Yayu Romdhonah, N. Fujiuchi, N. Takahashi, H. Nishina, K. Takayama
{"title":"Empirical Model for the Estimation of Whole-plant Photosynthetic Rate of Cherry Tomato Grown in a Commercial Greenhouse","authors":"Yayu Romdhonah, N. Fujiuchi, N. Takahashi, H. Nishina, K. Takayama","doi":"10.2525/ecb.59.117","DOIUrl":null,"url":null,"abstract":"There have been many works to improve productivity of greenhouse-grown tomato. One effort is to analyze the photosynthetic rate as it influences productivity (Hisaeda et al., 2007; Takayama et al., 2010). Thus, quantifying photosynthetic rates is essential to diagnose the plant condition as well as to achieve the optimum cultivation condition in the greenhouse in the speaking plant approach concept (Hashimoto, 1989; Udink ten Cate et al., 1978). To bridge the plant’s photosynthesis and greenhouse climate control, many researchers developed various kinds of mathematical models of the environmental response of photosynthesis. The models were used as research tools or analytical means, for forecasting, or to be implemented in a computerized system for climate control (Nederhoff and Vegter, 1994). Thornley’s model (Thornley, 1976), Acock’s model (Acock et al., 1978), TOMGRO (Dayan et al., 1993), and TOMSIM (Heuvelink, 1996) are some established models. Some studies used photosynthesis measurements of single-leaf (Thornley, 1976; Acock et al., 1978; Xin et al., 2019), other studies used canopy-level measurements in a closed chamber (Acock et al., 1978), or whole-greenhouse (Nederhoff and Vegter, 1994; Tsafaras and de Koning, 2017). However, these studies could not provide a realtime response of the photosynthesis of a full-size plant, as part of a community under greenhouse condition, to its environment. Furthermore, the variables used in the photosynthesis models vary among the models. The Thornley’s model used incident light flux density, ambient CO2 concentration, and dark respiration rate with three other parameters to calculate net photosynthesis of single leaf (Acock et al., 1978). The model was then constructed by Acock et al. (1978) for canopy photosynthesis in tomato. Nederhoff and Vegter (1994) used variables of photosynthetically active radiation (PAR, i.e., light flux, 400―700 nm), CO2 concentration, and leaf area index (LAI) in an empirical photosynthesis model. However, other environmental factors may also contribute to photosynthesis activity. Based on previous literature, photosynthesis activity has an apparent response to temperature (Castilla, 2013), and is affected by vapor pressure deficit (Acock et al., 1976; Shamshiri et al., 2018). The objective of the present study was to develop an empirical model for the estimation of the whole-plant net photosynthetic rate (Pn) of cherry tomato as a function of relevant greenhouse environmental factors. We used data of Pn at the whole-plant level as a real-time response to instantaneous PAR, air temperature, vapor pressure deficit,","PeriodicalId":85505,"journal":{"name":"Seibutsu kankyo chosetsu. [Environment control in biology","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Seibutsu kankyo chosetsu. [Environment control in biology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2525/ecb.59.117","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
There have been many works to improve productivity of greenhouse-grown tomato. One effort is to analyze the photosynthetic rate as it influences productivity (Hisaeda et al., 2007; Takayama et al., 2010). Thus, quantifying photosynthetic rates is essential to diagnose the plant condition as well as to achieve the optimum cultivation condition in the greenhouse in the speaking plant approach concept (Hashimoto, 1989; Udink ten Cate et al., 1978). To bridge the plant’s photosynthesis and greenhouse climate control, many researchers developed various kinds of mathematical models of the environmental response of photosynthesis. The models were used as research tools or analytical means, for forecasting, or to be implemented in a computerized system for climate control (Nederhoff and Vegter, 1994). Thornley’s model (Thornley, 1976), Acock’s model (Acock et al., 1978), TOMGRO (Dayan et al., 1993), and TOMSIM (Heuvelink, 1996) are some established models. Some studies used photosynthesis measurements of single-leaf (Thornley, 1976; Acock et al., 1978; Xin et al., 2019), other studies used canopy-level measurements in a closed chamber (Acock et al., 1978), or whole-greenhouse (Nederhoff and Vegter, 1994; Tsafaras and de Koning, 2017). However, these studies could not provide a realtime response of the photosynthesis of a full-size plant, as part of a community under greenhouse condition, to its environment. Furthermore, the variables used in the photosynthesis models vary among the models. The Thornley’s model used incident light flux density, ambient CO2 concentration, and dark respiration rate with three other parameters to calculate net photosynthesis of single leaf (Acock et al., 1978). The model was then constructed by Acock et al. (1978) for canopy photosynthesis in tomato. Nederhoff and Vegter (1994) used variables of photosynthetically active radiation (PAR, i.e., light flux, 400―700 nm), CO2 concentration, and leaf area index (LAI) in an empirical photosynthesis model. However, other environmental factors may also contribute to photosynthesis activity. Based on previous literature, photosynthesis activity has an apparent response to temperature (Castilla, 2013), and is affected by vapor pressure deficit (Acock et al., 1976; Shamshiri et al., 2018). The objective of the present study was to develop an empirical model for the estimation of the whole-plant net photosynthetic rate (Pn) of cherry tomato as a function of relevant greenhouse environmental factors. We used data of Pn at the whole-plant level as a real-time response to instantaneous PAR, air temperature, vapor pressure deficit,
已经有许多工作来提高温室种植番茄的生产力。一项努力是分析光合速率对生产力的影响(Hisaeda等人,2007年;Takayama等人,2010年)。因此,量化光合速率对于诊断植物状况以及在温室中实现最佳栽培条件至关重要(Hashimoto,1989;Udink-ten-Cate等人,1978年)。为了将植物的光合作用与温室气候控制联系起来,许多研究人员开发了各种光合作用环境响应的数学模型。这些模型被用作研究工具或分析手段,用于预测,或在气候控制的计算机系统中实施(Nederhoff和Vetter,1994)。Thornley模型(Thornley,1976)、Acock模型(Acock et al.,1978)、TOMGRO(Dayan et al.,1993)和TOMSIM(Heuvelink,1996)是一些已建立的模型。一些研究使用了单叶片的光合作用测量(Thornley,1976;Acock等人,1978年;Xin等人,2019),其他研究使用了密闭室(Acock et al.,1978)或整个温室中的冠层水平测量(Nederhoff和Vetter,1994;Tsafaras和de Koning,2017)。然而,作为温室条件下群落的一部分,这些研究无法提供全尺寸植物光合作用对环境的实时响应。此外,光合作用模型中使用的变量因模型而异。Thornley模型使用入射光通量密度、环境CO2浓度和暗呼吸率以及其他三个参数来计算单叶片的净光合作用(Acock等人,1978)。Acock等人(1978)构建了番茄冠层光合作用模型。Nederhoff和Vetter(1994)在经验光合作用模型中使用了光合作用活性辐射(标准杆数,即光通量,400–700 nm)、CO2浓度和叶面积指数(LAI)等变量。然而,其他环境因素也可能有助于光合作用的活性。根据先前的文献,光合作用活性对温度有明显的反应(Castilla,2013),并受到蒸汽压不足的影响(Acock等人,1976;Shamshiri等人,2018)。本研究的目的是建立一个经验模型,用于估计樱桃番茄全株净光合速率(Pn)与相关温室环境因素的关系。我们使用整体水平的Pn数据作为对瞬时标准杆数、空气温度、蒸汽压不足的实时响应,