Measurement and modelling of Moringa transpiration for improved irrigation management

IF 5.9 1区 农林科学 Q1 AGRONOMY Agricultural Water Management Pub Date : 2024-10-30 DOI:10.1016/j.agwat.2024.109127
Ambroise Ndayakunze , Joachim Martin Steyn , Christian Phillipus du Plooy , Nadia Alcina Araya
{"title":"Measurement and modelling of Moringa transpiration for improved irrigation management","authors":"Ambroise Ndayakunze ,&nbsp;Joachim Martin Steyn ,&nbsp;Christian Phillipus du Plooy ,&nbsp;Nadia Alcina Araya","doi":"10.1016/j.agwat.2024.109127","DOIUrl":null,"url":null,"abstract":"<div><div>A greater understanding of Moringa (<em>Moringa oleifera</em> Lam.) transpiration (T) can assist in the development of accurate irrigation management tools. This study aimed at quantifying Moringa T by measuring and modelling the sap flow (SF) of intact stems using an improved heat balance technique. The study was conducted during two consecutive seasons (2021–2022 (Season 1) and 2022–2023 (Season 2)) at the Roodeplaat Experimental Farm of the Agricultural Research Council in South Africa. EXO-Skin sap flow sensors were used. Transpiration-related drivers such as weather and plant physiological parameters were measured simultaneously. The measured SF data in Seasons 1 and 2 were used to respectively parameterize and validate a canopy conductance T model. There was a positive correlation between the measured SF and its drivers, evidenced through coefficients of determination (R<sup>2</sup>) of 0.82, 0.99 and 0.92 for the relationships between SF and short-grass reference evapotranspiration (ET<sub>o</sub>), stem area and stomatal conductance, respectively. The measured and simulated SF varied from 0.82–1.29 and 0.71–1.19 mm tree<sup>−1</sup> day<sup>−1</sup> (model parameterization), as well as from 0.77–3.54 and 1.10–3.10 mm tree<sup>−1</sup> day<sup>−1</sup> (model validation). Despite the slight discrepancies between measured and predicted SF values during model performance evaluation, an acceptable agreement was achieved through root mean square errors (RMSEs) of 0.32 and 0.37 mm day<sup>−1</sup> and model efficiencies (Efs) of 0.93 and 0.88, for model parameterization and validation, respectively. The current study showed that the canopy conductance T model has the potential to accurately predict Moringa T and contribute to optimizing irrigation water management.</div></div>","PeriodicalId":7634,"journal":{"name":"Agricultural Water Management","volume":"305 ","pages":"Article 109127"},"PeriodicalIF":5.9000,"publicationDate":"2024-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Agricultural Water Management","FirstCategoryId":"97","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0378377424004633","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

A greater understanding of Moringa (Moringa oleifera Lam.) transpiration (T) can assist in the development of accurate irrigation management tools. This study aimed at quantifying Moringa T by measuring and modelling the sap flow (SF) of intact stems using an improved heat balance technique. The study was conducted during two consecutive seasons (2021–2022 (Season 1) and 2022–2023 (Season 2)) at the Roodeplaat Experimental Farm of the Agricultural Research Council in South Africa. EXO-Skin sap flow sensors were used. Transpiration-related drivers such as weather and plant physiological parameters were measured simultaneously. The measured SF data in Seasons 1 and 2 were used to respectively parameterize and validate a canopy conductance T model. There was a positive correlation between the measured SF and its drivers, evidenced through coefficients of determination (R2) of 0.82, 0.99 and 0.92 for the relationships between SF and short-grass reference evapotranspiration (ETo), stem area and stomatal conductance, respectively. The measured and simulated SF varied from 0.82–1.29 and 0.71–1.19 mm tree−1 day−1 (model parameterization), as well as from 0.77–3.54 and 1.10–3.10 mm tree−1 day−1 (model validation). Despite the slight discrepancies between measured and predicted SF values during model performance evaluation, an acceptable agreement was achieved through root mean square errors (RMSEs) of 0.32 and 0.37 mm day−1 and model efficiencies (Efs) of 0.93 and 0.88, for model parameterization and validation, respectively. The current study showed that the canopy conductance T model has the potential to accurately predict Moringa T and contribute to optimizing irrigation water management.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
测量和模拟辣木蒸腾作用,改进灌溉管理
进一步了解辣木(Moringa oleifera Lam.)的蒸腾作用(T)有助于开发精确的灌溉管理工具。本研究旨在利用改进的热平衡技术,通过测量和模拟完整茎干的汁液流(SF)来量化辣木的蒸腾作用。该研究在南非农业研究理事会的 Roodeplaat 试验农场连续进行了两季(2021-2022 年(第 1 季)和 2022-2023 年(第 2 季))。使用了 EXO-Skin 树液流传感器。同时测量了与蒸腾作用相关的驱动因素,如天气和植物生理参数。第 1 季和第 2 季测得的汁液流数据分别用于树冠传导 T 模型的参数化和验证。测得的 SF 与其驱动因素之间存在正相关,SF 与短灌草参考蒸散量(ETo)、茎杆面积和气孔导度之间的决定系数(R2)分别为 0.82、0.99 和 0.92。测量和模拟的 SF 变化范围分别为 0.82-1.29 和 0.71-1.19 毫米树-1 日-1(模型参数化),以及 0.77-3.54 和 1.10-3.10 毫米树-1 日-1(模型验证)。尽管在模型性能评估过程中,测得的 SF 值与预测的 SF 值略有出入,但在模型参数化和验证过程中,两者的均方根误差(RMSE)分别为 0.32 和 0.37 毫米-1 天-1,模型效率(Efs)分别为 0.93 和 0.88,两者的一致性可以接受。目前的研究表明,冠层传导 T 模型具有准确预测辣木 T 的潜力,有助于优化灌溉水管理。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
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.
期刊最新文献
Influences of residual stomatal conductance on the intrinsic water use efficiency of two C3 and two C4 species Accurate irrigation decision-making of winter wheat at the filling stage based on UAV hyperspectral inversion of leaf water content Comparative analysis of machine learning models and explainable AI for agriculture drought prediction: A case study of the Ta-pieh mountains Intermittent sprinkler irrigation during the establishment of strawberry (Fragaria ×ananassa Duch.) bare-root transplants conserves water without loss of yield and fruit quality Biochar enhances soil hydrological function by improving the pore structure of saline soil
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1