1Scientist, Agricultural Mechanization Division, ICAR-Central Institute of Agricultural Engineering, Bhopal-462038, India
2Project Coordinator, AICRP on ESA, ICAR-Central Institute of Agricultural Engineering, Bhopal-462038, India
*Corresponding author e-mail address: narendracae@gmail.com; narendra.chandel@icar.gov.in
Online published on 12 March, 2020.
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.
Automatic yield monitor, GPS, indigenous grain combine harvester, variability map, optical sensor
