A method for estimating yield of maize inbred lines by assimilating WOFOST model with Sentinel-2 satellite data
Maize is the most widely planted food crop in China, and maize inbred lines, as the basis of maize genetic breeding and seed breeding, have a significant impact on China’s seed security and food safety. Satellite remote sensing technology has been widely used for growth monitoring and yield estimati...
| Main Authors: | , , , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Frontiers Media S.A.
2023-09-01
|
| Series: | Frontiers in Plant Science |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fpls.2023.1201179/full |
| _version_ | 1827822398762647552 |
|---|---|
| author | Junyi Liu Xianpeng Hou Shuaiming Chen Yanhua Mu Hai Huang Hengbin Wang Zhe Liu Zhe Liu Shaoming Li Shaoming Li Xiaodong Zhang Xiaodong Zhang Yuanyuan Zhao Yuanyuan Zhao Jianxi Huang Jianxi Huang |
| author_facet | Junyi Liu Xianpeng Hou Shuaiming Chen Yanhua Mu Hai Huang Hengbin Wang Zhe Liu Zhe Liu Shaoming Li Shaoming Li Xiaodong Zhang Xiaodong Zhang Yuanyuan Zhao Yuanyuan Zhao Jianxi Huang Jianxi Huang |
| author_sort | Junyi Liu |
| collection | DOAJ |
| description | Maize is the most widely planted food crop in China, and maize inbred lines, as the basis of maize genetic breeding and seed breeding, have a significant impact on China’s seed security and food safety. Satellite remote sensing technology has been widely used for growth monitoring and yield estimation of various crops, but it is still doubtful whether the existing remote sensing monitoring means can distinguish the growth difference between maize inbred lines and hybrids and accurately estimate the yield of maize inbred lines. This paper explores a method for estimating the yield of maize inbred lines based on the assimilation of crop models and remote sensing data, initially solves the problem. At first, this paper analyzed the WOFOST(World Food Studies)model parameter sensitivity and used the MCMC(Markov Chain Monte Carlo) method to calibrate the sensitive parameters to obtain the parameter set of maize inbred lines differing from common hybrid maize; then the vegetation indices were selected to establish an empirical model with the measured LAI(Leaf Area Index) at three key development stages to obtain the remotely sensed estimated LAI; finally, the yield of maize inbred lines in the study area was estimated and mapped pixel by pixel using the EnKF(Ensemble Kalman Filter) data assimilation algorithm. Also, this paper compares a method of assimilation by setting a single parameter. Instead of the WOFOST parameter optimization process, a parameter representing the growth weakness of the inbred lines was set in WOFOST to distinguish the inbred lines from the hybrids. The results showed that the yield estimated by the two methods compared with the field measured yield data had R2: 0.56 and 0.18, and RMSE: 684.90 Kg/Ha and 949.95 Kg/Ha, respectively, which proved that the crop growth model of maize inbred lines established in this study combined with the data assimilation method could initially achieve the growth monitoring and yield estimation of maize inbred lines. |
| first_indexed | 2024-03-12T01:57:28Z |
| format | Article |
| id | doaj.art-a9cd868c0f1b484ca843f714f5de6b05 |
| institution | Directory Open Access Journal |
| issn | 1664-462X |
| language | English |
| last_indexed | 2024-03-12T01:57:28Z |
| publishDate | 2023-09-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Plant Science |
| spelling | doaj.art-a9cd868c0f1b484ca843f714f5de6b052023-09-07T22:14:06ZengFrontiers Media S.A.Frontiers in Plant Science1664-462X2023-09-011410.3389/fpls.2023.12011791201179A method for estimating yield of maize inbred lines by assimilating WOFOST model with Sentinel-2 satellite dataJunyi Liu0Xianpeng Hou1Shuaiming Chen2Yanhua Mu3Hai Huang4Hengbin Wang5Zhe Liu6Zhe Liu7Shaoming Li8Shaoming Li9Xiaodong Zhang10Xiaodong Zhang11Yuanyuan Zhao12Yuanyuan Zhao13Jianxi Huang14Jianxi Huang15College of Land Science and Technology, China Agricultural University, Beijing, ChinaCollege of Land Science and Technology, China Agricultural University, Beijing, ChinaCollege of Land Science and Technology, China Agricultural University, Beijing, ChinaCollege of Land Science and Technology, China Agricultural University, Beijing, ChinaCollege of Land Science and Technology, China Agricultural University, Beijing, ChinaCollege of Land Science and Technology, China Agricultural University, Beijing, ChinaCollege of Land Science and Technology, China Agricultural University, Beijing, ChinaKey Laboratory of Remote Sensing for Agri-Hazards, Ministry of Agriculture and Rural Affairs, Beijing, ChinaCollege of Land Science and Technology, China Agricultural University, Beijing, ChinaKey Laboratory of Remote Sensing for Agri-Hazards, Ministry of Agriculture and Rural Affairs, Beijing, ChinaCollege of Land Science and Technology, China Agricultural University, Beijing, ChinaKey Laboratory of Remote Sensing for Agri-Hazards, Ministry of Agriculture and Rural Affairs, Beijing, ChinaCollege of Land Science and Technology, China Agricultural University, Beijing, ChinaKey Laboratory of Remote Sensing for Agri-Hazards, Ministry of Agriculture and Rural Affairs, Beijing, ChinaCollege of Land Science and Technology, China Agricultural University, Beijing, ChinaKey Laboratory of Remote Sensing for Agri-Hazards, Ministry of Agriculture and Rural Affairs, Beijing, ChinaMaize is the most widely planted food crop in China, and maize inbred lines, as the basis of maize genetic breeding and seed breeding, have a significant impact on China’s seed security and food safety. Satellite remote sensing technology has been widely used for growth monitoring and yield estimation of various crops, but it is still doubtful whether the existing remote sensing monitoring means can distinguish the growth difference between maize inbred lines and hybrids and accurately estimate the yield of maize inbred lines. This paper explores a method for estimating the yield of maize inbred lines based on the assimilation of crop models and remote sensing data, initially solves the problem. At first, this paper analyzed the WOFOST(World Food Studies)model parameter sensitivity and used the MCMC(Markov Chain Monte Carlo) method to calibrate the sensitive parameters to obtain the parameter set of maize inbred lines differing from common hybrid maize; then the vegetation indices were selected to establish an empirical model with the measured LAI(Leaf Area Index) at three key development stages to obtain the remotely sensed estimated LAI; finally, the yield of maize inbred lines in the study area was estimated and mapped pixel by pixel using the EnKF(Ensemble Kalman Filter) data assimilation algorithm. Also, this paper compares a method of assimilation by setting a single parameter. Instead of the WOFOST parameter optimization process, a parameter representing the growth weakness of the inbred lines was set in WOFOST to distinguish the inbred lines from the hybrids. The results showed that the yield estimated by the two methods compared with the field measured yield data had R2: 0.56 and 0.18, and RMSE: 684.90 Kg/Ha and 949.95 Kg/Ha, respectively, which proved that the crop growth model of maize inbred lines established in this study combined with the data assimilation method could initially achieve the growth monitoring and yield estimation of maize inbred lines.https://www.frontiersin.org/articles/10.3389/fpls.2023.1201179/fullmaize inbred linesWOFOSTdata assimilationSentinel-2EnKF |
| spellingShingle | Junyi Liu Xianpeng Hou Shuaiming Chen Yanhua Mu Hai Huang Hengbin Wang Zhe Liu Zhe Liu Shaoming Li Shaoming Li Xiaodong Zhang Xiaodong Zhang Yuanyuan Zhao Yuanyuan Zhao Jianxi Huang Jianxi Huang A method for estimating yield of maize inbred lines by assimilating WOFOST model with Sentinel-2 satellite data Frontiers in Plant Science maize inbred lines WOFOST data assimilation Sentinel-2 EnKF |
| title | A method for estimating yield of maize inbred lines by assimilating WOFOST model with Sentinel-2 satellite data |
| title_full | A method for estimating yield of maize inbred lines by assimilating WOFOST model with Sentinel-2 satellite data |
| title_fullStr | A method for estimating yield of maize inbred lines by assimilating WOFOST model with Sentinel-2 satellite data |
| title_full_unstemmed | A method for estimating yield of maize inbred lines by assimilating WOFOST model with Sentinel-2 satellite data |
| title_short | A method for estimating yield of maize inbred lines by assimilating WOFOST model with Sentinel-2 satellite data |
| title_sort | method for estimating yield of maize inbred lines by assimilating wofost model with sentinel 2 satellite data |
| topic | maize inbred lines WOFOST data assimilation Sentinel-2 EnKF |
| url | https://www.frontiersin.org/articles/10.3389/fpls.2023.1201179/full |
| work_keys_str_mv | AT junyiliu amethodforestimatingyieldofmaizeinbredlinesbyassimilatingwofostmodelwithsentinel2satellitedata AT xianpenghou amethodforestimatingyieldofmaizeinbredlinesbyassimilatingwofostmodelwithsentinel2satellitedata AT shuaimingchen amethodforestimatingyieldofmaizeinbredlinesbyassimilatingwofostmodelwithsentinel2satellitedata AT yanhuamu amethodforestimatingyieldofmaizeinbredlinesbyassimilatingwofostmodelwithsentinel2satellitedata AT haihuang amethodforestimatingyieldofmaizeinbredlinesbyassimilatingwofostmodelwithsentinel2satellitedata AT hengbinwang amethodforestimatingyieldofmaizeinbredlinesbyassimilatingwofostmodelwithsentinel2satellitedata AT zheliu amethodforestimatingyieldofmaizeinbredlinesbyassimilatingwofostmodelwithsentinel2satellitedata AT zheliu amethodforestimatingyieldofmaizeinbredlinesbyassimilatingwofostmodelwithsentinel2satellitedata AT shaomingli amethodforestimatingyieldofmaizeinbredlinesbyassimilatingwofostmodelwithsentinel2satellitedata AT shaomingli amethodforestimatingyieldofmaizeinbredlinesbyassimilatingwofostmodelwithsentinel2satellitedata AT xiaodongzhang amethodforestimatingyieldofmaizeinbredlinesbyassimilatingwofostmodelwithsentinel2satellitedata AT xiaodongzhang amethodforestimatingyieldofmaizeinbredlinesbyassimilatingwofostmodelwithsentinel2satellitedata AT yuanyuanzhao amethodforestimatingyieldofmaizeinbredlinesbyassimilatingwofostmodelwithsentinel2satellitedata AT yuanyuanzhao amethodforestimatingyieldofmaizeinbredlinesbyassimilatingwofostmodelwithsentinel2satellitedata AT jianxihuang amethodforestimatingyieldofmaizeinbredlinesbyassimilatingwofostmodelwithsentinel2satellitedata AT jianxihuang amethodforestimatingyieldofmaizeinbredlinesbyassimilatingwofostmodelwithsentinel2satellitedata AT junyiliu methodforestimatingyieldofmaizeinbredlinesbyassimilatingwofostmodelwithsentinel2satellitedata AT xianpenghou methodforestimatingyieldofmaizeinbredlinesbyassimilatingwofostmodelwithsentinel2satellitedata AT shuaimingchen methodforestimatingyieldofmaizeinbredlinesbyassimilatingwofostmodelwithsentinel2satellitedata AT yanhuamu methodforestimatingyieldofmaizeinbredlinesbyassimilatingwofostmodelwithsentinel2satellitedata AT haihuang methodforestimatingyieldofmaizeinbredlinesbyassimilatingwofostmodelwithsentinel2satellitedata AT hengbinwang methodforestimatingyieldofmaizeinbredlinesbyassimilatingwofostmodelwithsentinel2satellitedata AT zheliu methodforestimatingyieldofmaizeinbredlinesbyassimilatingwofostmodelwithsentinel2satellitedata AT zheliu methodforestimatingyieldofmaizeinbredlinesbyassimilatingwofostmodelwithsentinel2satellitedata AT shaomingli methodforestimatingyieldofmaizeinbredlinesbyassimilatingwofostmodelwithsentinel2satellitedata AT shaomingli methodforestimatingyieldofmaizeinbredlinesbyassimilatingwofostmodelwithsentinel2satellitedata AT xiaodongzhang methodforestimatingyieldofmaizeinbredlinesbyassimilatingwofostmodelwithsentinel2satellitedata AT xiaodongzhang methodforestimatingyieldofmaizeinbredlinesbyassimilatingwofostmodelwithsentinel2satellitedata AT yuanyuanzhao methodforestimatingyieldofmaizeinbredlinesbyassimilatingwofostmodelwithsentinel2satellitedata AT yuanyuanzhao methodforestimatingyieldofmaizeinbredlinesbyassimilatingwofostmodelwithsentinel2satellitedata AT jianxihuang methodforestimatingyieldofmaizeinbredlinesbyassimilatingwofostmodelwithsentinel2satellitedata AT jianxihuang methodforestimatingyieldofmaizeinbredlinesbyassimilatingwofostmodelwithsentinel2satellitedata |