Analysis of a precision agriculture approach to cotton production

The hope of precision agriculture is that through more precise timing and usage of seed, agricultural chemicals and irrigation water that higher economic yields can occur while enhancing the economic production of field crops and protecting the environment. The analyses performed in this manuscript demonstrate proof of concept of how precision agriculture coupled with crop simulation models and geographic information systems technology can be used in the cotton production system in the Mid South to optimize yields while minimizing water and nitrogen inputs. The Hood Farm Levingston Field, located in Bolivar County, Mississippi, next to the Mississippi River, was chosen as the test sight to obtain a one hectare soil physical property grid over the entire 201 ha field. The 1997 yield was used as a comparison for the analysis. Actual cultural practices for 1997 were used as input to the model. After the 201 simulations were made using the expert system to optimize for water and nitrogen on a one hectare basis, the model predicted that an increase of 322 kg/ha could be obtained by using only an average increase of 2.6 cm of water/ha and an average decrease of 35 kg N/ha.

[1]  James W. Jones,et al.  Modeling Soybean Growth for Crop Management , 1983 .

[2]  John R. Williams,et al.  The EPIC crop growth model , 1989 .

[3]  J. M. McKinion,et al.  Crop Modeling and Applications: A Cotton Example , 1997 .

[4]  J. L. Steiner,et al.  Evaluation of the EPIC Simulation Model Using a Dryland Wheat‐Sorghum‐Fallow Crop Rotation1 , 1987 .

[5]  R. Bruce Curry,et al.  Agricultural Systems modeting and Simulation , 1997 .

[6]  Angela Lee,et al.  Perspectives on … Environmental Systems Research Institute, Inc , 1997 .

[7]  Douglas L. Karlen,et al.  Spatial scale requirements for precision farming: a case study in the southeastern USA , 1998 .

[8]  Ewald Schnug,et al.  Sampling and nutrient recommendations ‐ the future , 1998 .

[9]  F. D. Whisler,et al.  Application of the GOSSYM/COMAX system to cotton crop management , 1989 .

[10]  F. D. Whisler,et al.  Simulation in Crop Management: GOSSYM/COMAX , 2018, Agricultural Systems modeting and Simulation.

[11]  J. M. McKinion,et al.  Expert systems for agriculture , 1985 .

[12]  Alfred Stein,et al.  Model-based decision support in agriculture. , 1997 .

[13]  E. Sadler,et al.  Center pivot irrigation system for site-specific water and nutrient management , 1994 .

[14]  Graeme L. Hammer,et al.  APSIM: a novel software system for model development, model testing and simulation in agricultural systems research , 1996 .

[15]  Masahiro Kikusawa,et al.  Crop models and precision agriculture , 1997 .

[16]  J. R. Kiniry,et al.  CERES-Maize: a simulation model of maize growth and development , 1986 .