Evaluating Photosynthetic Light Response Models for Leaf Photosynthetic Traits in Paddy Rice (<i>Oryza sativa</i> L.) Under Field Conditions
Accurate photosynthetic parameters obtained from photosynthetic light-response curves (LRCs) are crucial for enhancing our comprehension of plant photosynthesis. However, the task of fitting LRCs is still demanding due to diverse variations in LRCs under different environmental conditions, as previo...
Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2024-12-01
|
| Series: | Plants |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2223-7747/14/1/23 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1841549067213078528 |
|---|---|
| author | Xinfeng Yao Huifeng Sun Sheng Zhou Linyi Li |
| author_facet | Xinfeng Yao Huifeng Sun Sheng Zhou Linyi Li |
| author_sort | Xinfeng Yao |
| collection | DOAJ |
| description | Accurate photosynthetic parameters obtained from photosynthetic light-response curves (LRCs) are crucial for enhancing our comprehension of plant photosynthesis. However, the task of fitting LRCs is still demanding due to diverse variations in LRCs under different environmental conditions, as previous models were evaluated based on a limited number of leaf traits and a small number of LRCs. This study aimed to compare the performance of nine LRC models in fitting a set of 108 LRCs measured from paddy rice (<i>Oryza sativa</i> L.) grown in field across 3 years under different leaf positions, leaf ages, nitrogen levels, irrigation levels, and varieties. The shape of 108 LRCs varies significantly under a range of leaf traits, which can be typed into three leaf light-acclimation types—high-light leaves (HL-1 and HL-2), and low-light leaves (LL). The accuracy of these models was evaluated by (1) LRCs from three acclimation types: HL-1 and HL-2, and LL; and (2) LRCs across three irradiance stages: light-limited, light-saturated, and photoinhibition. Results indicate that the Ye model emerged as the top performance among the nine models, particularly in the photoinhibition stage of LL leaves, with median values of <i>R<sup>2</sup></i>, <i>SSE</i>, and <i>AIC</i> of 0.99, 2.39, and −14.03, respectively. Furthermore, the Ye model produced the most accurate predictions of key photosynthetic parameters, including dark respiration (<i>R<sub>D</sub></i>), light-compensation point (<i>I<sub>comp</sub></i>), maximum net photosynthetic rate (<i>P<sub>Nma</sub></i><sub>x</sub>), and light-saturation point (<i>I<sub>sat</sub></i>). Results also suggest that <i>P<sub>NImax</sub></i> and <i>I<sub>max</sub></i> were the most appropriate parameters to describe photosynthetic activity at the light-saturation point. These findings have significant implications for improving the accuracy of fitting LRCs, and thus robust predictions of photosynthetic parameters in rice under different environmental conditions. |
| format | Article |
| id | doaj-art-5092b42ef2f044af8e39bb99849f29cc |
| institution | Kabale University |
| issn | 2223-7747 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Plants |
| spelling | doaj-art-5092b42ef2f044af8e39bb99849f29cc2025-01-10T13:19:31ZengMDPI AGPlants2223-77472024-12-011412310.3390/plants14010023Evaluating Photosynthetic Light Response Models for Leaf Photosynthetic Traits in Paddy Rice (<i>Oryza sativa</i> L.) Under Field ConditionsXinfeng Yao0Huifeng Sun1Sheng Zhou2Linyi Li3Institute of Agricultural Science and Technology Information, Shanghai Academy of Agricultural Sciences, Shanghai 201403, ChinaEco-Environmental Protection Research Institute, Shanghai Academy of Agricultural Sciences, Shanghai 201403, ChinaEco-Environmental Protection Research Institute, Shanghai Academy of Agricultural Sciences, Shanghai 201403, ChinaInstitute of Agricultural Science and Technology Information, Shanghai Academy of Agricultural Sciences, Shanghai 201403, ChinaAccurate photosynthetic parameters obtained from photosynthetic light-response curves (LRCs) are crucial for enhancing our comprehension of plant photosynthesis. However, the task of fitting LRCs is still demanding due to diverse variations in LRCs under different environmental conditions, as previous models were evaluated based on a limited number of leaf traits and a small number of LRCs. This study aimed to compare the performance of nine LRC models in fitting a set of 108 LRCs measured from paddy rice (<i>Oryza sativa</i> L.) grown in field across 3 years under different leaf positions, leaf ages, nitrogen levels, irrigation levels, and varieties. The shape of 108 LRCs varies significantly under a range of leaf traits, which can be typed into three leaf light-acclimation types—high-light leaves (HL-1 and HL-2), and low-light leaves (LL). The accuracy of these models was evaluated by (1) LRCs from three acclimation types: HL-1 and HL-2, and LL; and (2) LRCs across three irradiance stages: light-limited, light-saturated, and photoinhibition. Results indicate that the Ye model emerged as the top performance among the nine models, particularly in the photoinhibition stage of LL leaves, with median values of <i>R<sup>2</sup></i>, <i>SSE</i>, and <i>AIC</i> of 0.99, 2.39, and −14.03, respectively. Furthermore, the Ye model produced the most accurate predictions of key photosynthetic parameters, including dark respiration (<i>R<sub>D</sub></i>), light-compensation point (<i>I<sub>comp</sub></i>), maximum net photosynthetic rate (<i>P<sub>Nma</sub></i><sub>x</sub>), and light-saturation point (<i>I<sub>sat</sub></i>). Results also suggest that <i>P<sub>NImax</sub></i> and <i>I<sub>max</sub></i> were the most appropriate parameters to describe photosynthetic activity at the light-saturation point. These findings have significant implications for improving the accuracy of fitting LRCs, and thus robust predictions of photosynthetic parameters in rice under different environmental conditions.https://www.mdpi.com/2223-7747/14/1/23light-response curveslight acclimationphotosynthetic parameterspaddy rice (<i>Oryza sativa</i> L.)Ye model |
| spellingShingle | Xinfeng Yao Huifeng Sun Sheng Zhou Linyi Li Evaluating Photosynthetic Light Response Models for Leaf Photosynthetic Traits in Paddy Rice (<i>Oryza sativa</i> L.) Under Field Conditions Plants light-response curves light acclimation photosynthetic parameters paddy rice (<i>Oryza sativa</i> L.) Ye model |
| title | Evaluating Photosynthetic Light Response Models for Leaf Photosynthetic Traits in Paddy Rice (<i>Oryza sativa</i> L.) Under Field Conditions |
| title_full | Evaluating Photosynthetic Light Response Models for Leaf Photosynthetic Traits in Paddy Rice (<i>Oryza sativa</i> L.) Under Field Conditions |
| title_fullStr | Evaluating Photosynthetic Light Response Models for Leaf Photosynthetic Traits in Paddy Rice (<i>Oryza sativa</i> L.) Under Field Conditions |
| title_full_unstemmed | Evaluating Photosynthetic Light Response Models for Leaf Photosynthetic Traits in Paddy Rice (<i>Oryza sativa</i> L.) Under Field Conditions |
| title_short | Evaluating Photosynthetic Light Response Models for Leaf Photosynthetic Traits in Paddy Rice (<i>Oryza sativa</i> L.) Under Field Conditions |
| title_sort | evaluating photosynthetic light response models for leaf photosynthetic traits in paddy rice i oryza sativa i l under field conditions |
| topic | light-response curves light acclimation photosynthetic parameters paddy rice (<i>Oryza sativa</i> L.) Ye model |
| url | https://www.mdpi.com/2223-7747/14/1/23 |
| work_keys_str_mv | AT xinfengyao evaluatingphotosyntheticlightresponsemodelsforleafphotosynthetictraitsinpaddyriceioryzasativailunderfieldconditions AT huifengsun evaluatingphotosyntheticlightresponsemodelsforleafphotosynthetictraitsinpaddyriceioryzasativailunderfieldconditions AT shengzhou evaluatingphotosyntheticlightresponsemodelsforleafphotosynthetictraitsinpaddyriceioryzasativailunderfieldconditions AT linyili evaluatingphotosyntheticlightresponsemodelsforleafphotosynthetictraitsinpaddyriceioryzasativailunderfieldconditions |