Model development and feature parameter extraction to capture variations in rice leaf color changes during the later reproductive period

doi:10.1016/j.jia.2025.03.011

Journal of Integrative Agriculture

2026, Vol. 25

Issue (6): 2353-2361 DOI: 10.1016/j.jia.2025.03.011

Crop Science

Advanced Online Publication | Current Issue | Archive | Adv Search

Model development and feature parameter extraction to capture variations in rice leaf color changes during the later reproductive period

Yanan Xu¹^,^2*, Yi Tao^1*, Chang Ye¹, Deshun Xiao¹, Song Chen¹, Guang Chu¹, Chunmei Xu¹, Jianliang Huang^2#, Danying Wang¹^#

¹State Key Laboratory of Rice Biology, China National Rice Research Institute, Hangzhou 310006, China

²National Key Laboratory of Crop Genetic Improvement/Key Laboratory of Crop Ecophysiology and Farming Systems in the Middle Reaches of the Yangtze River, Ministry of Agriculture and Rural Affairs/College of Plant Science and Technology, Huazhong Agricultural University, Wuhan 430070, China

Highlights
● The leaf color change model and extracted parameters established here can quantitatively depict the leaf color change process during the later reproductive period.
● Significant differences in the leaf color change parameters are observed across leaf positions, rice varieties and nitrogen treatments.
● High-yielding varieties are characterized by a later onset time and a slower rate of leaf color change.

Abstract
References

Download: PDF in ScienceDirect
Export: BibTeX | EndNote (RIS)

摘要

水稻生育后期叶片的转色动态直接关系到植株灌浆期间光合物质的积累和营养物质的再利用，影响水稻籽粒的充实和产量的形成。研究水稻生育后期叶片转色动态的表征模型，提取叶片转色动态特征参数，对于高产高效水稻品种的筛选与栽培具有重要意义。本研究以31个水稻品种为材料，动态监测水稻齐穗至成熟期间剑叶、倒2叶和倒3叶的SPAD值并进行归一化处理，建立了水稻生育后期叶色指数（CI）随时间（t）变化的函数模型CI=at²+bt+c，并提取了7个转色特征参数用于定量化比较和评估叶色动态，包含3个转色时间（启始时间T₀，50%转色时长T₅₀和转色持续期T₁₀₀, d）；1个叶色指数（叶色指数终值CI_f）；3个平均转色速率（T₀−T₅₀转色时段R₁，T₅₀−T₁₀₀转色时段R₂，转色全过程R_m, d^–¹）。利用上述叶片转色动态评价体系分析叶位、品种以及氮处理间水稻叶片转色模式差异，发现与剑叶相比，倒2叶和倒3叶的T₀提前2.6−3.0 d，剑叶CI_f分别较倒2叶和倒3叶升高12.12%和21.15%，倒3叶R₁、R₂和R_m较剑叶和倒2叶分别提高10.75%−19.82%、17.99%−20.09%和18.23%−11.61%。水稻产量高于8000 kg ha⁻¹品种的平均T₀、T₅₀和T₁₀₀分别为6.8 d、22.2 d和31.8 d，CI_f为0.56，R_m为0.015 d⁻¹。增施N肥推迟春优927和甬优1540剑叶T₀4.5−6.2 d，降低R_m30.06−32.33%，增加CI_f 35.78−39.69%。本研究的结果表明，建立的叶片转色动态模型和参数体系能定量化表征水稻生育后期叶片的转色动态，评价水稻品种间、叶位间和氮处理间叶片转色动态差异。对高产高效水稻品种的选育及其内在机制解析具有重要价值。

Abstract

The change in leaf color during the later reproductive period of rice is directly related to photoassimilate accumulation and nutrient reuse, and it ultimately affects grain filling and yield. This study aimed to explore an assessment model that depicts the leaf color change process, and extract parameters that can precisely distinguish differences in leaf color changes among different treatments and varieties. A total of 31 rice varieties were selected as the field experiment materials in 2019 and 2023. The SPAD values of the flag, 2nd and 3rd leaves were measured after heading, and they were normalized to the leaf color index (CI). A functional model for the variation of leaf CI with time (t) in the late reproductive stage of rice was established based on CI=at²+bt+c, and seven color change parameters were extracted for the quantitative comparison and assessment of leaf color changes, including three time related parameters for color change (onset time, T₀; midpoint time, T₅₀; and color change duration, T₁₀₀); one leaf color index (final value of CI, CI_f); and three parameters related to the color change rate (the rate during T₀−T₅₀, R₁; the rate during T₅₀−T₁₀₀, R₂; and the mean color change rate, R_m). In 2023, Chunyou 927 (CY927) with a dark leaf color and Yongyou 1540 (YY1540) with a normal leaf color were used as materials, and three N fertilizer amounts were applied to explore the effects of N fertilizer on the leaf color change process through the established assessment system. The T₀ of the flag leaf was delayed by 2.6−3.0 d compared to the 2nd and 3rd leaves. The CI_f of the flag leaf was 12.12 and 21.15% higher than those of 2nd and 3rd leaves, respectively. In addition, the R₁, R₂ and R_m of the 3rd leaf were 10.75–19.82%, 17.99–20.09% and 18.23–11.61% higher than the flag and 2nd leaves, respectively. Rice yield was significantly positively correlated with T₀, positively correlated with T₅₀ and T₁₀₀, and negatively correlated with R₁, R₂ and R_m. The average T₀, T₅₀, and T₁₀₀ of rice varieties with yields higher than 8,000 kg ha⁻¹ were 6.8, 22.2, and 31.8 d, respectively, with a CI_f of 0.563 and an R_m of 0.015 d^–1. N applications delayed T₀ by 4.5–6.2 d, reduced R_m by 30.06–32.33%, and increased CI_f by 35.78–39.69%. The established leaf color change model and extracted parameters quantitatively depicted the leaf color change process during the later reproductive period. They also effectively distinguished the differences in leaf color change among leaf positions, rice varieties and N treatments. This approach is valuable for selecting and cultivating high-yield and nutrient-efficient rice varieties, as well as for analyzing the underlying mechanisms.

Keywords: rice leaf color-changing grain filling model feature parameters

Received: 18 October 2024 Accepted: 27 December 2024 Online: 20 March 2025

Fund:

This study was supported by the National Natural Science Foundation of China (32272210) and the Agricultural Science and Technology Innovation Program (ASTIP), China.

About author: Yanan Xu, E-mail: xuyanan@caas.cn; Yi Tao, E-mail: ancoinna@163.com; #Correspondence Danying Wang, Tel: +86-571-63370191, E-mail: wangdanying@caas.cn; Jianliang Huang, E-mail: jhuang@mail.hzau.edu.cn * These authors contributed equally to this study.

	Service
	E-mail this article
	Add to citation manager
	E-mail Alert
	RSS
	Articles by authors

Cite this article:

Yanan Xu, Yi Tao, Chang Ye, Deshun Xiao, Song Chen, Guang Chu, Chunmei Xu, Jianliang Huang, Danying Wang. 2026. Model development and feature parameter extraction to capture variations in rice leaf color changes during the later reproductive period. Journal of Integrative Agriculture, 25(6): 2353-2361.

Acevedo-Siaca L G, Coe R, Quick W P, Long S P. 2021. Variation between rice accessions in photosynthetic induction in flag leaves and underlying mechanisms. Journal of Experimental Botany, 72, 1284–1294.

Antonietta M, Fanello D D, Acciaresi H A, Guiamet J J. 2014. Senescence and yield responses to plant density in stay green and earlier-senescing maize hybrids from Argentina. Field Crops Research, 155, 111–119.

Asad M A U, Guan X Y, Zhou L J, Qian Z, Yan Z, Cheng F M. 2023. Involvement of plant signaling network and cell metabolic homeostasis in nitrogen deficiency-induced early leaf senescence. Plant Science, 336, 111855.

Chang L Y, Zhang W Y, Zhang Y P, Gu D X, Yao X F, Zhu Y, Cao W X. 2007. A simulation model on leaf color dynamic changes in rice. Acta Agronomica Sinica, 33, 1108–1115. (in Chinese)

Christopher J T, Veyradier M, Borrell A K, Harvey G, Fletcher S, Chenu K. 2014. Phenotyping novel stay-green traits to capture genetic variation in senescence dynamics. Functional Plant Biology, 41, 1035–1048.

Gaju O, Allard V, Martre P, Le Gouis J, Moreau D, Bogard M, Hubbart S, Foulkes M J. 2014. Nitrogen partitioning and remobilization in relation to leaf senescence grain yield and grain nitrogen concentration in wheat cultivars. Field Crops Research, 155, 213–223.

Gaju O, Allard V, Martre P, Snape J W, Heumez E, LeGouis J, Moreau D, Bogard M, Griffiths S, Orford S, Hubbart S, Foulkes M J. 2011. Identification of traits to improve the nitrogen-use efficiency of wheat genotypes. Field Crops Research, 123, 139–152.

Gregersen P L, Culetic A, Boschian L, Krupinska K. 2013. Plant senescence and crop productivity. Plant Molecular Biology, 82, 603–622.

Have M, Marmagne A, Chardon F, Masclaux-Daubresse C. 2017. Nitrogen remobilization during leaf senescence: Lessons from Arabidopsis to crops. Journal of Experimental Botany, 68, 2513–2529.

Inada K. 1963. Studies on a method for determining the deepness of green color and chlorophyll content of intact crop leaves and its practical applications 1 Principle for estimating the deepness of green color and chlorophyll content of whole leaves. Proceedings of the Crop Science Society of Japan, 32, 157–162.

Kitonyo O M, Sadras V O, Zhou Y, Denton M D. 2017. Evaluation of historic Australian wheat varieties reveals increased grain yield and changes in senescence patterns but limited adaptation to tillage systems. Field Crops Research, 206, 65–73.

Kövesi B, Saoudi S, Boucher J M, Horváth G. 1999. Real time vector quantization of LSP parameters. Speech Communication, 29, 39–47.

Latif S, Wang L P, Khan J, Ali Z, Sehgal S K, Babar M A, Wang J P, Quraishi U M. 2020. Deciphering the role of stay-green trait to mitigate terminal heat stress in bread wheat. Agronomy, 10, 1001.

Lee S, Masclaux-Daubresse C. 2021. Current understanding of leaf senescence in rice. International Journal of Molecular Sciences, 22, 4515.

Lei P, Yu F, Liu X Y. 2023. Recent advances in cellular degradation and nuclear control of leaf senescence. Journal of Experimental Botany, 74, 5472–5486.

Lopes M S, Reynolds M P. 2012. Stay-green in spring wheat can be determined by spectral reflectance measurements (normalized difference vegetation index) independently from phenology. Journal of Experimental Botany, 63, 3789–3798.

Masoni A, Ercoli L, Mariotti M, Arduini I. 2007. Post-anthesis accumulation and remobilization of dry matter nitrogen and phosphorus in durum wheat as affected by soil type. European Journal of Agronomy, 26, 179–186.

Mirosavljevic M, Momcilovic V, Mikic S, Trkulja D, Brbaklic L, Zoric M, Abicic I. 2020. Changes in stay-green and nitrogen use efficiency traits in historical set of winter barley cultivars. Field Crops Research, 249, 107740.

Moraga F, Alcaino M, Matus I, Castillo D, del Pozo A. 2022. Leaf and canopy traits associated with stay-green expression are closely related to yield components of wheat genotypes with contrasting tolerance to water stress. Plants, 11, 292.

Mu X, Chen Q, Chen F, Yuan L, Mi G. 2018. Dynamic remobilization of leaf nitrogen components in relation to photosynthetic rate during grain filling in maize. Plant Physiology and Biochemistry, 129, 27–34.

Pommel B, Gallais A, Coque M, Quillere I, Hirel B, Prioul J L, Andrieu B, Floriot M. 2006. Carbon and nitrogen allocation and grain filling in three maize hybrids differing in leaf senescence. European Journal of Agronomy, 24, 203–211.

Shin D, Lee S, Kim T H, Lee J H, Park J, Lee J, Lee J Y, Cho L H, Choi J Y, Lee W, Park J H, Lee D W, Ito H, Kim D H, Tanaka A, Cho J H, Song Y C, Hwang D, Purugganan M D, Jeon J S, et al. 2020. Natural variations at the Stay-Green gene promoter control lifespan and yield in rice cultivars. Nature Communications, 11, 2819.

Soudry E, Ulitzur S, Gepstein S. 2005. Accumulation and remobilization of amino acids during senescence of detached and attached leaves: in planta analysis of tryptophan levels by recombinant luminescent bacteria. Journal of Experimental Botany, 56, 695–702.

Tanaka M, Keira M, Yoon D K, Mae T, Ishida H, Makino A, Ishiyama K. 2022. Photosynthetic enhancement lifespan extension and leaf area enlargement in flag leaves increased the yield of transgenic rice plants overproducing rubisco under sufficient N fertilization. Rice, 15, 10.

Villegas-Velazquez I, Zavaleta-Mancera H A, Arévalo-Galarza M L, Suarez-Espinosa J, Garcia-Osorio C, Padilla-Chacon D, Galvan-Escobedo I G, Jimenez-Bremont J F. 2022. Chlorophyll measurements in Alstroemeria sp. using SPAD-502 meter and the color space CIE L*a*b* and its validation in foliar senescence. Photosynthetica, 60, 230–239.

Wang F B, Liu J C, Chen M X, Zhou L J, Li Z W, Zhao Q, Pan G, Zaidi S H R, Cheng F M. 2016a. Involvement of abscisic acid in PSII photodamage and D1 protein turnover for light-induced premature senescence of rice flag leaves. PLoS ONE, 11, e0161203.

Wang F B, Liu J C, Zhou L J, Pan G, Li Z W, Zaidi S H R, Cheng F M. 2016b. Senescence-specific change in ROS scavenging enzyme activities and regulation of various SOD isozymes to ROS levels in psf mutant rice leaves. Plant Physiology and Biochemistry, 109, 248–261.

Wen B B, Gong X Y, Tan Q P, Zhao W Z, Chen X D, Li D M, Li L, Xiao W. 2022. MdNAC4 interacts with MdAPRR2 to regulate nitrogen deficiency-induced leaf senescence in apple (Malus domestica). Frontiers in Plant Sciences, 13, 925035.

Woo H R, Kim H J, Lim P O, Nam H G. 2019. Leaf senescence: Systems and dynamics aspects. Annual Review of Plant Biology, 70, 347–376.

Xie Q, Mayes S, Sparkes D L. 2016. Early anthesis and delayed but fast leaf senescence contribute to individual grain dry matter and water accumulation in wheat. Field Crops Research, 187, 24–34.

Xu F X, Xiong H, Zhang L, Guo X Y, Zhu Y C, Zhou X B, Liu M. 2009. Effects of the decreased index of SPAD value of leaf after full heading on ratooning ability. Scientia Agricultura Sinica, 42, 3442–3450. (in Chinese)

Zakari S A, Asad M A U, Han Z Y, Guan X Y, Zaidi S H R, Gang P, Cheng F M. 2019. Senescence-related translocation of nonstructural carbohydrate in rice leaf sheaths under different nitrogen supply. Agronomy, 112, 1601–1616.

Zakari S A, Asad M A U, Han Z Y, Zhao Q Y, Cheng F M. 2020. Relationship of nitrogen deficiency-induced leaf senescence with ROS generation and ABA concentration in rice flag leaves. Journal of Plant Growth Regulation, 39, 1503–1517.

Zhang L L, Zhou X L, Fan Y, Fu J, Hou P, Yang H L, Qi H. 2019. Post-silking nitrogen accumulation and remobilization are associated with green leaf persistence and plant density in maize. Journal of Integrative Agriculture, 18, 1882–1892.

Zhang W Y, Zhou Y J, Li C Q, Zhu K Y, Xu Y J, Wang W L, Liu L J, Zhang H, Gu J F, Wang Z Q, Zhang J H, Yang J C. 2022. Post-anthesis moderate soil-drying facilitates source-to-sink remobilization of nitrogen via redistributing cytokinins in rice. Field Crops Research, 288, 108692.

Zhou Z X, Struik P C, Gu J F, van der Putten P E L, Wang Z Q, Yin X Y, Yang J C. 2023. Leaf-colour modification affects canopy photosynthesis dry-matter accumulation and yield traits in rice. Field Crops Research, 290, 108746.

[1]	Yufei Ling, Qun Hu, Yuxin Xia, Kaiwei Zhang, Dihui Fu, Yuan Feng, Fangfu Xu, Guangyan Li, Zhipeng Xing, Hui Gao, Haiyan Wei, Hongcheng Zhang. Enhancing rice yield by optimizing tillering through transplantation of high-density seedlings cultivated on crop straw boards[J]. >Journal of Integrative Agriculture, 2026, 25(6): 0-.
[2]	Yuchen Song, Sijin Wang, Yuehong Du, Zhenyu Li, Yumeng Yuan, Yihan Chen, Wanwan Wang, Hongqiang Dong, Zhongyang Huo, You Liang. Development of biodegradable triple-stimuli-responsive mesoporous organosilica nanocarriers for targeted pesticide delivery and enhanced plant immunity in rice disease management[J]. >Journal of Integrative Agriculture, 2026, 25(6): 0-.
[3]	Min Xiong, Chuxin Wang, Xinrui Liang, Jiawen Yu, Tingting Liu, Bin Peng, Xiaoxuan Du, Tingyu Yang, Gongneng Feng, Qiaoquan Liu, Qianfeng Li. Multi-omics approach reveals the contribution of brassinosteroids to salt tolerance for seed germination in rice[J]. >Journal of Integrative Agriculture, 2026, 25(6): 2288-2298.
[4]	Bo Zhou, Kuopeng Xie, Muhammad Azhar Iqbal, Tariq Ali. Drivers and barriers to unmanned aerial vehicle (UAV) adoption in agriculture: Evidence from Jiangxi Province, China[J]. >Journal of Integrative Agriculture, 2026, 25(6): 2201-2213.
[5]	Hua Zhang, Lena Kuhn, Hang Xiong, Zhanli Sun. Farmers’ preferences for agricultural drone services under uncertainty: A choice experiment in Hubei, China[J]. >Journal of Integrative Agriculture, 2026, 25(6): 2188-2200.
[6]	Chenchen Zhang, Yan Wang, Lu Chen, Xixi Wang, Sheng Teng. Advances in rice synthetic biology: Toward a better staple crop and beyond[J]. >Journal of Integrative Agriculture, 2026, 25(5): 1741-1759.
[7]	Junwei Wang, Qi Zou, Huimin Yuan. Improved selected soil properties predictions using MIR and pXRF sensor fusion[J]. >Journal of Integrative Agriculture, 2026, 25(4): 1687-1699.
[8]	Haihe Gao, Changrong Yan, Joann K. Whalen, Wenqing He, Hongjin Liu, Jixiao Cui, Daozhi Gong, Karen Mancl, Qin Liu, Xurong Mei. Biodegradable mulch films support root proliferation and yield in water-saving rice production[J]. >Journal of Integrative Agriculture, 2026, 25(4): 1664-1674.
[9]	Xiaoxiao Song, Cong Dang, Ran Li, Fang Wang, Hongwei Yao, David W. Stanley, Gongyin Ye. Monitoring agricultural arthropod diversity by eDNA metabarcoding from plant cleaning fluid[J]. >Journal of Integrative Agriculture, 2026, 25(4): 1586-1596.
[10]	Chunhai Liu, Chao Wu, Zheming Yuan, Bingchuan Tian, Peiyi Yu, Deze Xu, Xingfei Zheng, Lanzhi Li. Multi-trait genome-wide association studies reveal novel pleiotropic loci associated with yield and yield-related traits in rice[J]. >Journal of Integrative Agriculture, 2026, 25(4): 1359-1372.
[11]	Qiaohong Fan, Jingnan Zou, Zhimin Lin, Gui Chen, Wu You, Kai Su, Wenxiong Lin. Underlying mechanisms of high carbon budget surplus in low-stubble rice ratooning in Southeast China[J]. >Journal of Integrative Agriculture, 2026, 25(3): 918-937.
[12]	Lu Zhang, Ze Qu, Yihui Tan, Yao Li, Xinyi Li, Zhipeng Huang, Siyuan Ruan, Shimin Zuo, Fang Liu, Wenxing Hu. Rice stripe virus protein NS3 exploits synergistically insect vector importin and ubiquitin systems to promote viral replication[J]. >Journal of Integrative Agriculture, 2026, 25(3): 1087-1098.
[13]	Hao Wu, Wenjiang Jing, Yajun Zhang, Ying Zhang, Weilu Wang, Kuanyu Zhu, Weiyang Zhang, Junfei Gu, Lijun Liu, Jianhua Zhang, Hao Zhang. Optimized application strategy of controlled-release nitrogen improves grain yield, nitrogen use efficiency and lodging resistance of rice[J]. >Journal of Integrative Agriculture, 2026, 25(3): 903-917.
[14]	Valensi Kautsar, Takamori Kanno, Kaho Sakai, Riza Kurnia Sabri, Keitaro Tawaraya, Kazunobu Toriyama, Kazuhiko Kobayashi, Weiguo Cheng. Reconstructed organic rice fields: Effects on soil organic carbon, total nitrogen, their mineralization, and rice yield in Japanese Andosols[J]. >Journal of Integrative Agriculture, 2026, 25(2): 493-500.
[15]	Jun Deng, Ke Liu, Xiangqian Feng, Jiayu Ye, Matthew Tom Harrison, Peter de Voil, Tajamul Hussain, Liying Huang, Xiaohai Tian, Meixue Zhou, Yunbo Zhang. Exploring strategies for agricultural sustainability in super hybrid rice using the food–carbon–nitrogen–water–energy–profit nexus framework[J]. >Journal of Integrative Agriculture, 2026, 25(2): 624-638.

No Suggested Reading articles found!

Viewed

Full text

Abstract

Cited

Shared

Discussed

Cite this article:

About JIA

Editorial board

For authors