Theoretical frequencies of green area index （GAI） measurements were assessed in order to bring out the optimum frequencies for the monitoring of the senescence of winter wheat as well as the relationships between me...Theoretical frequencies of green area index （GAI） measurements were assessed in order to bring out the optimum frequencies for the monitoring of the senescence of winter wheat as well as the relationships between metrics which could be derived and the final grain yield. Several profiles of GAI decreasing curves were elaborated based on field measurements. Two functions, usually employed in green leaf area decreasing curves fitting （i.e., modified Gompertz and logistic functions） were then used to characterize the senescence phase and to calculate their metrics. These analyses showed that the two curve fitting functions satisfactorily described the senescence phase on frequencies of four to six GAI measurements, well distributed throughout a period of 30-35 days. The regression-based modeling showed that those involving metrics from logistic function （i.e., maximum value of GAI, green area duration and senescent rate） were more suitable than that of the modified Gompertz function for wheat yield estimates. Such results could be useful for studies at larger scales （involving remote sensing airplane or satellite data） and focused on the senescence in terms of optimum number of measurements and frequencies for developing models for yield estimates.展开更多
文摘Theoretical frequencies of green area index （GAI） measurements were assessed in order to bring out the optimum frequencies for the monitoring of the senescence of winter wheat as well as the relationships between metrics which could be derived and the final grain yield. Several profiles of GAI decreasing curves were elaborated based on field measurements. Two functions, usually employed in green leaf area decreasing curves fitting （i.e., modified Gompertz and logistic functions） were then used to characterize the senescence phase and to calculate their metrics. These analyses showed that the two curve fitting functions satisfactorily described the senescence phase on frequencies of four to six GAI measurements, well distributed throughout a period of 30-35 days. The regression-based modeling showed that those involving metrics from logistic function （i.e., maximum value of GAI, green area duration and senescent rate） were more suitable than that of the modified Gompertz function for wheat yield estimates. Such results could be useful for studies at larger scales （involving remote sensing airplane or satellite data） and focused on the senescence in terms of optimum number of measurements and frequencies for developing models for yield estimates.
