Abstract
A study was conducted to assess yield variability of paddy crop using automatic yield monitoring (AYM) system fitted on an indigenous grain combine harvester. Algorithms were developed to assess the on-farm yield variability and classify the field in different yield zones. Yield maps were created using ArcGIS and open source GeoDa software for four years (2014, 2015, 2016 and 2017). The calibration factor (CF) of AYM system for paddy crop was 6.79. Yield variations were recorded in one ha plot, and classified in five different yield zones of<1900 kg.ha-1, 2000-2999 kg.ha-1, 3000-3999 kg.ha-1, 4000-4999 kg.ha-1, and >5000 kg.ha-1. Variation in actual yield and yield measured by automatic yield monitor varied from (+) 2.8 to (+)5.1 per cent. Maximum temporal variability (14.7 %) was observed between the year 2014 and 2017. The AYM system could show the real-time temporal and spatial variability classification and quantification in paddy field.
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Claims 5
Claim · model-written summary
The calibration factor of the AYM system for paddy crop was 6.79.
Verbatim
e0“assess yield variability of paddy crop using automatic yield monitoring (AYM) system”
e1“The calibration factor (CF) of AYM system for paddy crop was 6.79”
Claim · model-written summary
Yield measured by the automatic yield monitor differed from actual yield by +2.8 to +5.1%.
Verbatim
e0“assess yield variability of paddy crop using automatic yield monitoring (AYM) system”
e2“Variation in actual yield and yield measured by automatic yield monitor varied from (+) 2.8 to (+)5.1 per cent”
Claim · model-written summary
Maximum temporal yield variability in paddy was 14.7%, observed between 2014 and 2017.
Verbatim
e0“assess yield variability of paddy crop using automatic yield monitoring (AYM) system”
e3“Maximum temporal variability (14.7 %) was observed between the year 2014 and 2017”
Claim · model-written summary
Paddy yield in the one-hectare plot was classified into five different yield zones.
Verbatim
e0“assess yield variability of paddy crop using automatic yield monitoring (AYM) system”
e4“Yield variations were recorded in one ha plot, and classified in five different yield zones”
Claim · model-written summary
The AYM system showed real-time temporal and spatial yield variability classification and quantification in paddy field.
Verbatim
e0“assess yield variability of paddy crop using automatic yield monitoring (AYM) system”
e5“The AYM system could show the real-time temporal and spatial variability classification and quantification in paddy field”