Influences of residual stomatal conductance on the intrinsic water use efficiency of two C3 and two C4 species

IF 5.9 1区 农林科学 Q1 AGRONOMY Agricultural Water Management Pub Date : 2024-11-20 DOI:10.1016/j.agwat.2024.109136
Zi Piao Ye, Jian Qiang He, Ting An, Shi Hua Duan, Hua Jing Kang, Fu Biao Wang
{"title":"Influences of residual stomatal conductance on the intrinsic water use efficiency of two C3 and two C4 species","authors":"Zi Piao Ye, Jian Qiang He, Ting An, Shi Hua Duan, Hua Jing Kang, Fu Biao Wang","doi":"10.1016/j.agwat.2024.109136","DOIUrl":null,"url":null,"abstract":"Intrinsic water use efficiency (<ce:italic>WUE</ce:italic><ce:inf loc=\"post\">i</ce:inf>) is a critical parameter that encapsulates the equilibrium between carbon assimilation and the concomitant water expenditure. Enhancing the <ce:italic>WUE</ce:italic><ce:inf loc=\"post\">i</ce:inf> of crops is not only instrumental in bolstering their resilience to drought but also enables higher carbon fixation efficiency under conditions of scarce water resources. Improving the <ce:italic>WUE</ce:italic><ce:inf loc=\"post\">i</ce:inf> of crop varieties has become a major goal because water has become a critical limiting factor in crop productivity within the context of global change. The <ce:italic>WUE</ce:italic><ce:inf loc=\"post\">i</ce:inf>, traditionally calculated by <mml:math altimg=\"si0001.svg\"><mml:mrow><mml:mi>W</mml:mi><mml:mi>U</mml:mi><mml:msub><mml:mrow><mml:mi>E</mml:mi></mml:mrow><mml:mrow><mml:mi mathvariant=\"normal\">i</mml:mi></mml:mrow></mml:msub><mml:mo linebreak=\"goodbreak\">=</mml:mo><mml:mrow><mml:mrow><mml:mo stretchy=\"true\">(</mml:mo><mml:mrow><mml:msub><mml:mrow><mml:mi>C</mml:mi></mml:mrow><mml:mrow><mml:mi mathvariant=\"normal\">a</mml:mi></mml:mrow></mml:msub><mml:mo linebreak=\"badbreak\">−</mml:mo><mml:msub><mml:mrow><mml:mi>C</mml:mi></mml:mrow><mml:mrow><mml:mi mathvariant=\"normal\">i</mml:mi></mml:mrow></mml:msub></mml:mrow><mml:mo stretchy=\"true\">)</mml:mo></mml:mrow><mml:mo>/</mml:mo><mml:mrow><mml:mn>1.6</mml:mn></mml:mrow></mml:mrow></mml:mrow></mml:math>(<ce:italic>C</ce:italic><ce:inf loc=\"post\">a</ce:inf>, atmospheric CO<ce:inf loc=\"post\">2</ce:inf> concentration; <ce:italic>C</ce:italic><ce:inf loc=\"post\">i</ce:inf>, intercellular CO<ce:inf loc=\"post\">2</ce:inf> concentration), may vary from that derived from <mml:math altimg=\"si0002.svg\"><mml:mrow><mml:mi>W</mml:mi><mml:mi>U</mml:mi><mml:msub><mml:mrow><mml:mi>E</mml:mi></mml:mrow><mml:mrow><mml:mi mathvariant=\"normal\">i</mml:mi></mml:mrow></mml:msub><mml:mo linebreak=\"goodbreak\">=</mml:mo><mml:mrow><mml:mi>A</mml:mi><mml:mo>/</mml:mo><mml:mrow><mml:msub><mml:mrow><mml:mi>g</mml:mi></mml:mrow><mml:mrow><mml:mi mathvariant=\"normal\">sw</mml:mi></mml:mrow></mml:msub></mml:mrow></mml:mrow></mml:mrow></mml:math>(<ce:italic>A</ce:italic>, net photosynthetic rate; <ce:italic>g</ce:italic><ce:inf loc=\"post\">sw</ce:inf>, stomatal conductance to water vapor). In the study, the LI-6400 portable photosynthesis system was used for monitoring the leaf gas exchange of two C<ce:inf loc=\"post\">3</ce:inf> (soybean and wheat) and two C<ce:inf loc=\"post\">4</ce:inf> (maize and grain amaranth) species under changing irradiance (<ce:italic>I</ce:italic>) and CO<ce:inf loc=\"post\">2</ce:inf> concentration conditions. One paired-sample <ce:italic>t</ce:italic> test was used to compare the significant differences between <ce:italic>WUE</ce:italic><ce:inf loc=\"post\">i</ce:inf> values calculated by different equations and the observed values. The results showed that <mml:math altimg=\"si0003.svg\"><mml:mrow><mml:mi>W</mml:mi><mml:mi>U</mml:mi><mml:msub><mml:mrow><mml:mi>E</mml:mi></mml:mrow><mml:mrow><mml:mi mathvariant=\"normal\">i</mml:mi></mml:mrow></mml:msub><mml:mo linebreak=\"goodbreak\">=</mml:mo><mml:mrow><mml:mrow><mml:mo stretchy=\"true\">(</mml:mo><mml:mrow><mml:msub><mml:mrow><mml:mi>C</mml:mi></mml:mrow><mml:mrow><mml:mi mathvariant=\"normal\">a</mml:mi></mml:mrow></mml:msub><mml:mo linebreak=\"badbreak\">−</mml:mo><mml:msub><mml:mrow><mml:mi>C</mml:mi></mml:mrow><mml:mrow><mml:mi mathvariant=\"normal\">i</mml:mi></mml:mrow></mml:msub></mml:mrow><mml:mo stretchy=\"true\">)</mml:mo></mml:mrow><mml:mo>/</mml:mo><mml:mrow><mml:mn>1.6</mml:mn></mml:mrow></mml:mrow></mml:mrow></mml:math> significantly overestimated the calculated <ce:italic>WUE</ce:italic><ce:inf loc=\"post\">i</ce:inf> values than their corresponding observations by at least 17.78 %, 23.20 %, 9.07 %, and 14.26 % in light-response of <ce:italic>WUE</ce:italic><ce:inf loc=\"post\">i</ce:inf> (<ce:italic>WUE</ce:italic><ce:inf loc=\"post\">i</ce:inf><ce:italic>–I</ce:italic>) and by at least 23.28 %, 22.02 %, 13.44 %, and 12.59 % in CO<ce:inf loc=\"post\">2</ce:inf>-response of <ce:italic>WUE</ce:italic><ce:inf loc=\"post\">i</ce:inf> (<ce:italic>WUE</ce:italic><ce:inf loc=\"post\">i</ce:inf>–<ce:italic>C</ce:italic><ce:inf loc=\"post\">i</ce:inf>) curves for soybean, wheat, maize, and grain amaranth, respectively. However, the relationship between net photosynthetic rate (<ce:italic>A</ce:italic>) and stomatal conductance to CO<ce:inf loc=\"post\">2</ce:inf> (<ce:italic>g</ce:italic><ce:inf loc=\"post\">sc</ce:inf>) can be improved by incorporating an empirical slope (<ce:italic>g</ce:italic><ce:inf loc=\"post\">1</ce:inf>) and residual stomatal conductance (<ce:italic>g</ce:italic><ce:inf loc=\"post\">0</ce:inf>), which can be characterized as<mml:math altimg=\"si0004.svg\"><mml:mrow><mml:mi>A</mml:mi><mml:mo linebreak=\"goodbreak\">=</mml:mo><mml:mrow><mml:mo stretchy=\"true\">(</mml:mo><mml:mrow><mml:msub><mml:mrow><mml:mi>g</mml:mi></mml:mrow><mml:mrow><mml:mi mathvariant=\"normal\">sc</mml:mi></mml:mrow></mml:msub><mml:mo>–</mml:mo><mml:msub><mml:mrow><mml:mi>g</mml:mi></mml:mrow><mml:mrow><mml:mn>0</mml:mn></mml:mrow></mml:msub></mml:mrow><mml:mo stretchy=\"true\">)</mml:mo></mml:mrow><mml:mrow><mml:mo stretchy=\"true\">(</mml:mo><mml:mrow><mml:msub><mml:mrow><mml:mi>C</mml:mi></mml:mrow><mml:mrow><mml:mi mathvariant=\"normal\">a</mml:mi></mml:mrow></mml:msub><mml:mo>–</mml:mo><mml:msub><mml:mrow><mml:mi>C</mml:mi></mml:mrow><mml:mrow><mml:mi mathvariant=\"normal\">i</mml:mi></mml:mrow></mml:msub></mml:mrow><mml:mo stretchy=\"true\">)</mml:mo></mml:mrow><mml:mo>/</mml:mo><mml:msub><mml:mrow><mml:mi>g</mml:mi></mml:mrow><mml:mrow><mml:mn>1</mml:mn></mml:mrow></mml:msub></mml:mrow></mml:math>. Consequently, <ce:italic>WUE</ce:italic><ce:inf loc=\"post\">i</ce:inf> can be calculated by <mml:math altimg=\"si0005.svg\"><mml:mrow><mml:mi>W</mml:mi><mml:mi>U</mml:mi><mml:msub><mml:mrow><mml:mi>E</mml:mi></mml:mrow><mml:mrow><mml:mi mathvariant=\"normal\">i</mml:mi></mml:mrow></mml:msub><mml:mo linebreak=\"goodbreak\">=</mml:mo><mml:mfrac><mml:mn>1</mml:mn><mml:mrow><mml:mn>1.6</mml:mn><mml:msub><mml:mrow><mml:mi>g</mml:mi></mml:mrow><mml:mrow><mml:mn>1</mml:mn></mml:mrow></mml:msub></mml:mrow></mml:mfrac><mml:mrow><mml:mo stretchy=\"true\">(</mml:mo><mml:mrow><mml:mn>1</mml:mn><mml:mo linebreak=\"badbreak\">−</mml:mo><mml:mfrac><mml:mrow><mml:mn>1.6</mml:mn><mml:msub><mml:mrow><mml:mi>g</mml:mi></mml:mrow><mml:mrow><mml:mn mathvariant=\"normal\">0</mml:mn></mml:mrow></mml:msub></mml:mrow><mml:mrow><mml:msub><mml:mrow><mml:mi>g</mml:mi></mml:mrow><mml:mrow><mml:mi mathvariant=\"normal\">sw</mml:mi></mml:mrow></mml:msub></mml:mrow></mml:mfrac></mml:mrow><mml:mo stretchy=\"true\">)</mml:mo></mml:mrow><mml:mrow><mml:mo stretchy=\"true\">(</mml:mo><mml:mrow><mml:msub><mml:mrow><mml:mi>C</mml:mi></mml:mrow><mml:mrow><mml:mi mathvariant=\"normal\">a</mml:mi></mml:mrow></mml:msub><mml:mo linebreak=\"badbreak\">−</mml:mo><mml:msub><mml:mrow><mml:mi>C</mml:mi></mml:mrow><mml:mrow><mml:mi mathvariant=\"normal\">i</mml:mi></mml:mrow></mml:msub></mml:mrow><mml:mo stretchy=\"true\">)</mml:mo></mml:mrow></mml:mrow></mml:math>. It is highlighted that this modified equation can not only more accurately characterize the <ce:italic>WUE</ce:italic><ce:inf loc=\"post\">i</ce:inf> in responses to varying <ce:italic>I</ce:italic> and CO<ce:inf loc=\"post\">2</ce:inf> concentration conditions but also yields a remarkably high coefficient of determination (<ce:italic>R</ce:italic><ce:sup loc=\"post\">2</ce:sup> &gt; 0.989) for the four species. These findings will provide plant physiologists and agronomists with a precise calculation tool to better understand and optimize crop water use efficiency in the face of environmental challenges.","PeriodicalId":7634,"journal":{"name":"Agricultural Water Management","volume":"33 1","pages":""},"PeriodicalIF":5.9000,"publicationDate":"2024-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Agricultural Water Management","FirstCategoryId":"97","ListUrlMain":"https://doi.org/10.1016/j.agwat.2024.109136","RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"AGRONOMY","Score":null,"Total":0}
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Abstract

Intrinsic water use efficiency (WUEi) is a critical parameter that encapsulates the equilibrium between carbon assimilation and the concomitant water expenditure. Enhancing the WUEi of crops is not only instrumental in bolstering their resilience to drought but also enables higher carbon fixation efficiency under conditions of scarce water resources. Improving the WUEi of crop varieties has become a major goal because water has become a critical limiting factor in crop productivity within the context of global change. The WUEi, traditionally calculated by WUEi=(CaCi)/1.6(Ca, atmospheric CO2 concentration; Ci, intercellular CO2 concentration), may vary from that derived from WUEi=A/gsw(A, net photosynthetic rate; gsw, stomatal conductance to water vapor). In the study, the LI-6400 portable photosynthesis system was used for monitoring the leaf gas exchange of two C3 (soybean and wheat) and two C4 (maize and grain amaranth) species under changing irradiance (I) and CO2 concentration conditions. One paired-sample t test was used to compare the significant differences between WUEi values calculated by different equations and the observed values. The results showed that WUEi=(CaCi)/1.6 significantly overestimated the calculated WUEi values than their corresponding observations by at least 17.78 %, 23.20 %, 9.07 %, and 14.26 % in light-response of WUEi (WUEi–I) and by at least 23.28 %, 22.02 %, 13.44 %, and 12.59 % in CO2-response of WUEi (WUEiCi) curves for soybean, wheat, maize, and grain amaranth, respectively. However, the relationship between net photosynthetic rate (A) and stomatal conductance to CO2 (gsc) can be improved by incorporating an empirical slope (g1) and residual stomatal conductance (g0), which can be characterized asA=(gscg0)(CaCi)/g1. Consequently, WUEi can be calculated by WUEi=11.6g1(11.6g0gsw)(CaCi). It is highlighted that this modified equation can not only more accurately characterize the WUEi in responses to varying I and CO2 concentration conditions but also yields a remarkably high coefficient of determination (R2 > 0.989) for the four species. These findings will provide plant physiologists and agronomists with a precise calculation tool to better understand and optimize crop water use efficiency in the face of environmental challenges.
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残余气孔导度对两种 C3 和两种 C4 物种内在水分利用效率的影响
内在水分利用效率(WUEi)是一个关键参数,它体现了碳同化与相应水分消耗之间的平衡。提高作物的水分利用效率不仅有助于增强作物的抗旱能力,还能在水资源匮乏的条件下提高碳固定效率。提高作物品种的WUEi已成为一个主要目标,因为在全球变化的背景下,水已成为作物生产力的一个关键限制因素。传统的 WUEi 计算公式为 WUEi=(Ca-Ci)/1.6(Ca,大气二氧化碳浓度;Ci,细胞间二氧化碳浓度),与 WUEi=A/gsw(A,净光合速率;gsw,气孔对水蒸气的传导率)得出的 WUEi 可能有所不同。本研究使用 LI-6400 便携式光合作用系统监测两个 C3(大豆和小麦)和两个 C4(玉米和谷粒苋)物种在辐照度(I)和二氧化碳浓度变化条件下的叶片气体交换。采用配对样本 t 检验比较不同方程计算的 WUEi 值与观测值之间的显著差异。结果表明,WUEi=(Ca-Ci)/1.6 与相应的观测值相比,分别高估了至少 17.78 %、23.20 %、9.07 % 和 14.26 %。在大豆、小麦、玉米和籽粒苋的 WUEi 的光响应曲线(WUEi-I)中,分别高估了至少 17.78 %、23.20 %、9.07 % 和 14.26 %;在 WUEi 的 CO2 响应曲线(WUEi-Ci)中,分别高估了至少 23.28 %、22.02 %、13.44 % 和 12.59 %。不过,净光合速率(A)和气孔对 CO2 的传导(gsc)之间的关系可以通过加入经验斜率(g1)和残余气孔传导(g0)来改进,其特征为:A=(gsc-g0)(Ca-Ci)/g1。因此,WUEi 的计算公式为 WUEi=11.6g1(1-1.6g0gsw)(Ca-Ci)。该公式不仅能更准确地描述 WUEi 对不同 I 和 CO2 浓度条件的响应,而且对四个物种的判定系数(R2 >0.989)也非常高。这些发现将为植物生理学家和农学家提供一个精确的计算工具,以便在面临环境挑战时更好地理解和优化作物的水分利用效率。
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来源期刊
Agricultural Water Management
Agricultural Water Management 农林科学-农艺学
CiteScore
12.10
自引率
14.90%
发文量
648
审稿时长
4.9 months
期刊介绍: Agricultural Water Management publishes papers of international significance relating to the science, economics, and policy of agricultural water management. In all cases, manuscripts must address implications and provide insight regarding agricultural water management.
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