Potential yield and yield gap analysis of sugarcane (Saccharum officinarum) using the DSSAT-CANEGRO model in different districts of Uttar Pradesh, India
DOI:
https://doi.org/10.54386/jam.v23i2.60Keywords:
DSSAT-CANEGRO model, Uttar Pradesh, seasonal potential yield, yield gap analysisAbstract
DSSAT-CANEGRO model have been used to determine crop potential yield over eight districts (viz; Muzaffarnagar, Shahjahanpur, Agra, Lucknow, Basti, Faizabad, Allahabad and Jhansi) representing different agroclimatic conditions & environmentof Uttar Pradesh state in India. The thirty six years (1980-2016) daily weather data of above districts were used to simulate seasonal yield potentials under the various management conditions and compared with the respective district reported yield. The simulated mean potential yield by the CANEGRO model over different district of the state varied between 77.8 t ha-1 in Muzaffarnagar and 97.8 t ha-1 in Agra, while mean reported yield (fresh stalk mass) varied between 40.1 t ha-1 in Jhansi and 62.8 t ha-1 in Muzaffarnagar within the state. Similarly, the attainable yield by the model was simulated lowest of 65.1 t ha-1 in Shahjahanpur and the highest of 73.6 t ha-1 in Faizabad district. The management yield gap was between 9.0 to 30.0 t ha-1 while sowing yield gap was between 7.0 to 26.0 t ha-1 in different districts under study. Further it is not only interesting & surprising but also encouraging to growers that the trends in total yield gap at all the above districts in various agro-climatic zones were found decreasing (narrowed down) at the rate of 138.8 – 801.2 kg ha–1 year–1. Delayed planting by about 30 days in some of the districts resulted into a decrease in sugarcane yield to the tune of 106.7 to 146.7, 103.3 to 143.3 and 80.0 to 133.0 kg ha–1 day–1, respectively. Findings reveal that DSSAT crop simulation model can be an effective tool to aid in decision support system. Yield gap estimates using the past crop data and subsequent adjustment in planting window may help to achieve close to the potential yields.
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