TY - JOUR
T1 - Modeling the water and nitrogen productivity of sunflower using OILCROP-SUN model in Pakistan
AU - Awais, Muhammad
AU - Wajid, Aftab
AU - Nasim, Wajid
AU - Ahmad, Ashfaq
AU - Salee, Muhammad Farrukh
AU - Raza, Muhammad Aown Sammar
AU - Bashir, Muhammad Usman
AU - Rahman, Muhammad Habib ur
AU - Saeed, Umer
AU - Hussain, Jamshad
AU - Arshad, Muhammad Naveed
AU - Hoogenboom, Gerrit
PY - 2017/4/1
Y1 - 2017/4/1
N2 - Water and nitrogen (N) limitations in soil usually restrict plant growth hence reducing water and nitrogen productivity. Precise irrigation application is vital in water scarce areas of the world, such as Pakistan. Water and N are generally the most important factors in high yielding of crops. This interaction between irrigation levels and N can be analyzed through field experiments in concert with crop simulation models and decision support systems. Recently the use of crop growth models in crop husbandry has become more common to provide the decision support for farmers. The proposed study was conducted at Agronomic Research Area, University of Agriculture Faisalabad, Pakistan during the years 2012 and 2013 to evaluate OILCROP-SUN model under decision support system for agro-technology transfer (DSSAT) for simulating growth, development and achene yield of sunflower hybrid Hysun-33. The experiment was laid out using split plot design with four irrigation levels (control, 45, 60 and 75 mm potential soil moisture deficit) in main plots and three N rates (90, 120 and 150 kg ha−1) in sub plots. The model was first calibrated with control irrigation plus 150 kg N ha−1 treatment (I1N3), then evaluated (2012) and validated (2013) by utilizing experimental data. The evaluation and validation exhibited that the model simulated anthesis date, maturity date, maximum leaf area index (LAI), total dry matter (TDM), achene yield and oil contents very well with an error of 0–6.15%, 0–3.96%, −25.14 to 6%, −0.37 to 17.75%, −4.58 to 17.12% and −15.04 to 12.15%, respectively. Similarly, root mean square error (RMSE) values for soil water and leaf N contents were ranged from 0.03 to 0.05 cm3 cm−3 and 0.16% to 0.71%, respectively. While RMSE for crop evapotranspiration (ET) was 29.87 mm in 2012 and 32.56 mm in 2013. The highest achene yield and oil contents were achieved with the control irrigation in combination of 150 kg N ha−1 application. However saving of water (110 mm in 2012 and 120 mm in 2013) with 45 mm potential soil moisture deficit (PSMD) treatment (without significant reduction in sunflower productivity) recognized it as most suitable irrigation scheduling technique under water scarce areas of the world. The results disclosed that OILCROP-SUN model can be efficaciously used for simulation of spring sown sunflower under semi-arid conditions of Pakistan
AB - Water and nitrogen (N) limitations in soil usually restrict plant growth hence reducing water and nitrogen productivity. Precise irrigation application is vital in water scarce areas of the world, such as Pakistan. Water and N are generally the most important factors in high yielding of crops. This interaction between irrigation levels and N can be analyzed through field experiments in concert with crop simulation models and decision support systems. Recently the use of crop growth models in crop husbandry has become more common to provide the decision support for farmers. The proposed study was conducted at Agronomic Research Area, University of Agriculture Faisalabad, Pakistan during the years 2012 and 2013 to evaluate OILCROP-SUN model under decision support system for agro-technology transfer (DSSAT) for simulating growth, development and achene yield of sunflower hybrid Hysun-33. The experiment was laid out using split plot design with four irrigation levels (control, 45, 60 and 75 mm potential soil moisture deficit) in main plots and three N rates (90, 120 and 150 kg ha−1) in sub plots. The model was first calibrated with control irrigation plus 150 kg N ha−1 treatment (I1N3), then evaluated (2012) and validated (2013) by utilizing experimental data. The evaluation and validation exhibited that the model simulated anthesis date, maturity date, maximum leaf area index (LAI), total dry matter (TDM), achene yield and oil contents very well with an error of 0–6.15%, 0–3.96%, −25.14 to 6%, −0.37 to 17.75%, −4.58 to 17.12% and −15.04 to 12.15%, respectively. Similarly, root mean square error (RMSE) values for soil water and leaf N contents were ranged from 0.03 to 0.05 cm3 cm−3 and 0.16% to 0.71%, respectively. While RMSE for crop evapotranspiration (ET) was 29.87 mm in 2012 and 32.56 mm in 2013. The highest achene yield and oil contents were achieved with the control irrigation in combination of 150 kg N ha−1 application. However saving of water (110 mm in 2012 and 120 mm in 2013) with 45 mm potential soil moisture deficit (PSMD) treatment (without significant reduction in sunflower productivity) recognized it as most suitable irrigation scheduling technique under water scarce areas of the world. The results disclosed that OILCROP-SUN model can be efficaciously used for simulation of spring sown sunflower under semi-arid conditions of Pakistan
KW - Helianthus anuus L.
KW - potential soil moisture deficit
KW - phenology
KW - irrigation
KW - achene yield
KW - total dry matter
U2 - 10.1016/j.fcr.2017.01.013
DO - 10.1016/j.fcr.2017.01.013
M3 - Article
SN - 0378-4290
VL - 205
SP - 67
EP - 77
JO - Field Crops Research
JF - Field Crops Research
IS - 66-67
ER -