2019˜The œinternational archives of the photogrammetry, remote sensing and spatial information sciences/International archives of the photogrammetry, remote sensing and spatial information sciencesOpen access

MULTI STAGE WHEAT YIELD ESTIMATION USING DIFFERENT MODEL UNDER SEMI ARID REGION OF INDIA

Ananta Vashisth, P. Krishanan, D.K. Joshi

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Abstract

Abstract. Crop yield estimation before harvest is required for marketing, pricing, storage, import, export etc. Productivity of cropping systems under various weather, management and policy scenarios can be predicted successfully by simulation models. Due to increase in input cost of agricultural operation, agriculture produces become costly. Therefore, crop yield estimation in the agriculture becomes essential. Weather variability causes the losses in the yield. Therefore, model based on weather parameters, soil parameter and crop parameters can provide reliable crop yield estimation in advance. For estimating the multi stage wheat crop yield, experiments were conducted at research farm of IARI, New Delhi during Rabi 2016–17 and Rabi 2017–18. Crop yield were estimated by weather based and crop simulation model. Percentage deviation of estimated yield by observed yield at flowering and grain filling stage was −5.1 and 2.0 by weather based model, 4.3 and 2.1 by InfoCrop model, 10.2 and 9.0 by DSSAT model during Rabi 2016–17 and 5.3 and 5.9 by weather based model, 2.3 and 2.2 by InfoCrop model, −10.8 and −9.6 by DSSAT model during Rabi 2017–18 respectively. Among the three models opted for estimating the yield at flowering and grain filling stage, InfoCrop model gave better results followed by weather based and DSSAT model. Therefore, this model can be used for multi stage wheat crop yield estimation at district as well as regional level.

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Abstract. Crop yield estimation before harvest is required for marketing, pricing, storage, import, export etc. Productivity of cropping systems under various weather, management and policy scenarios can be predicted successfully by simulation models. Due to increase in input cost of agricultural operation, agriculture produces become costly. Therefore, crop yield estimation in the agriculture becomes essential. Weather variability causes the losses in the yield. Therefore, model based on weather parameters, soil parameter and crop parameters can provide reliable crop yield estimation in advance. For estimating the multi stage wheat crop yield, experiments were conducted at research farm of IARI, New Delhi during Rabi 2016–17 and Rabi 2017–18. Crop yield were estimated by weather based and crop simulation model. Percentage deviation of estimated yield by observed yield at flowering and grain filling stage was −5.1 and 2.0 by weather based model, 4.3 and 2.1 by InfoCrop model, 10.2 and 9.0 by DSSAT model during Rabi 2016–17 and 5.3 and 5.9 by weather based model, 2.3 and 2.2 by InfoCrop model, −10.8 and −9.6 by DSSAT model during Rabi 2017–18 respectively. Among the three models opted for estimating the yield at flowering and grain filling stage, InfoCrop model gave better results followed by weather based and DSSAT model. Therefore, this model can be used for multi stage wheat crop yield estimation at district as well as regional level.

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Available abstract

Abstract. Crop yield estimation before harvest is required for marketing, pricing, storage, import, export etc. Productivity of cropping systems under various weather, management and policy scenarios can be predicted successfully by simulation models. Due to increase in input cost of agricultural operation, agriculture produces become costly. Therefore, crop yield estimation in the agriculture becomes essential. Weather variability causes the losses in the yield. Therefore, model based on weather parameters, soil parameter and crop parameters can provide reliable crop yield estimation in advance. For estimating the multi stage wheat crop yield, experiments were conducted at research farm of IARI, New Delhi during Rabi 2016–17 and Rabi 2017–18. Crop yield were estimated by weather based and crop simulation model. Percentage deviation of estimated yield by observed yield at flowering and grain filling stage was −5.1 and 2.0 by weather based model, 4.3 and 2.1 by InfoCrop model, 10.2 and 9.0 by DSSAT model during Rabi 2016–17 and 5.3 and 5.9 by weather based model, 2.3 and 2.2 by InfoCrop model, −10.8 and −9.6 by DSSAT model during Rabi 2017–18 respectively. Among the three models opted for estimating the yield at flowering and grain filling stage, InfoCrop model gave better results followed by weather based and DSSAT model. Therefore, this model can be used for multi stage wheat crop yield estimation at district as well as regional level.

Key concepts: DSSAT, Yield (engineering), Crop simulation model, Crop yield, Agriculture, Cropping, Crop, Cropping system

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