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InfoCrop-Cotton Simulation Model - Its Application in Land Quality Assessment for Cotton Cultivation


Affiliations
1 Central Institute for Cotton Research, Nagpur 440 010, India
2 Regional Centre, National Bureau of Soil Survey and Land Use Planning, Nagpur 440 033, India
3 Indian Agricultural Research Institute, New Delhi 110 012, India
4 International Crops Research Institute for the Semi-Arid Tropics, Patancheru 502 324, India
5 Regional Centre, National Bureau of Soil Survey and Land Use Planning, New Delhi 110 012, India
6 Regional Centre, National Bureau of Soil Survey and Land Use Planning, Bangalore 560 024, India
7 Regional Centre, National Bureau of Soil Survey and Land Use Planning, Kolkata 700 091, India
8 National Bureau of Agriculturally Important Microorganisms, Mau 275 103, India
9 Regional Centre, National Bureau of Soil Survey and Land Use Planning, Udaipur 313 001, India
10 Regional Centre, National Bureau of Soil Survey and Land Use Planning, Jorhat 785 004, India
11 Directorate of Water Management, Bhubaneswar 751 023, India
12 Regional Centre, National Bureau of Soil Survey and Land Use Planning, Nagpur 440 033
13 Regional Centre, National Bureau of Soil Survey and Land Use Planning, Kolkata 700 091
 

Crop simulation models have emerged as powerful tools for estimating yield gaps, forecasting production of agricultural crops and analysing the impact of climate change. In this study, the genetic coefficients for Bt hybrids established from field experiments were used in the InfoCrop-cotton model, which was calibrated and validated earlier to simulate the cotton production under different agro-climatic conditions. The model simulated results for Bt hybrids were satisfactory with an R2 value of 0.55 (n = 22), d value of 0.85 and a ischolar_main mean square error of 277 kg ha-1, which was 11.2% of the mean observed. Relative yield index (RYI) defined as the ratio between simulated rainfed (water-limited) yield to potential yield, was identified as a robust land quality index for rainfed cotton. RYI was derived for 16 representative benchmark (BM) locations of the black soil region from long-term simulation results of InfoCrop-cotton model (based on 11-40 years of weather data). The model could satisfactorily capture subtle differences in soil variables and weather patterns prevalent in the BM locations spread over 16 agro-ecological sub-regions (AESRs) resulting in a wide range of mean simulated rainfed cotton yields (482-4393 kg ha-1). The BM soils were ranked for their suitability for cotton cultivation based on RYI. The RYI of black soils (vertisols) ranged from 0.07 in Nimone to 0.80 in Panjari representing AESR (6.1) and AESR (10.2) respectively, suggesting that Panjri soils are better suited for rainfed cotton.

Keywords

Bt Cotton, Land Quality, Relative Yield Index, Simulation Model.
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  • InfoCrop-Cotton Simulation Model - Its Application in Land Quality Assessment for Cotton Cultivation

Abstract Views: 341  |  PDF Views: 149

Authors

M. V. Venugopalan
Central Institute for Cotton Research, Nagpur 440 010, India
P. Tiwary
Regional Centre, National Bureau of Soil Survey and Land Use Planning, Nagpur 440 033, India
S. K. Ray
Regional Centre, National Bureau of Soil Survey and Land Use Planning, Nagpur 440 033, India
S. Chatterji
Regional Centre, National Bureau of Soil Survey and Land Use Planning, Nagpur 440 033, India
K. Velmourougane
Central Institute for Cotton Research, Nagpur 440 010, India
T. Bhattacharyya
Regional Centre, National Bureau of Soil Survey and Land Use Planning, Nagpur 440 033, India
K. K. Bandhopadhyay
Indian Agricultural Research Institute, New Delhi 110 012, India
D. Sarkar
Regional Centre, National Bureau of Soil Survey and Land Use Planning, Nagpur 440 033, India
P. Chandran
Regional Centre, National Bureau of Soil Survey and Land Use Planning, Nagpur 440 033, India
D. K. Pal
International Crops Research Institute for the Semi-Arid Tropics, Patancheru 502 324, India
D. K. Mandal
Regional Centre, National Bureau of Soil Survey and Land Use Planning, Nagpur 440 033, India
J. Prasad
Regional Centre, National Bureau of Soil Survey and Land Use Planning, Nagpur 440 033, India
G. S. Sidhu
Regional Centre, National Bureau of Soil Survey and Land Use Planning, New Delhi 110 012, India
K. M. Nair
Regional Centre, National Bureau of Soil Survey and Land Use Planning, Bangalore 560 024, India
A. K. Sahoo
Regional Centre, National Bureau of Soil Survey and Land Use Planning, Kolkata 700 091, India
K. S. Anil Kumar
Regional Centre, National Bureau of Soil Survey and Land Use Planning, Bangalore 560 024, India
A. Srivastava
National Bureau of Agriculturally Important Microorganisms, Mau 275 103, India
T. H. Das
Regional Centre, National Bureau of Soil Survey and Land Use Planning, Kolkata 700 091, India
R. S. Singh
Regional Centre, National Bureau of Soil Survey and Land Use Planning, Udaipur 313 001, India
C. Mandal
Regional Centre, National Bureau of Soil Survey and Land Use Planning, Nagpur 440 033, India
R. Srivastava
Regional Centre, National Bureau of Soil Survey and Land Use Planning, Nagpur 440 033, India
T. K. Sen
Regional Centre, National Bureau of Soil Survey and Land Use Planning, Nagpur 440 033, India
N. G. Patil
Regional Centre, National Bureau of Soil Survey and Land Use Planning, Nagpur 440 033, India
G. P. Obireddy
Regional Centre, National Bureau of Soil Survey and Land Use Planning, Nagpur 440 033, India
S. K. Mahapatra
Regional Centre, National Bureau of Soil Survey and Land Use Planning, New Delhi 110 012, India
K. Das
Regional Centre, National Bureau of Soil Survey and Land Use Planning, Kolkata 700 091, India
S. K. Singh
Regional Centre, National Bureau of Soil Survey and Land Use Planning, Kolkata 700 091, India
S. K. Reza
Regional Centre, National Bureau of Soil Survey and Land Use Planning, Jorhat 785 004, India
D. Dutta
Regional Centre, National Bureau of Soil Survey and Land Use Planning, Kolkata 700 091, India
S. Srinivas
Regional Centre, National Bureau of Soil Survey and Land Use Planning, Bangalore 560 024, India
K. Karthikeyan
Regional Centre, National Bureau of Soil Survey and Land Use Planning, Nagpur 440 033, India
Mausumi Raychaudhuri
Directorate of Water Management, Bhubaneswar 751 023, India
D. K. Kundu
Directorate of Water Management, Bhubaneswar 751 023, India
K. K. Mandal
Directorate of Water Management, Bhubaneswar 751 023, India
G. Kar
Directorate of Water Management, Bhubaneswar 751 023, India
S. L. Durge
Regional Centre, National Bureau of Soil Survey and Land Use Planning, Nagpur 440 033, India
G. K. Kamble
Regional Centre, National Bureau of Soil Survey and Land Use Planning, Nagpur 440 033, India
M. S. Gaikwad
Regional Centre, National Bureau of Soil Survey and Land Use Planning, Nagpur 440 033, India
A. M. Nimkar
Regional Centre, National Bureau of Soil Survey and Land Use Planning, Nagpur 440 033, India
S. V. Bobade
Regional Centre, National Bureau of Soil Survey and Land Use Planning, Nagpur 440 033, India
S. G. Anantwar
Regional Centre, National Bureau of Soil Survey and Land Use Planning, Nagpur 440 033, India
S. Patil
Regional Centre, National Bureau of Soil Survey and Land Use Planning, Nagpur 440 033
M. S. Gaikwad
Regional Centre, National Bureau of Soil Survey and Land Use Planning, Nagpur 440 033, India
V. T. Sahu
Regional Centre, National Bureau of Soil Survey and Land Use Planning, Nagpur 440 033, India
H. Bhondwe
Regional Centre, National Bureau of Soil Survey and Land Use Planning, Nagpur 440 033, India
S. S. Dohtre
Regional Centre, National Bureau of Soil Survey and Land Use Planning, Nagpur 440 033, India
S. Gharami
Regional Centre, National Bureau of Soil Survey and Land Use Planning, Nagpur 440 033, India
S. G. Khapekar
Regional Centre, National Bureau of Soil Survey and Land Use Planning, Nagpur 440 033, India
A. Koyal
Regional Centre, National Bureau of Soil Survey and Land Use Planning, Bangalore 560 024, India
Sujatha
Regional Centre, National Bureau of Soil Survey and Land Use Planning, Bangalore 560 024, India
B. M. N. Reddy
Regional Centre, National Bureau of Soil Survey and Land Use Planning, Bangalore 560 024, India
P. Sreekumar
Regional Centre, National Bureau of Soil Survey and Land Use Planning, Bangalore 560 024, India
D. P. Dutta
Regional Centre, National Bureau of Soil Survey and Land Use Planning, Jorhat 785 004, India
L. Gogoi
Regional Centre, National Bureau of Soil Survey and Land Use Planning, Jorhat 785 004, India
V. N. Parhad
Regional Centre, National Bureau of Soil Survey and Land Use Planning, Nagpur 440 033, India
A. S. Halder
Regional Centre, National Bureau of Soil Survey and Land Use Planning, Kolkata 700 091
R. Basu
Regional Centre, National Bureau of Soil Survey and Land Use Planning, Kolkata 700 091, India
R. Singh
Regional Centre, National Bureau of Soil Survey and Land Use Planning, Udaipur 313 001, India
B. L. Jat
Regional Centre, National Bureau of Soil Survey and Land Use Planning, Udaipur 313 001, India
D. L. Oad
Regional Centre, National Bureau of Soil Survey and Land Use Planning, Udaipur 313 001, India
N. R. Ola
Regional Centre, National Bureau of Soil Survey and Land Use Planning, Udaipur 313 001, India
A. Sahu
Central Institute for Cotton Research, Nagpur 440 010, India
K. Wadhai
Regional Centre, National Bureau of Soil Survey and Land Use Planning, Nagpur 440 033, India
M. Lokhande
Regional Centre, National Bureau of Soil Survey and Land Use Planning, Nagpur 440 033, India
V. T. Dongare
Regional Centre, National Bureau of Soil Survey and Land Use Planning, Nagpur 440 033, India
A. Hukare
Regional Centre, National Bureau of Soil Survey and Land Use Planning, Nagpur 440 033, India
N. Bansod
Regional Centre, National Bureau of Soil Survey and Land Use Planning, Nagpur 440 033, India
A. Kolhe
Regional Centre, National Bureau of Soil Survey and Land Use Planning, Nagpur 440 033, India
J. Khuspure
Regional Centre, National Bureau of Soil Survey and Land Use Planning, Nagpur 440 033, India
H. Kuchankar
Regional Centre, National Bureau of Soil Survey and Land Use Planning, Nagpur 440 033, India
D. Balbuddhe
Regional Centre, National Bureau of Soil Survey and Land Use Planning, Nagpur 440 033, India
S. Sheikh
Regional Centre, National Bureau of Soil Survey and Land Use Planning, Nagpur 440 033, India
B. P. Sunitha
Regional Centre, National Bureau of Soil Survey and Land Use Planning, Bangalore 560 024, India
B. Mohanty
Regional Centre, National Bureau of Soil Survey and Land Use Planning, New Delhi 110 012, India
D. Hazarika
Regional Centre, National Bureau of Soil Survey and Land Use Planning, Jorhat 785 004, India
S. Majumdar
Regional Centre, National Bureau of Soil Survey and Land Use Planning, Kolkata 700 091, India
R. S. Garhwal
Regional Centre, National Bureau of Soil Survey and Land Use Planning, Udaipur 313 001, India
S. Mahapatra
Directorate of Water Management, Bhubaneswar 751 023, India
S. Puspamitra
Directorate of Water Management, Bhubaneswar 751 023, India
A. Kumar
National Bureau of Agriculturally Important Microorganisms, Mau 275 103, India
N. Gautam
Regional Centre, National Bureau of Soil Survey and Land Use Planning, Nagpur 440 033, India
B. A. Telpande
Regional Centre, National Bureau of Soil Survey and Land Use Planning, Nagpur 440 033, India
A. M. Nimje
Regional Centre, National Bureau of Soil Survey and Land Use Planning, Nagpur 440 033, India
C. Likhar
Regional Centre, National Bureau of Soil Survey and Land Use Planning, Nagpur 440 033, India
S. Thakre
Regional Centre, National Bureau of Soil Survey and Land Use Planning, Nagpur 440 033, India

Abstract


Crop simulation models have emerged as powerful tools for estimating yield gaps, forecasting production of agricultural crops and analysing the impact of climate change. In this study, the genetic coefficients for Bt hybrids established from field experiments were used in the InfoCrop-cotton model, which was calibrated and validated earlier to simulate the cotton production under different agro-climatic conditions. The model simulated results for Bt hybrids were satisfactory with an R2 value of 0.55 (n = 22), d value of 0.85 and a ischolar_main mean square error of 277 kg ha-1, which was 11.2% of the mean observed. Relative yield index (RYI) defined as the ratio between simulated rainfed (water-limited) yield to potential yield, was identified as a robust land quality index for rainfed cotton. RYI was derived for 16 representative benchmark (BM) locations of the black soil region from long-term simulation results of InfoCrop-cotton model (based on 11-40 years of weather data). The model could satisfactorily capture subtle differences in soil variables and weather patterns prevalent in the BM locations spread over 16 agro-ecological sub-regions (AESRs) resulting in a wide range of mean simulated rainfed cotton yields (482-4393 kg ha-1). The BM soils were ranked for their suitability for cotton cultivation based on RYI. The RYI of black soils (vertisols) ranged from 0.07 in Nimone to 0.80 in Panjari representing AESR (6.1) and AESR (10.2) respectively, suggesting that Panjri soils are better suited for rainfed cotton.

Keywords


Bt Cotton, Land Quality, Relative Yield Index, Simulation Model.



DOI: https://doi.org/10.18520/cs%2Fv107%2Fi9%2F1512-1518