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> > 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}
引用次数: 0
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=(Ca−Ci)/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=(Ca−Ci)/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 (WUEi–Ci) 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=(gsc–g0)(Ca–Ci)/g1. Consequently, WUEi can be calculated by WUEi=11.6g1(1−1.6g0gsw)(Ca−Ci). 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.
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.