Simulating Canopy Temperature Using a Random Forest Model to Calculate the Crop Water Stress Index of Chinese Brassica
The determination of crop water status has positive effects on the Chinese Brassica industry and irrigation decisions. Drought can decrease the production of Chinese Brassica, whereas over-irrigation can waste water. It is desirable to schedule irrigation when the crop suffers from water stress. In...
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| Format: | Article |
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MDPI AG
2021-11-01
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| Series: | Agronomy |
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| Online Access: | https://www.mdpi.com/2073-4395/11/11/2244 |
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| author | Mingxin Yang Peng Gao Ping Zhou Jiaxing Xie Daozong Sun Xiongzhe Han Weixing Wang |
| author_facet | Mingxin Yang Peng Gao Ping Zhou Jiaxing Xie Daozong Sun Xiongzhe Han Weixing Wang |
| author_sort | Mingxin Yang |
| collection | DOAJ |
| description | The determination of crop water status has positive effects on the Chinese Brassica industry and irrigation decisions. Drought can decrease the production of Chinese Brassica, whereas over-irrigation can waste water. It is desirable to schedule irrigation when the crop suffers from water stress. In this study, a random forest model was developed using sample data derived from meteorological measurements including air temperature (Ta), relative humidity (RH), wind speed (WS), and photosynthetic active radiation (Par) to predict the lower baseline (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mi>T</mi><mrow><mi>w</mi><mi>e</mi><mi>t</mi></mrow></msub></mrow></semantics></math></inline-formula>) and upper baseline (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mi>T</mi><mrow><mi>d</mi><mi>r</mi><mi>y</mi></mrow></msub></mrow></semantics></math></inline-formula>) canopy temperatures for Chinese Brassica from 27 November to 31 December 2020 (E1) and from 25 May to 20 June 2021 (E2). Crop water stress index (CWSI) values were determined based on the predicted canopy temperature and used to assess the crop water status. The study demonstrated the viability of using a random forest model to forecast <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mi>T</mi><mrow><mi>w</mi><mi>e</mi><mi>t</mi></mrow></msub></mrow></semantics></math></inline-formula> and <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mi>T</mi><mrow><mi>d</mi><mi>r</mi><mi>y</mi></mrow></msub></mrow></semantics></math></inline-formula>. The coefficients of determination (R<sup>2</sup>) in E1 were 0.90 and 0.88 for development and 0.80 and 0.77 for validation, respectively. The R<sup>2</sup> values in E2 were 0.91 and 0.89 for development and 0.83 and 0.80 for validation, respectively. Our results reveal that the measured and predicted CWSI values had similar R<sup>2</sup> values related to stomatal conductance (~0.5 in E1, ~0.6 in E2), whereas the CWSI showed a poor correlation with transpiration rate (~0.25 in E1, ~0.2 in E2). Finally, the methodology used to calculate the daily CWSI for Chinese Brassica in this study showed that both <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mi>T</mi><mrow><mi>w</mi><mi>e</mi><mi>t</mi></mrow></msub></mrow></semantics></math></inline-formula> and <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mi>T</mi><mrow><mi>d</mi><mi>r</mi><mi>y</mi></mrow></msub></mrow></semantics></math></inline-formula>, which require frequent measuring and design experiment due to the trial site and condition changes, have the potential to simulate environmental parameters and can therefore be applied to conveniently calculate the CWSI. |
| first_indexed | 2024-03-10T05:46:48Z |
| format | Article |
| id | doaj.art-1cb93c4db9c34ca5a496e00b6ba2c38e |
| institution | Directory Open Access Journal |
| issn | 2073-4395 |
| language | English |
| last_indexed | 2024-03-10T05:46:48Z |
| publishDate | 2021-11-01 |
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| series | Agronomy |
| spelling | doaj.art-1cb93c4db9c34ca5a496e00b6ba2c38e2023-11-22T22:02:41ZengMDPI AGAgronomy2073-43952021-11-011111224410.3390/agronomy11112244Simulating Canopy Temperature Using a Random Forest Model to Calculate the Crop Water Stress Index of Chinese BrassicaMingxin Yang0Peng Gao1Ping Zhou2Jiaxing Xie3Daozong Sun4Xiongzhe Han5Weixing Wang6College of Electronic Engineering, South China Agricultural University, Guangzhou 510642, ChinaCollege of Electronic Engineering, South China Agricultural University, Guangzhou 510642, ChinaCollege of Electronic Engineering, South China Agricultural University, Guangzhou 510642, ChinaCollege of Electronic Engineering, South China Agricultural University, Guangzhou 510642, ChinaCollege of Electronic Engineering, South China Agricultural University, Guangzhou 510642, ChinaDepartment of Biosystems Engineering, College of Agriculture and Life Sciences, Kangwon National University, Chuncheon 24341, KoreaCollege of Electronic Engineering, South China Agricultural University, Guangzhou 510642, ChinaThe determination of crop water status has positive effects on the Chinese Brassica industry and irrigation decisions. Drought can decrease the production of Chinese Brassica, whereas over-irrigation can waste water. It is desirable to schedule irrigation when the crop suffers from water stress. In this study, a random forest model was developed using sample data derived from meteorological measurements including air temperature (Ta), relative humidity (RH), wind speed (WS), and photosynthetic active radiation (Par) to predict the lower baseline (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mi>T</mi><mrow><mi>w</mi><mi>e</mi><mi>t</mi></mrow></msub></mrow></semantics></math></inline-formula>) and upper baseline (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mi>T</mi><mrow><mi>d</mi><mi>r</mi><mi>y</mi></mrow></msub></mrow></semantics></math></inline-formula>) canopy temperatures for Chinese Brassica from 27 November to 31 December 2020 (E1) and from 25 May to 20 June 2021 (E2). Crop water stress index (CWSI) values were determined based on the predicted canopy temperature and used to assess the crop water status. The study demonstrated the viability of using a random forest model to forecast <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mi>T</mi><mrow><mi>w</mi><mi>e</mi><mi>t</mi></mrow></msub></mrow></semantics></math></inline-formula> and <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mi>T</mi><mrow><mi>d</mi><mi>r</mi><mi>y</mi></mrow></msub></mrow></semantics></math></inline-formula>. The coefficients of determination (R<sup>2</sup>) in E1 were 0.90 and 0.88 for development and 0.80 and 0.77 for validation, respectively. The R<sup>2</sup> values in E2 were 0.91 and 0.89 for development and 0.83 and 0.80 for validation, respectively. Our results reveal that the measured and predicted CWSI values had similar R<sup>2</sup> values related to stomatal conductance (~0.5 in E1, ~0.6 in E2), whereas the CWSI showed a poor correlation with transpiration rate (~0.25 in E1, ~0.2 in E2). Finally, the methodology used to calculate the daily CWSI for Chinese Brassica in this study showed that both <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mi>T</mi><mrow><mi>w</mi><mi>e</mi><mi>t</mi></mrow></msub></mrow></semantics></math></inline-formula> and <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mi>T</mi><mrow><mi>d</mi><mi>r</mi><mi>y</mi></mrow></msub></mrow></semantics></math></inline-formula>, which require frequent measuring and design experiment due to the trial site and condition changes, have the potential to simulate environmental parameters and can therefore be applied to conveniently calculate the CWSI.https://www.mdpi.com/2073-4395/11/11/2244Chinese Brassicacanopy temperaturecrop water stress indexstomatal conductancerandom forest |
| spellingShingle | Mingxin Yang Peng Gao Ping Zhou Jiaxing Xie Daozong Sun Xiongzhe Han Weixing Wang Simulating Canopy Temperature Using a Random Forest Model to Calculate the Crop Water Stress Index of Chinese Brassica Agronomy Chinese Brassica canopy temperature crop water stress index stomatal conductance random forest |
| title | Simulating Canopy Temperature Using a Random Forest Model to Calculate the Crop Water Stress Index of Chinese Brassica |
| title_full | Simulating Canopy Temperature Using a Random Forest Model to Calculate the Crop Water Stress Index of Chinese Brassica |
| title_fullStr | Simulating Canopy Temperature Using a Random Forest Model to Calculate the Crop Water Stress Index of Chinese Brassica |
| title_full_unstemmed | Simulating Canopy Temperature Using a Random Forest Model to Calculate the Crop Water Stress Index of Chinese Brassica |
| title_short | Simulating Canopy Temperature Using a Random Forest Model to Calculate the Crop Water Stress Index of Chinese Brassica |
| title_sort | simulating canopy temperature using a random forest model to calculate the crop water stress index of chinese brassica |
| topic | Chinese Brassica canopy temperature crop water stress index stomatal conductance random forest |
| url | https://www.mdpi.com/2073-4395/11/11/2244 |
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