Application of CSM-CROPGRO-Cotton model for cultivars and optimum planting dates: Evaluation in changing semi-arid climate

被引:49
|
作者
Rahman, Muhammad Habib Ur [1 ,2 ]
Ahmad, Ashfaq [3 ,4 ]
Wajid, Aftab [3 ]
Hussain, Manzoor [5 ]
Rasul, Fand [2 ,3 ]
Ishaque, Wajid [5 ]
Islam, Md Aminul [2 ,6 ]
Shelia, Vakhtang [2 ,7 ]
Awais, Muhammad [8 ]
Ullah, Asmat [9 ]
Wahid, Abdul [10 ]
Sultana, Syeda Refat [11 ]
Saud, Shah [12 ]
Khan, Shahbaz [13 ]
Fahad, Shah [13 ,14 ]
Hussai, Manzoor [15 ]
Hussain, Saddam [13 ,16 ]
Nasim, Wajid [11 ,17 ,18 ]
机构
[1] Muhammad Nawaz Shareef Univ Agr, Dept Agron, Multan, Pakistan
[2] Washington State Univ, AgWeatherNet, Prosser, WA USA
[3] Univ Agr Faisalabad, Dept Agron, Agroclimatol Lab, Faisalabad, Pakistan
[4] Univ Agr Faisalabad, USPCAS AFS, Program Chair Climate Change, Faisalabad, Pakistan
[5] NIAB, Faisalabad, Pakistan
[6] Dept Agr Extens, Dhaka, Bangladesh
[7] Univ Florida, ISFS, Agr & Biol Engn Dept, Gainesville, FL 32611 USA
[8] Islamia Univ Bahwalpur, Univ Coll Agr & Environm Sci, Dept Agron, Bahawalpur, Pakistan
[9] AARI, Faisalabad, Pakistan
[10] Bahauddin Zakariya Univ, Dept Environm Sci, Multan, Pakistan
[11] COMSATS Inst Informat Technol CIIT, Dept Environm Sci, Vehari, Pakistan
[12] Northeast Agr Univ Harbin, Coll Hort, Harbin 150030, Heilongjiang, Peoples R China
[13] Huazhong Agr Univ, Coll Plant Sci & Technol, Wuhan, Hubei, Peoples R China
[14] Abdul Wali Khan Univ Mardan, Dept Agr, Khyber Pakhtunkhwa, Pakistan
[15] Nucl Inst Agr & Biol, Plant Breeding & Genet Div, Faisalabad, Pakistan
[16] Univ Agr Faisalabad, Dept Agron, Faisalabad, Pakistan
[17] IAMM, CIHEAM, F-34090 Montpellier, France
[18] CSIRO Sustainable Agr, Natl Res Flagship, Toowoomba, Qld 4350, Australia
关键词
DSSAT; Temporal variation; Calibration; Evaluation; Application; Pakistan; CERES-MAIZE MODEL; GLOBAL SENSITIVITY-ANALYSIS; OILCROP-SUN MODEL; SUNFLOWER HYBRIDS; SIMULATION-MODELS; HIGH-TEMPERATURE; HEAT TOLERANCE; GROWTH; NITROGEN; YIELD;
D O I
10.1016/j.fcr.2017.07.007
中图分类号
S3 [农学(农艺学)];
学科分类号
0901 ;
摘要
Simulation models are widely used for making decision support especially under sub-optimal climatic conditions for yield improvement. The impact of uncertain weather conditions on cotton production can be explored with the aid of such models. Cotton, being the queen of fibers, enjoys itself a predominant position amongst all other cash crops and has the potential to narrow the gap between production and consumption of fiber and edible oil. The goal of the study was to evaluate the performance of Cropping System Model CROPGRO-Cotton for examining temporal variation in cultivars and to determine the potential impact of planting dates. The model was calibrated using a diverse range of field observation for phenology, growth and seed cotton yield (SCY) and its components of 20-April planting date, genetic coefficients were estimated using Generalized Likelihood Uncertainty Estimation (GLUE) and sensitivity analysis sub modules in CSM-DSSAT. Calibrated and evaluated results were reasonably good for phenology, growth, boll weight, SCY and yield attributes with good statistics. Simulation and observed data revealed the decreasing trend with delayed planting for all cultivars. Phenological phases were predicted well with high d-index ( > 0.94 and > 0.85), and the dynamics of time series for LAI and biomass were predicted also well (d > 0.96 and > 0.98), respectively during model evaluation for all planting dates and cultivars. Seed cotton yield was simulated with lower RMSE (137-382) at final picking, while dynamics of time series for SCY were predicted reasonably well with high values of d-index (0.95-0.99) for all cultivars during model evaluation. Planting date analyses of the years (1980-2013) agreed with observed SCY trend, showed decrease of 27% for delayed planting from 20-April to 21-June while first too early planting (10-March) had also faced 8% reduction for all cultivars. Cultivars [MNH-886, NIAB-9811 (NIAB-Kiran) and NIAB-112] outperformed with higher SCY predominantly due to longer appropriate growing season by utilizing optimal weather conditions, attained optimum growth at all key phenological phases. Cultivar NIAB-112 performed well being a short duration and attained high SCY for late planting (1-June) as well during the growing years. Cotton cultivars planting during 1-April-10-May can be suggested for the farmer's field to avoid weather stress and to improve utilization of resources for sustainable cotton production in the region. Result demonstrated the model potential for decision support for cotton management practices in the region, including identifying optimum planting dates for cotton production.
引用
收藏
页码:139 / 152
页数:14
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