ 34 ]. These measurements were referred to as laboratory spectrophotometry.

where C a is the content of chlorophyll a in µg/mL −1 , C b is the content of chlorophyll b in µg/mL −1 , v is the volume of the solvent (5 mL in this study), and s is the area of the leaf sample in cm 2 . C is the content of total chlorophyll in mg/m 2 .

To further validate the laboratory spectrophotometry measurements, we flash-froze leaf material from 44 samples (18 broadleaves and 26 conifers) out of the 79 samples in liquid nitrogen and transported them in a −20 °C freezer to the University of Minnesota-Twin Cities, where the chlorophyll content was measured using high-performance liquid chromatography (HPLC) (Agilent 1200 Series HPLC; Agilent Technologies, Santa Clara, CA, USA). HPLC methods are described by Schweiger et al. [ 35 ].

Samples from (NEON) were collected for a large-scale study that utilizes imaging spectroscopy to map foliar functional traits [ 36 ]. As part of the functional trait measurements, the same CCM-300 instrument was used to rapidly obtain leaf chlorophyll content in the field. Following the NEON sampling protocol [ 36 ], measurements were averaged over five leaves in the field. Among these, two to three leaves were immediately flash-frozen to −80 °C in liquid nitrogen. The flash-frozen samples were then kept in a −20 °C freezer and transported to the University of Minnesota-Twin Cities for HPLC measurements. Samples measured using HPLC were referred to as ‘HPLC’.

This NEON dataset includes 244 samples (104 broadleaves, 129 conifers, 11 graminoids) and provides a valuable opportunity to evaluate the performance of the CCM-300 for different plant functional types across two years.

2.2. Methods

In each of our analyses, we used methods of laboratory chemistry (HPLC and/or laboratory spectrophotometry) as our “gold standard” due to the reliable, consistent results that these methods have yielded over time [ 34 , 37 ].

We first utilized a paired, two-tailed T-test to compare CCM-300 measurements to HPLC and/or laboratory spectrophotometry results, as well as measurements between HPLC and spectrophotometry. We then used linear regression to further explore the relationships between CCM-300 and HPLC measurements for different plant functional types and across years. Statistical analyses were performed using R (Stats library, R version 4.3.1).

Before all analyses, we removed outliers outside of the interval defined by Equation (4) [ 38 ] for each measurement type (CCM-300, HPLC, and laboratory spectrophotometry).

where Q1 is the first quartile found by calculating the median of the lower half of data presented in numerical order. Q3 is the third quartile found by calculating the median of the upper half of data presented in numerical order. IQR is the interquartile range, calculated by taking the difference between Q3 and Q1. Sample data after outlier removal are grouped by measurement type pairs in Table 1 .

Sample sizes for measurement type, year, and plant functional type presented in terms of paired sample data.

2.2.1. Paired, Two-Tailed T-Test

We first conducted the T-test for the 41 samples that were common across all three measurement types. We then performed the T-test for all the paired samples in the [CCM-300, HPLC] and [CCM-300, Spec] pairs. We calculated the mean absolute difference between measurement types for each pair following Equation (5).

where X and Y correspond to values of different measurements for a same sample, and n is the total number of samples per pair.

The significance level ( p -value) from the T-test is affected by the sample size. Due to dramatic differences in sample sizes for paired data ( Table 1 , 165 + 96 vs. 72 vs. 41), it is difficult to compare their T-test results (significance levels). To obtain more comparable results, we iteratively subsampled 41 samples randomly from [CCM-300, HPLC] and [CCM-300, Spec] pairs to match the sample size of [HPLC, Spec] pairs. We ran 1000 permutations of T-tests for each pair and calculated the p -values for each permutation.

2.2.2. Linear Regression Analysis

We created simple linear regression models to compare HPLC and CCM-300 measurements for different plant functional types with the CCM-300 measurements as the independent variable (x) and HPLC results as the response (y). We also performed the linear regression for broadleaf and conifer samples for 2018 and 2019 separately. We calculated the following evaluation metrics to quantify the quality of our regression models:

Correlation coefficient ( r ):

Root mean square error (RMSE):

where y i is observed values, y p is predicted values, and n is the number of observations.

where θ ^ is predicted values, θ is observed values, and n is the number of observations.

Our tests are a comparison of CCM-300 measurements to laboratory chemistry values. Because our data were gathered opportunistically, each analysis that we conducted does not include either HPLC or Spec data.

3.1. CCM-300 Measurements vs. Laboratory Chemistry Measurements

Statistics for the paired samples are summarized in Table 2 .

Sample size, mean (mg/m 2 ), standard deviation (mg/m 2 ), and median (mg/m 2 ) for pairs of [CCM-300, HPLC], [CCM-300, Spec], and [HPLC, Spec] measurements.

3.1.1. Paired T-Test for 41 Samples with All Three Measurements

When comparing samples that were subjected to each of the three measurement types ( n = 41), the data showed a higher median for CCM-300 values than both HPLC and laboratory spectrophotometry (Spec) ( Figure 2 ). The HPLC median was lower than the laboratory spectrophotometry median.

Chlorophyll concentrations (mg/m 2 ) by measurement type for paired and presented 41 samples common to all measurement types.

The results of a paired T-test restricted to these pairs showed that the difference between CCM-300 and HPLC was significant ( p = 2.20 × 10 −5 ). There was also a significant difference between CCM-300 and laboratory spectrophotometry ( p = 0.005). We did not see a significant difference between HPLC and laboratory spectrophotometry ( p = 0.32). The mean absolute difference for [CCM-300, HPLC], [CCM-300, Spec], and [HPLC, Spec] was 136.44 mg/m 2 , 131.49 mg/m 2 , and 101.99 mg/m 2 , respectively ( Figure 3 ). [HPLC, Spec] in particular is skewed to the right due to a few samples that have a very high absolute difference, spiking the average for this pair.

Distribution of absolute differences (mg/m 2 ) between specified measurement types for the common 41 samples. Mean absolute difference values are represented by the solid black line.

3.1.2. Paired T-Test of All Paired Samples

More paired measurements were available for analysis than the 41 common observations represented in Figure 2 . The patterns of distribution consisting of all available paired data ( Figure 4 ) were consistent with the distribution of common data points in Figure 2 . The results of the paired T-test for all available pairs showed that there was a significant difference between CCM-300 and HPLC ( p = 2.05 × 10 −5 ). There was also a significant difference between CCM-300 and laboratory spectrophotometry (Spec) ( p = 0.047). There was no significant difference between HPLC and laboratory spectrophotometry ( p = 0.32). The mean absolute difference for [CCM-300, HPLC], [CCM-300, Spec], and [HPLC, Spec] was 130.26 mg/m 2 , 123.73 mg/m 2 , and 101.99 mg/m 2 , respectively ( Figure 5 ). Each of the pairs was skewed to the right to some extent with [CCM-300, HPLC] and [HPLC, Spec] being impacted by particularly high absolute differences.

Chlorophyll concentration (mg/m 2 ) by measurement type of all paired data before permutations.

Distribution of the absolute differences (mg/m 2 ) between different measurement types for all paired data. Mean absolute differences are represented by the solid black line.

3.1.3. Iterative Subsampling for Randomized, Permutated Analysis

The distribution of p -values from 1000 permutations is shown in Figure 6 . We observed similar distribution patterns for p -values from [CCM-300, HPLC] and [CCM-300, Spec]. The p -value that occurred for [CCM-300, HPLC] most frequently after 1000 permutations was 0.03. The p -value that resulted most often for [CCM-300, Spec] after 1000 permutations was 0.047. In comparison, the p -value for the [HPLC, Spec] pair was 0.32.

Density plot of p -values for ( n = 41) common paired measurement type samples after 1000 subsampling permutations. The p -value for [HPLC, Spec], which has only 41 observations and is therefore not subsampled, is represented by the solid blue line at 0.32.

3.2. CCM-300 Measurements for Different Plant Functional Types

3.2.1. ccm-300 measurements for different plant functional types.

We further classified our data into three groups—broadleaf, conifer, and graminoid based on a structural–functional approach, as described by Box [ 39 ]. Our original data included a shrub functional type which we reclassified into broadleaf or conifer based on the species. The data available for this part of our study did not include results from laboratory spectrophotometry.

Mean and standard deviation values for [CCM-300, HPLC] pairs separated by plant functional type are presented in Table 3 . The CCM-300 mean was higher than HPLC for every plant functional type. The linear regression results between CCM-300 and HPLC for all functional types are shown in Figure 7 . Overall, our data gathered closely around the 1:1 line. There was a strong correlation between CCM-300 and HPLC measurements for both broadleaves (r = 0.55) and conifers (r = 0.52), but the correlation was weak for graminoids (r = 0.32) ( Table 4 ). Interestingly, the model for graminoids yielded the smallest RMSE (127.12) across all plant functional types, indicating its ability to capture the proper magnitude of chlorophyll content.

Scatter plot with CCM-300 measurements as X and HPLC as Y colored by different plant functional types. The dashed line is the 1:1 line. The solid black line is the regression trendline with data from all plant functional types. Colored trendlines correspond to plant functional types in the figure legend. The equation, r, and RMSE values in the plot are for the pooled regression model.

Mean (mg/m 2 ) and standard deviation (S.D.) (mg/m 2 ) values for CCM-300 and HPLC by plant functional type.

Regression data for CCM-300 vs. HPLC by functional type.

Positive bias between CCM-300 measurements and HPLC for all plant functional types (78.41 mg/m 2 , 13.99 mg/m 2 , and 38.11 mg/m 2 for broadleaf, conifer, and graminoid, respectively) indicated that CCM-300 generally overestimated chlorophyll content for the tested samples. The overestimation was most severe for broadleaf, followed by graminoids, and the least for conifers. Additionally, we observed meter saturation above 625 mg/m 2 for conifers.

3.2.2. Needle Age Analysis

The UW-Madison dataset recorded needle age during the sample collection and enabled us to explore how needle age affects the CCM-300 measurements. We used 51 conifer samples with both CCM-300 and Spec measurements to further study the effects of age. It can be seen in Figure 8 that the CCM-300 meter performed well for new needles but appeared inconsistent for old needles. There was a strong correlation between CCM-300 and laboratory spectrophotometry (Spec) for new needles ( Table 5 ). A similar trend was observed for the HPLC measurements from the UW-Madison dataset ( n = 26, Figure S1 ).

Comparison of new and old needles for CCM-300 (mg/m 2 ) vs. Spec (mg/m 2 ).

Regression data for CCM-300 (mg/m 2 ) vs. Spec (mg/m 2 ) by needle age.

Positive bias for new needles (34.46 mg/m 2 ) indicated that the CCM-300 mostly overestimated chlorophyll content in the analyzed samples. Negative bias for old needles (−105.62), however, indicated that the CCM-300 underestimated chlorophyll content in these samples.

3.3. CCM-300 Performance across Years

There was a positive linear relationship for both years and both functional types in [CCM-300, HPLC] sample pairs ( Figure 9 ). We observed strong correlations between CCM-300 and HPLC measurements for broadleaf species in both years, and conifers in 2018 (r > 0.5) while the correlation was weaker for conifers in 2019 ( Table 6 ). For conifer samples, the CCM-300 appeared to saturate around 625 mg/m 2 for all measurements while HPLC measurements can reach values above 900 mg/m 2 ( Figure 9 ). The CCM-300 performed better for broadleaf species with higher r and lower RMSE compared to conifers in both years.

Scatter plots of years for [CCM-300, HPLC] samples compared by functional type. The black dashed lines indicate a 1:1 trendline.

Regression data for CCM-300 vs. HPLC by functional type and year, where n represents the number of samples.

Positive bias for broadleaf samples analyzed in 2018 and 2019 (127.27 mg/m 2 and 66 mg/m 2 , respectively) indicated that the CCM-300 typically overestimated chlorophyll content in both years, but more so in 2018. For conifer samples, negative bias in 2018 (−6.28 mg/m 2 ) and positive bias in 2019 (57.63 mg/m 2 ) indicated that the CCM-300 mildly underestimated chlorophyll content in 2018, but generally overestimated in 2019. The CCM-300 performance was inconsistent between years.

4. Discussion

4.1. ccm-300 measurements vs. laboratory chemistry measurements.

Based on the results of each of our paired T-tests, we found no statistically significant difference between HPLC and laboratory spectrophotometric (Spec) estimates of chlorophyll content ( p > 0.1). Both laboratory chemistry methods are reliable for obtaining chlorophyll content ( Figure 2 and Figure 4 ). The biggest discrepancies between HPLC and Spec measurements are from old conifer samples ( Figure 3 , pair [HPLC, Spec]). Old needles usually have higher chlorophyll content [ 40 ] and it takes a longer time to fully extract the chlorophyll from the needle samples. During HPLC analyses, all samples were subjected to the same extraction procedure. While the extraction time is enough for most samples, it may not be for a few old needles with exceptionally high chlorophyll contents, which may cause discrepancies between HPLC and Spec.

In contrast, we observed a significant difference between both CCM-300 and HPLC, and CCM-300 and laboratory spectrophotometry (Spec). Comparison of iteratively subsampled paired data (with 41 samples), all pairs, and peak values of permutation p -value distribution did not influence the significance of paired T-test results, further supporting our inferences regarding the continued reliability of laboratory chemistry analyses and the potential limitations of the CCM-300. Our results are significantly different at α = 0.05, but the significance would change at α = 0.01 for some pairs. This change in alpha would result in no statistically significant difference for [CCM-300, Spec] pairs from all available paired data, as well as [CCM-300, HPLC] and [CCM-300, Spec] pairs from the permutation analysis ( Figure 6 ).

Additionally, for NEON data, CCM-300 measurements represented the average conditions of five samples while the laboratory chemistry only tested two to three samples. This mismatch could contribute to the observed difference between CCM-300 measurements and laboratory chemistry results.

Despite the differences between CCM-300 and HPLC in the paired T-test, the regression model performed reasonably well when predicting HPLC using CCM-300 measurements ( Figure 7 ). The correlation coefficient (r) for [CCM-300, HPLC] was 0.52. Although the CCM-300 did not match HPLC exactly, it is able to track the variation in chlorophyll content. Nevertheless, laboratory chemistry analyses could produce more reliable estimates.

4.2. CCM-300 Measurements for Different Plant Functional Types

The grouping of data around the 1:1 line in Figure 7 implies that the CCM-300 produces reasonable results for chlorophyll content across the plant functional types analyzed in this study. A regression relationship can be used to “correct” the trend in the CCM-300 data, but no single regression is suitable across plant functional types ( Table 4 ). This observation has been seen in other meters and has raised concern in the literature [ 17 , 41 ]. Richardson et al. [ 17 ] encourage users of absorptance-based portable chlorophyll meters to consider the need for species-specific calibration when leaf structure varies among samples, while Gamon and Surfus [ 41 ] concluded that the chlorophyll index used when analyzing leaf samples with a reflectance-based meter varies between species, specifically those with dissimilar leaf structures.

The meter performed the best for broadleaf species, followed by conifers, but poorly for graminoids. The poor performance for graminoids is likely due to the small variation in range (356 mg/m 2 for graminoids, compared to 780.35 mg/m 2 for broadleaf and 830.85 mg/m 2 for conifer) represented by 10 samples for this functional type in our dataset.

We observed meter saturation around 625 mg/m 2 ( Figure 7 ) for conifers, indicating a deterioration in meter sensitivity and accuracy in measuring needles with chlorophyll content beyond this threshold. This saturation is the worst for old needles ( Figure 8 ) where our regression model has the highest RMSE (222.48 mg/m 2 ) ( Table 5 ). We suspect that differences in leaf anatomy, likely in the cuticle and epidermis, resulted in the saturation we observed. Needle leaves are known to have thicker and denser external layers compared to broadleaves; thus, the tough structure of old needles likely contributes to the saturation. Lhotáková et al. [ 42 ] evaluated the effects of leaf structure on meter outputs and determined that the assessment of needle leaves has several constraints, and it is necessary to perform other biochemical assessments, such as spectrophotometry, for determination of chlorophyll content in needle leaves.

While meter measurements suffered from saturation for conifer samples, measurements are mostly reliable for broadleaves. This is not surprising, since the CCM-300 is based on the work of Gitelson et al. [ 26 ], which used broadleaf species exclusively. To the best of our knowledge, Opti-Sciences has not updated the equations utilized by the meter. Our recommendation is to primarily use the CCM-300 for broadleaf species. When analyzing coniferous species with the meter, it is advisable to supplement the measurements with laboratory chemistry to account for any discrepancies [ 42 ].

Other studies have reported potential factors contributing to the varied performance of absorptance-based portable chlorophyll meters. Richardson et al. [ 17 ] suggest that the size of the measurement area on a given device has an impact on the output of hand-held chlorophyll meters. However, fluorescence-based meters, such as the CCM-300, do not suffer from this drawback, as fluorescence is an active technique measuring light actively emitted from the leaf itself. This does not require the entirety of the measurement window to be filled by a sample, allowing for the measurement of very small leaves. Various studies report that absorptance-based meters also produce less accurate estimations as chlorophyll content increases [ 17 , 19 , 43 , 44 ], which is consistent with the results of our study using the CCM-300. It is not surprising for the CCM-300 to be impacted by meter saturation, as other types of handheld devices experience the same phenomenon.

4.3. CCM-300 Performance across Years

Based on the results of our analysis between years, the correlation coefficients ( r ) suggest that the CCM-300 captured chlorophyll variation better in 2018 than in 2019 ( Table 6 ). This could be attributed to the lack of hardware calibration for the meter, and/or a deterioration in the quality of the calibration slide used before sample collection. After extensive usage in tough field conditions, the quality of the calibration slide may deteriorate. This could potentially cause drifts in the calibration and may have led to a worse performance of the meter in 2019.

As well, it is plausible that a larger overall sample size with greater uniformity among the sample size of all groups would yield results that are more consistent between both years and functional types. For broadleaf samples, the sample size from 2018 ( n = 47) was slightly less than 2019 ( n = 65). Within conifer samples, 2018 ( n = 111) has significantly more samples than 2019 ( n = 31).

4.4. Study Limitations

The Opti-Sciences CCM-300 provides reasonable results for chlorophyll content if users desire measurements of coarse-scale relative variations. However, broad applications of the CCM-300 for precise estimates may be problematic. Our study used opportunistic data and we cannot rule out that a larger sample size would better validate the precision of CCM-300 measurements, thus our findings may not fully capture the variability in CCM-300 performance. We also provide no absolute measure of accuracy for the HPLC and laboratory spectrophotometric analyses. Regardless, this study provides important evidence that users must carefully evaluate data from the CCM-300 for their applications.

Due to the expense of laboratory chemistry, our study was limited, to an extent, by cost. It is not realistic for many researchers to complete laboratory analyses for every sample in a study, thus portable chlorophyll content meters can be used in certain scenarios as a cost-effective, non-destructive method.

5. Conclusions

Our study utilizing opportunistic data suggests that the Opti-Sciences CCM-300 can produce reasonable results for estimating chlorophyll content, but is limited, especially if comparing measurements across functional physiognomic types. Laboratory chemistry analyses continue to be the most reliable method for measurement of chlorophyll content. The CCM-300 is most compatible with broadleaf species and is likely least reliable in measurements of old needles due to meter saturation. There is mild deterioration of the CCM-300 performance between years which could be due to calibration drift.

Moving forward, users of the CCM-300 for broad scale studies, such as in situ measurements to support remote sensing, should conduct a dedicated study with a large sample size composed of many samples from a wider variety of functional types. When measuring needle leaves, we recommend using equations, such as those represented in Table 5 , to correct for the large bias in the CCM-300 measurements. It is best practice, however, for users to develop their own equations tailored specifically to their studies.

It may be helpful for those planning future chlorophyll meter studies to consider that chlorophyll is not uniformly distributed within a leaf, impacting meter outputs depending on where the measurement is taken [ 45 ]. It is recommended that multiple measurements be taken from each leaf then averaged to improve the accuracy of chlorophyll estimation [ 32 , 43 ]. When doing so, it is best practice to complete measurements of the same leaf within 3 min of the initial measurement to minimize the effects of chloroplast migration on meter outputs [ 32 ]. The CCM-300 Chlorophyll Content Meter Operation Manual [ 32 ] also recommends that ambient temperatures be considered when taking sample measurements, as this factor may have the potential to influence measurement results.

It is important to adjust measurement parameters to suit the study at hand, but we recommend completing studies with multiple replications of each sample. The CCM-300 includes a range of measuring options that allows users to average between 2 and 30 measurements. Samples with a lower fluorescence emission signal strength may require more measurements [ 32 ].

Finally, one should take note of the conditions of the slide used to calibrate the CCM-300 meter. After repeated use, the calibration slide may undergo wear and tear that includes scratches, dents, and loss of adherence to the fluorescence coefficient it was once measured to be. Integrating an internal calibration slide into the meter would ensure consistent slide quality, and including a slide replacement schedule would enhance usability.

We hope that, ultimately, this study provides guidance on CCM-300 applications for large-scale chlorophyll content quantification in support of calibration and validation of a forthcoming generation of spaceborne imaging spectrometers, such as Surface Biology and Geology (SBG) and Copernicus Hyperspectral Imaging Mission for the Environment (CHIME) that will be used to map at high resolutions (30 m) seasonal chlorophyll worldwide at monthly or better time scales.

Acknowledgments

We thank all the members of field crews who assisted with data collection from these projects, as well the laboratories of Jeannine Cavender-Bares at the University of Minnesota for assistance with laboratory chemical analyses. We also express our gratitude to Amaya Atucha and Beth Ann Workmaster from the University of Wisconsin-Madison for providing us with access to their spectrophotometer and offering valuable guidance in the chlorophyll analysis.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/s24154784/s1 , Figure S1: HPLC measurements from the UW-Madison dataset ( n = 26).

Funding Statement

The research presented here was supported by NSF ASCEND Biology Integration Institute (BII) award DBI 2021898, with data provided from NSF Macrosystems Biology and NEON-Enabled Science (MSB-NES) award DEB 1638720 and USDA McIntire-Stennis Award WIS03008.

Author Contributions

Conceptualization, T.Z. and Z.W.; data curation, T.Z., Z.W. and K.R.K.; formal analysis, J.M.V.B.; funding acquisition, P.A.T.; methodology, J.M.V.B., T.Z. and K.R.K.; supervision, T.Z.; visualization, J.M.V.B.; writing—original draft, J.M.V.B.; writing—review and editing, J.M.V.B., T.Z., Z.W., K.R.K. and P.A.T. All authors have read and agreed to the published version of the manuscript.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Data availability statement, conflicts of interest.

The authors declare no conflict of interest.

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• Plant Biology

OsNF-YB7 inactivates OsGLK1 to inhibit chlorophyll biosynthesis in rice embryo

• Zongju Yang
• Baixiao Niu
• Chen Chen author has email address
• Jiangsu Key Laboratory of Crop Genomics and Molecular Breeding/ Zhongshan Biological Breeding Laboratory, Agricultural College of Yangzhou University, Yangzhou, China
• Jiangsu Co-Innovation Center for Modern Production Technology of Grain Crops/ Key Laboratory of Plant Functional Genomics of the Ministry of Education, Agricultural College of Yangzhou University, Yangzhou, China
• State Key Laboratory of Rice Biology and Breeding, China National Rice Research Institute, Hangzhou, China
• https://doi.org/ 10.7554/eLife.96553.2
• Open access
• Copyright information

Peer review process

Revised: This Reviewed Preprint has been revised by the authors in response to the previous round of peer review; the eLife assessment and the public reviews have been updated where necessary by the editors and peer reviewers.

• Reviewing Editor Paula Casati Center of Photosynthetic And Biochemical Studies (CEFOBI), Santa Fe, Argentina
• Senior Editor Jürgen Kleine-Vehn University of Freiburg, Freiburg, Germany

Reviewer #1 (Public Review):

This manuscript investigates the regulation of chlorophyll biosynthesis in rice embryos, focusing on the role of OsNF-YB7. The rigorous experimental approach, combining genetic, biochemical, and molecular analyses, provides a robust foundation for these findings. The research achieves its objectives, offering new insights into chlorophyll biosynthesis regulation, with the results convincingly supporting the authors' conclusions.

The major strengths include the detailed experimental design and the findings regarding OsNF-YB7's inhibitory role.

Weaknesses:

However, the manuscript's discussion on the practical implications for agriculture and the evolutionary analysis of regulatory mechanisms could be expanded.

• https://doi.org/ 10.7554/eLife.96553.2.sa3

Reviewer #2 (Public Review):

The authors set out to establish the role of the rice LEC1 homolog OsNF-YB7 in embryo development, especially as it pertains to the development of photosynthetic capacity, with chlorophyll production as a primary focus.

The results are well-supported and each approach used complements each other. There are no major questions left unanswered and the central hypothesis is addressed in every figure.

There are a handful of sections which could use clarifying for readers, but overall this is a solidly composed manuscript.

The authors clearly achieved their aims; the results compellingly establish a disparity between how this system operates in rice and Arabidopsis. Conclusions are thoroughly supported by the provided data and interpretations. This work will force a reconsideration of the value of Arabidopsis as a model organism for embryo chlorophyll biosynthesis and possibly photosynthesis during embryo maturation more broadly, as rice is a major crop organism and it very clearly does not follow the Arabidopsis model. It will thus be useful to carry out similar tests in other organisms rather than relying on Arabidopsis and attempt to more fully establish the regulatory mechanism in rice.

• https://doi.org/ 10.7554/eLife.96553.2.sa2

Reviewer #3 (Public Review):

In this study, the authors set out to understand the mechanisms behind chlorophyll biosynthesis in rice, focusing in particular on the role of OsNF-YB7, an ortholog of Arabidopsis LEC1, which is a positive regulator of chlorophyll (Chl) biosynthesis in Arabidopsis. They showed that OsNF-YB7 loss-of-function mutants in rice have chlorophyll-rich embryos, in contrast to Arabidopsis LEC1 loss-of-function mutants. This contrasting phenotype led the authors to carry out extensive molecular studies on OsNF-YB7, including in vitro and in vivo protein interaction studies, gene expression profiling and protein-DNA interaction assays. The evidence provided well supported the core arguments of the authors, emphasising that OsNF-YB7 is a negative regulator of Chl biosynthesis in rice embryos by mediating the expression of OsGLK1, a transcription factor that regulates downstream Chl biosynthesis genes. In addition, they showed that OsNF-YB7 interacts with OsGLK1 to negatively regulate the expression of OsGLK1, demonstrating the broad involvement of OsNF-YB7 in rice Chl biosynthetic pathways.

This study clearly demonstrated how OsNF-YB7 regulates its downstream pathways using several in vitro and in vivo approaches. For example, gene expression analysis of OsNF-YB7 loss-of-function and gain-of-function mutants revealed the expression of selected downstream chl biosynthetic genes. This was further validated by EMSA on the gel. The authors also confirmed this using luciferase assays in rice protoplasts. These approaches were used again to show how the interaction of OsNF-YB7 and OsGLK1 regulates downstream genes. The main idea of this study is very well supported by the results and data.

It would be interesting to see how two similar genes have come to play opposite roles in Arabidopsis and rice. Interspecies complementation might help to understand this point.

• https://doi.org/ 10.7554/eLife.96553.2.sa1

Author response:

The following is the authors’ response to the original reviews.

eLife assessment This is an important study on the regulation of chlorophyll biosynthesis in rice embryos. It provides insights into the genetic and molecular interactions that underlie chlorophyll accumulation, highlighting the inhibition of OsGLK1 by OsNF-YB7 and the broader implications for understanding chloroplast development and seed maturation in angiosperms. The results presented, including mutation analysis, gene expression profiles, and protein interaction studies, provide convincing evidence for the function of OsNF-YB7 as a repressor in the chlorophyll biosynthesis pathway.

Thank you very much for your positive assessment of our manuscript. We have carefully revised the manuscript according to the reviewers’ valuable suggestions and comments. For more details, please see the point-to-point response to the reviewers below.

Public Reviews: Reviewer #1 (Public Review): Summary: This manuscript investigates the regulation of chlorophyll biosynthesis in rice embryos, focusing on the role of OsNF-YB7. The rigorous experimental approach, combining genetic, biochemical, and molecular analyses, provides a robust foundation for these findings. The research achieves its objectives, offering new insights into chlorophyll biosynthesis regulation, with the results convincingly supporting the authors' conclusions. Strengths: The major strengths include the detailed experimental design and the findings regarding OsNF-YB7's inhibitory role. Weaknesses: However, the manuscript's discussion on the practical implications for agriculture and the evolutionary analysis of regulatory mechanisms could be expanded.

Thank you for your insightful comments and suggestions. In the revised manuscript, we discussed the potential application of the chlorophyllous embryo (please see line 270-274). The presence of chlorophyll in the embryo facilitates photosynthesis at early developmental stages, potentially leading to improved seedling growth and vigor (Smolikova and Medvedev, 2016). In crops such as soybean and canola, green embryo is considered as a valuable trait due to its association with enhanced photosynthetic capacity, which consequently promotes fatty acid biosynthesis (Ruuska et al., 2004). However, chlorophyll degradation must be carefully managed during seed maturation to avoid negative effects on seed viability and meal quality (Chung et al., 2006). Interestingly, the green embryo of lotus ( Nelumbo nucifera ) is widely used as a food ingredient in Asian, Australia, and North America. It is employed in herbal medicine to treat nervous disorders, insomnia, and other conditions (Zhu et al., 2017; Ha et al., 2022), highlighting the significant potential value of the green embryo.

In many chloroembryophytes, such as Arabidopsis, the embryo occupies a large proportion of the seed. From an evolutionary perspective, the presence of chlorophyll in the embryo may promote adaptation in such chloroembryophytes because more reserves can be accumulated in the seed through active photosynthesis, better supporting the embryo development and subsequent seedling growth (Sela et al., 2020). On the other hand, some leucoembryophytes, such as rice, have persistent endosperm rich in storage reserves to nourish embryo development (Liu et al., 2022). Gaining the ability to accumulate chlorophyll in the embryo is unnecessary for such species. In agreement with this hypothesis, cholorophyllous embryos are more prevalent in non-endospermous seeds (Dahlgren, 1980). However, we would like to emphasize that the evolutionary force driving the divergence of chloroembryophytes and leucoembryophytes is currently almost completely unknown and deserves in-depth investigation in the future. We discussed the possible evolution of the ability to accumulate chlorophyll in the embryo, please find the details in Line 276-295.

Reviewer #2 (Public Review): Summary: The authors set out to establish the role of the rice LEC1 homolog OsNF-YB7 in embryo development, especially as it pertains to the development of photosynthetic capacity, with chlorophyll production as a primary focus. Strengths: The results are well-supported and each approach used complements each other. There are no major questions left unanswered and the central hypothesis is addressed in every figure. Weaknesses: There are a handful of sections that could use clarifying for readers, but overall this is a solidly composed manuscript. The authors clearly achieved their aims; the results compellingly establish a disparity between how this system operates in rice and Arabidopsis. Conclusions are thoroughly supported by the provided data and interpretations. This work will force a reconsideration of the value of Arabidopsis as a model organism for embryo chlorophyll biosynthesis and possibly photosynthesis during embryo maturation more broadly, as rice is a major crop organism and it very clearly does not follow the Arabidopsis model. It will thus be useful to carry out similar tests in other organisms rather than relying on Arabidopsis and attempting to more fully establish the regulatory mechanism in rice.

Thank you very much for your positive comments. We have carefully revised the manuscript according to your and the other reviewers’ comments and suggestions. Particularly, we emphasized the necessary to carry out similar tests in other organisms rather than relying on Arabidopsis to better understand the regulatory mechanism in rice.

Reviewer #3 (Public Review): Summary: In this study, the authors set out to understand the mechanisms behind chlorophyll biosynthesis in rice, focusing in particular on the role of OsNF-YB7, an ortholog of Arabidopsis LEC1, which is a positive regulator of chlorophyll (Chl) biosynthesis in Arabidopsis. They showed that OsNF-YB7 loss-of-function mutants in rice have chlorophyll-rich embryos, in contrast to Arabidopsis LEC1 loss-of-function mutants. This contrasting phenotype led the authors to carry out extensive molecular studies on OsNF-YB7, including in vitro and in vivo protein interaction studies, gene expression profiling, and protein-DNA interaction assays. The evidence provided well supported the core arguments of the authors, emphasising that OsNF-YB7 is a negative regulator of Chl biosynthesis in rice embryos by mediating the expression of OsGLK1, a transcription factor that regulates downstream Chl biosynthesis genes. In addition, they showed that OsNF-YB7 interacts with OsGLK1 to negatively regulate the expression of OsGLK1, demonstrating the broad involvement of OsNF-YB7 in rice Chl biosynthetic pathways. Strengths: This study clearly demonstrated how OsNF-YB7 regulates its downstream pathways using several in vitro and in vivo approaches. For example, gene expression analysis of OsNF-YB7 loss-of-function and gain-of-function mutants revealed the expression of selected downstream chl biosynthetic genes. This was further validated by EMSA on the gel. The authors also confirmed this using luciferase assays in rice protoplasts. These approaches were used again to show how the interaction of OsNF-YB7 and OsGLK1 regulates downstream genes. The main idea of this study is very well supported by the results and data. Weaknesses: From an evolutionary perspective, it is interesting to see how two similar genes have come to play opposite roles in Arabidopsis and rice. It would have been more interesting if the authors had carried out a cross-species analysis of AtLEC1 and OsNF-YB7. For example, overexpressing AtLEC1 in an osnf-yb7 mutant to see if the phenotype is restored or enhanced. Such an approach would help us understand how two similar proteins can play opposite roles in the same mechanism within their respective plant species.

We appreciate your insightful comments and suggestions. It is a very interesting question whether AtLEC1 can fully restore osnf-yb7 , given the possible functional divergence between the genes in terms of regulation of chlorophyll biosynthesis in the embryo. We have previously expressed OsNF-YB7 in the lec1-1 background in Arabidopsis, driven by the native promoter of LEC1 (Niu et al., 2021). We found that OsNF-YB7 could almost completely rescue the embryo defects in Arabidopsis, indicating that OsNF-YB7 plays a resemble role in rice as the LEC1 does in Arabidopsis (Niu et al., 2021). We sought to determine whether AtLEC1 can complement the chlorophyll defect in osnf-yb7 . However, given the fact that osnf-yb7 shows severe callus induction defect, which is not surprising, because many studies have shown that LEC1 is indispensable for somatic embryo development in various plant species, we are struggling to obtain the genetic materials for analysis. We have to transform OsNF-YB7pro::AtLEC1 into the WT background first, and then cross the transformant with the osnf-yb7 mutant. This is a time-consuming process in rice, but hopefully we will able to isolate a line expressing OsNF-YB7pro::AtLEC1 in the osnf-yb7 background from the resulting segregating population.

Recommendations for the authors: Reviewer #1 (Recommendations For The Authors): A minor comment regarding the chlorophyll contents quantification in the study. Line 87: "The results showed that WT had an achlorophyllous embryo throughout embryonic development,...." In the TEM result, chloroplast was not observed in the WT embryo sections, indicating a lack of chlorophyll-containing structures, contrary to what was found in the osnf-yb7 embryos where chloroplasts were observed. The authors stated that the embryo morphologies and Chl autofluorescence data showed that WT had an achlorophyllous embryo throughout embryonic development. However, the quantification of Chl levels in Figure 1D and Figure 4C showed that WT does produce some chlorophylls, albeit at lower levels than osnf-yb7 or OSGLK-OX embryos (WT values in the two figures are slightly different). This discrepancy warrants clarification to ensure consistency and accuracy in the manuscript's findings.

We re-evaluated the Chl content in the embryos of WT and OsGLK1-OX mature seeds. The result confirmed our previous finding that WT embryos produce a small amount of chlorophyll (please see the updated Fig. 4C). Notably, we observed that the dark-grown etiolated plants still have measurable chlorophyll content as reported in many studies (for example, Wang et al., 2017; Yoo et al., 2019), suggesting that there is potential bias in measuring chlorophyll content using an absorbance-based approach. We assume this possibly explains the concern you have raised.

Reviewer #2 (Recommendations For The Authors): Mild editing for grammar is needed throughout, e.g. line 73, "It is still a mysterious why plant species".

We have carefully edited the grammar.

As a minor point, the placement of figure panels, such as in Figure 1, is not always intuitive.

Thank you for your suggestion. This figure has been revised as suggested. Please see the updated Fig. 1.

What is the significance of the two GFP mutants in Figures 2C and 2D? Is one of those the mislabeled Flag mutant?

The lines showed in Fig. 2C and D were not mislabeled. They were two independent transgenic events, both of which showed that OsNF-YB7 inhibited the expression of OsPORA and OsLHCB4 in rice. The transgenic lines overexpressing OsNF-YB7 tagging with the 3× Flag ( NF-YB7-Flag ) were also used for this experiment. In agreement, OsPORA and OsLHCB4 were significantly downregulated in the three independent NF-YB7-Flag lines (Fig. S4C), confirming the results showed in Fig. 2C and D.

In Figures 2G and 2H, what is that enormous band at the bottom of the gel?

The bands at the bottom of the gel were free probes. We indicated this in the revised figure.

Not until the Materials and Methods section did I realize that any of this study was being done in tobacco; the Introduction implies it's rice vs. Arabidopsis and it might be a good idea to mention the organism of study somewhere before Figure 6.

We apologize for any confusion caused by our previous writing. While the majority of this study was performed with rice plants or protoplasts, the split complementary LUC assays and BiFC assays were performed with tobacco. We have specified these in the revised manuscript as suggested.

Reviewer #3 (Recommendations For The Authors): It would be nice if the author could show what the phenotype is in AtLEC1 OX in osnf-yb7 and also OsNF-YB7 OX in atlec1 mutants.

Thank you for your suggestion. We have previously expressed OsNF-YB7 in the lec1-1 background of Arabidopsis, driven by the native promoter of Arabidopsis LEC1 (Niu et al., 2021). Since OsNF-YB7 could rescue the embryo morphogenesis defects in Arabidopsis (Niu et al., 2021), we assumed that OsNF-YB7 plays a similar role in rice as the LEC1 does in Arabidopsis. However, it remains unknown whether expression of LEC1 in osnf-yb7 may restore the chlorophyllous embryo phenotype in rice. As the generation of genetic material is time-consuming, and especially given the fact that osnf-yb7 has a severe callus induction defect, we are struggling to obtain the complementary line for analysis. We have to transform OsNF-YB7pro::AtLEC1 in a WT background first, and then cross the transformant with the osnf-yb7 mutant. Hopefully, we will be able to isolate a line expressing OsNF-YB7pro::AtLEC1 in osnf-yb7 background, from the derived segregating population. We discussed the reviewer’s concern in the revised manuscript, please see Line 369-376.

Line 46, I think it is vague to mention that 'Like most plant species'. Some species might have different copy numbers, for example, a single GLK in liverwort M. polymorpha.

The statement has been revised. Please see Line 46.

Figures 2F and 5B, why was only one promoter region used for OsLHCB4? It would be better to have more regions like OsPORA.

Thank you for your comments. Here, we have examined more promoter regions (P1, P2 and P3) in the revised manuscript as suggested, among which, the previously selected promoter region (P3) contains both the G-box and CCAATC motifs that can be potentially recognized by GLK1. Consistent to our previous report, the results showed that OsNF-YB7 (left) and OsGLK1 (right) were associated with the P3 region, but showed no significant differences in the other probes. Please see the results in Fig. 2F and Fig. 5B of the revised manuscript.

Legend of Figures 2G, H, OsPORA (I), and OsLHCB (J) should be (G) and (H) respectively.

Chung, D.W., Pruzinska, A., Hortensteiner, S., and Ort, D.R. (2006). The role of pheophorbide a oxygenase expression and activity in the canola green seed problem. Plant Physiol 142, 88-97.

Ha, T., Kim, M.S., Kang, B., Kim, K., Hong, S.S., Kang, T., Woo, J., Han, K., Oh, U., Choi, C.W., and Hong, G.S. (2022). Lotus Seed Green Embryo Extract and a Purified Glycosyloxyflavone Constituent, Narcissoside, Activate TRPV1 Channels in Dorsal Root Ganglion Sensory Neurons. J Agric Food Chem 70, 3969-3978.

Liu, J., Wu, M.W., and Liu, C.M. (2022). Cereal Endosperms: Development and Storage Product Accumulation. Annu Rev Plant Biol 73, 255-291.

Niu, B., Zhang, Z., Zhang, J., Zhou, Y., and Chen, C. (2021). The rice LEC1-like transcription factor OsNF-YB9 interacts with SPK, an endosperm-specific sucrose synthase protein kinase, and functions in seed development. Plant J 106, 1233-1246.

Ruuska, S.A., Schwender, J., and Ohlrogge, J.B. (2004). The capacity of green oilseeds to utilize photosynthesis to drive biosynthetic processes. Plant Physiol 136, 2700-2709.

Sela, A., Piskurewicz, U., Megies, C., Mene-Saffrane, L., Finazzi, G., and Lopez-Molina, L. (2020). Embryonic Photosynthesis Affects Post-Germination Plant Growth. Plant Physiol 182, 2166-2181.

Smolikova, G.N., and Medvedev, S.S. (2016). Photosynthesis in the seeds of chloroembryophytes. Russ J Plant Physl+ 63, 1-12.

Wang, Z., Hong, X., Hu, K., Wang, Y., Wang, X., Du, S., Li, Y., Hu, D., Cheng, K., An, B., and Li, Y. (2017). Impaired Magnesium Protoporphyrin IX Methyltransferase (ChlM) Impedes Chlorophyll Synthesis and Plant Growth in Rice. Front Plant Sci 8, 1694.

Yoo, C.Y., Pasoreck, E.K., Wang, H., Cao, J., Blaha, G.M., Weigel, D., and Chen, M. (2019). Phytochrome activates the plastid-encoded RNA polymerase for chloroplast biogenesis via nucleus-to-plastid signaling. Nat Commun 10, 2629.

Zhu, M., Liu, T., Zhang, C., and Guo, M. (2017). Flavonoids of Lotus (Nelumbo nucifera) Seed Embryos and Their Antioxidant Potential. J Food Sci 82, 1834-1841.

• https://doi.org/ 10.7554/eLife.96553.2.sa0

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• Five Ways LiSA is Advancing Solar Fuels
• Alternative Energy

Artificial photosynthesis could one day harness energy from the sun to convert carbon dioxide, nitrogen, and water into liquid fuels to power your car, and enable a process for creating chemicals and fertilizers that is better for the environment. But scientists first need new techniques to efficiently convert sunlight into solar fuels and chemicals at scale, and store them for later use.

Since its founding in 2020 , the Liquid Sunlight Alliance (LiSA) – a Fuels from Sunlight Energy Innovation Hub funded by the U.S. Department of Energy – has made advances in developing the science principles by which liquid fuels can be generated from sunlight, carbon dioxide, and water.

“LiSA is bringing solar fuels closer to reality. In just five years our researchers have achieved major milestones in artificial photosynthesis.” – Joel Ager, senior scientist and LiSA program lead at Berkeley Lab

Led by Caltech in close partnership with Lawrence Berkeley National Laboratory (Berkeley Lab), LiSA brings together more than 100 scientists from national lab partners at SLAC National Accelerator Laboratory and the National Renewable Energy Laboratory, and university partners at UC Irvine, UC San Diego, and the University of Oregon. This multi-institutional collaboration is focused on accelerating advances in solar fuels research by combining computationally driven experimentation with real-time observations using ultrafast X-rays and other advanced imaging techniques. By facilitating a national network of leading research capabilities, advanced instruments, and cutting-edge user facilities that are unique to national labs and universities, LiSA is paving the way for a solar fuels future.

“LiSA is bringing solar fuels closer to reality,” said Joel Ager, a senior scientist in Berkeley Lab’s Chemical Sciences Division who manages the Northern California LiSA facility at Berkeley Lab. “In just five years our researchers have achieved major milestones in artificial photosynthesis, from new materials and devices that convert sunlight and carbon dioxide into ethylene and other chemical fuels, to advances in computer modeling, data visualization, and X-ray imaging techniques that could make the conversion process more efficient and durable at the commercial scale.”

Here are five potential breakthroughs LiSA research teams led by Berkeley Lab have achieved so far.

1. Made solar energy available 24/7

Photoelectrochemical devices use sunlight to trigger chemical reactions that convert CO 2 and water into liquid fuels. This artificial photosynthesis technology has the potential to revolutionize our energy infrastructure, but current photoelectrochemical techniques in CO 2 reduction are limited by sluggish chemical processes and high energy requirements. A project led by Peidong Yang, a senior faculty scientist in Berkeley Lab’s Materials Sciences Division, offers an alternative approach: A new system design that is far less energy-demanding than conventional systems. This new design enabled 24/7 operation over multiple days – and effectively eliminated sunlight intermittency issues – by using silicon nanowire components that can be illuminated by renewably powered and superefficient LEDs.

2. Modeled artificial photosynthesis at multiple scales

Photoelectrochemical systems have the potential to produce hydrogen fuel and other liquid fuels through artificial photosynthesis, but manufacturing these fuels at scale will require improved efficiencies and product purity. In recent projects led by Adam Weber, senior scientist and head of the Energy Conversion Group in Berkeley Lab’s Energy Technologies Area, and Alexis Bell, faculty senior scientist in the Chemical Sciences Division, researchers developed and ran models to simulate how molecules, atoms, and electrons move around inside and at the interface of a photoelectrochemical device. These simulations shed light on the importance of ion transport – the movement of charged particles – in membrane materials and catalyst performance. The work also advanced new approaches to designing photoelectrochemical assemblies , including metal-insulator-semiconductor architectures, for CO 2 reduction.

3. Clarified the fundamentals of corrosion: How are ions born?

A project led by Shannon Boettcher, a senior faculty scientist in Berkeley Lab’s Energy Storage & Distributed Resources Division, and Martin Head-Gordon, a senior faculty scientist in Berkeley Lab’s Chemical Sciences Division, has created a validated molecular model which accurately delineates the rates at which ions – chemical species that carry electrical current in solutions – are created when a material rusts and dissolves. The advance will help researchers understand the fundamentals of corrosion in photoelectrochemical devices, a longstanding challenge to the commercialization of artificial photosynthesis. The model also maps out the rates at which ions are consumed at the interface between a solid and a liquid, such as when metals are plated from a solution to fabricate semiconductor chips.

By combining laboratory experiments with leading-edge computation, the team’s collaborative study revealed the sequence of molecular events and the resulting barriers that control how fast ions can be formed or consumed. The researchers are currently expanding the approach to complex systems: The aim is to create a general theory that is of broad importance to electrochemical technology in renewable liquid fuel synthesis, batteries, and controlling corrosion processes.

The experimental work was completed at the University of Oregon, a partnering LiSA institution where Boettcher was a chemistry and biochemistry professor before joining Berkeley Lab.

4. Developed superfast X-ray techniques to observe a cutting-edge catalyst at work in real time

Copper is one of the best catalysts in artificial photosynthesis for converting CO 2 into liquid fuels like ethanol, ethylene, and propanol. Researchers have wanted to improve the efficiency and product yield of these reactions, but observing them under operando or real-world working conditions at the interface between metal and electrolyte has been a challenge. A project led by Junko Yano, a senior scientist and Molecular Biophysics & Integrated Bioimaging Division Director at Berkeley Lab, could enable the operando characterization of chemical reactions that take place where metal and electrolyte meet. Using X-ray beamlines at SLAC’s Stanford Synchrotron Radiation Lightsource and Berkeley Lab’s Advanced Light Source , the team is developing and applying techniques to determine where chemical reactions take place in active sites of a copper-liquid interface at relevant time scales . The work can enable new insight related to the catalytic mechanism and durability issues in artificial photosynthesis systems.

5. Discovered new materials for solar-driven CO 2 conversion to fuels and chemicals

Photoelectrochemical devices for solar fuels applications rely on the reactions occurring on semiconductor surfaces under illumination. However, many otherwise promising semiconductors are not conducive for the desired CO 2 reduction chemistry due to underperformance in chemical stability and selectivity. Recent work by Joel Ager and his research team discovered two ways to overcome these challenges. First, they showed that an appropriately chosen metal oxide film can both protect the semiconductor from corrosion while allowing electrons to flow to a catalyst, allowing for solar-driven synthesis of ethylene from CO 2 .

Next, his team showed that Cu(InGa)S 2 or CIGS – a material used in the photovoltaic industry, but previously overlooked for solar fuels – can convert CO 2 to chemicals like carbon monoxide and formic acid all by itself, without any need for protective coatings or co-catalysts. This work was in collaboration with teams from imec Belgium and the Advanced Light Source at Berkeley Lab. These breakthroughs point to the vast potential of solar-driven CO 2 conversion and open new research avenues for exploration.

This work was supported by the DOE Office of Science.

Lawrence Berkeley National Laboratory (Berkeley Lab) is committed to delivering solutions for humankind through research in clean energy, a healthy planet, and discovery science. Founded in 1931 on the belief that the biggest problems are best addressed by teams, Berkeley Lab and its scientists have been recognized with 16 Nobel Prizes. Researchers from around the world rely on the Lab’s world-class scientific facilities for their own pioneering research. Berkeley Lab is a multiprogram national laboratory managed by the University of California for the U.S. Department of Energy’s Office of Science.

DOE’s Office of Science is the single largest supporter of basic research in the physical sciences in the United States, and is working to address some of the most pressing challenges of our time. For more information, please visit energy.gov/science .