Decision support system for agro-technology transfer (DSSAT), OIL CROP-SUN Model was used to stimulate the phenology, growth, yield of different two sunflower hybrids. i.e. Hysun-33 and S-78 by applying different nitrogen levels. The effect of nitrogen (N) on growth and yield components of different sunflower ( Helianthus annuus L.) hybrids were evaluated under agro-climatic conditions of Sargodha, Pakistan during spring 2013. The experiment was laid out in a randomized complete block design with split plot arrangement having three replications, keeping cultivars in the main plots and nitrogen levels (0, 45, 90,135 and 180 kg/ha) in sub plots. OIL CROP-SUN Model showed that the model was able to simulate the growth and yield of sunflower with an average of 10.44 error% between observed and simulate achene yield (AY). The result of simulation indicates that nitrogen rate of 180 kg/ha produced highest achene yield in S-78 hybrid as compared to other treatments and Hysun-33 cultivar.
Among the crops, oil crops are playing an important role as one of the largest sources of energy. These are being cultivated mainly due to the use of food and non-food oils. Pakistan is facing a serious shortage of edible oil because the domestic production is not sufficient to meet our total demand. Thus country is constrained to import edible oil in large quantities involving huge expenditure in foreign exchange. A developing country like Pakistan cannot afford such a huge amount indeed. So it is imperative to enhance the domestic production to meet the increasing demand of edible oils. The area under of sunflower crop in 2012- 13 was 700 thousand acres with seed and oil production of 378 and 144 thousand tons, respectively [
The experiment was carried out at the Agronomic Research Area of, University of Sargodha (32˚05"N, 72˚67"E), Pakistan during the spring seasons of 2013. The soil is sandy clay loamy somewhat poorly drained with pH ranging from 7.9 - 7.33. The nitrogen level was 0.066 to 0.052 are shown in
Prior to planting. Seed bed preparation was prepared with chisel plough and 3 cultivation with the help of common cultivar. After the preparation of field make a ridges with help of plough. The experiment was set in a Split plot arrangement under RCBD having 3 replications. The crop sowing was done by dibbler method using seed rate of 5 kg/ha. The net plot size was 4.2 m × 6 m having row to row spacing 70 cm and plant to plant distance 20 cm. The treatments were included with two different type of Sunflower hybrids (Hysun-33, S-278) were kept in a main plots and five levels of chemical nitrogen fertilizer (urea) consisting of (0, 45, 90, 135 and 180 kg/ha) in sub plots. The sources of fertilizer are Nitrogen, Phosphorus and potassium were used in the form of urea, DAP and Potassium (k2so4).The Phosphorus and potash at the rate of 80 - 40 kg/ha with 1/3 of nitrogen were applied at the time of sowing in all the plots by broadcast method. Remaining 2/3 dozes of urea fertilizer was used in two splits, at first irrigation and flowering stage. All other agronomic practices such as hoeing, weeding, irrigation and plant protection measure were kept normal for whole the experiment.
Phonological events as well as growth and canopy development were noted at vegetative and reproductive phases of sunflower crop. The randomly 5 plants were selected by visual observations from each treated plots and tagged them for determine the number of days are need from anthesis to gained physical maturity. The first growth sampling was done after the fifteen days of sowing. Then each sample was taken every 10 days interval. The every fifteen days of interval
Characteristic | Soil sample depth | |||
---|---|---|---|---|
10 cm | 15 cm | 20 cm | Mean | |
Soil pH | 7.9 | 7.9 | 8.0 | 7.33 |
Organic Matter (%) | 1.32 | 1.32 | 1.04 | 1.22 |
Total Nitrogen (%) | 0.066 | 0.066 | 0.052 | 0.061 |
Available P (mg∙kg−1) | 4.6 | 7.5 | 10.2 | 7.43 |
Available K (mg∙kg−1) | 188 | 164 | 144 | 165.33 |
Texture | Sandy loam | Sandy loam | Sandy loam |
Month | Mean Temperature (˚C) | Total Rainfall (mm) | Mean Relative Humidity (%) |
---|---|---|---|
March April May Jun | 21 25.7 32.20 34.70 | 7.95 31 4.50 6.61 | 61.53 51 37.79 43.28 |
take 10 g sample of leaves from each treatments by using area meter (JVC Model TK-S310EG) for the measurement of leaf area and dry weights were recorded at each harvesting stage are explained by [
Calibration is a process of adjusting some model parameters to the local conditions. It is also necessary for genetic coefficients for new cultivars used in modeling study. The data obtained from experiments conducted during the years, 2013 was used as input file for calibration and evaluation of the crop-model under optimum growth conditions. The comparison of model simulated outcome with observed data assesses accuracy of the model [
Simulation performance was evaluated by calculating different statistic indices like root mean square error (RMSE), mean percentage difference (MPD), error% and index of agreement [
The
The OILCROP-SUN model was calibrated with experimental data collected during 2010 sunflower crop season. The cultivar coefficients of Hysun-33 and S-278 were estimated through trial and error and comparison of simulated and observed data. The final values for the two cultivar coefficients that determine vegetative and reproductive growth and development are presented in
A close agreement was noted between observed and simulated values for sunflower phenology. The model predicted the dates for days to anthesis with a difference of one and 2 days between observed and simulated dates for Hysun-33 and S-278 hybrids, respectively are shown in
Genotype | P1 ((˚C days) | P2 ( days) | P5 (˚C days) | G2 (Nr) | G3 (mg∙day−1) | O1 (%) |
---|---|---|---|---|---|---|
Hysun-33 S-78 | 320 260 | 3.55 0.80 | 732 712 | 1500 1500 | 2.40 2.40 | 65 65 |
Hybrids | Nitrogen Level (kg∙ha−1) | Observed | Predicted | aP-O | PD (%) |
---|---|---|---|---|---|
Hysun-33 | 0 kg∙ha−1 | 67 | 73 | 4 | 3.4 |
45 kg∙ha−1 | 68 | 73 | 2 | 1.7 | |
90 kg∙ha−1 | 69 | 73 | 1 | .8 | |
135 kg∙ha−1 | 70 | 73 | −1 | −.8 | |
180 kg∙ha−1 | 72 | 73 | −2 | −1.6 | |
S-78 | 0 kg∙ha−1 | 58 | 73 | 5 | 5 |
45 kg∙ha−1 | 58 | 57 | 5 | 5 | |
90 kg∙ha−1 | 59 | 57 | 4 | 3.9 | |
135 kg∙ha−1 | 60 | 57 | 2 | 1.9 | |
180 kg∙ha−1 | 61 | 57 | 0 | 0 | |
Mean | 0.77 | 0.83 | |||
RMSE | 1.65 |
aP-O = Predicted-Observed; RMSE = Root Mean Square Error.
was able to anthesis date well and calibration results described that value for root mean square error (RMSE) was observed (1.65), was same in both sunflower hybrid S-78 and Hysun-33.
The observed and simulated values of physiological maturity are shown in
The OILCROP-SUN model was able to simulate final number of grain per meter square total well and calibrate results described there was a small difference in total number of grain per meter square between observed (5887 m−2) and simulate (6977 m−2) values of Hysun-33 hybrid and also small difference was noted in hybrid S-78 in total number of grain per meter square between observed (6535 m−2) and simulate (6841 m−2) root mean square error (RMSE) was observed (1.60) results are shown in
The observed and simulated value of achene yield is shown in
Hybrids | Nitrogen Level(kg∙ha−1) | Observed | Predicted | aP-O | PD (%) |
---|---|---|---|---|---|
Hysun-33 | 0 kg∙ha−1 | 117 | 121 | 4 | 3.4 |
45 kg∙ha−1 | 119 | 121 | 2 | 1.7 | |
90 kg∙ha−1 | 120 | 121 | 1 | .8 | |
135 kg∙ha−1 | 122 | 121 | −1 | −.8 | |
180 kg∙ha−1 | 123 | 121 | −2 | −1.6 | |
S-78 | 0 kg∙ha−1 | 100 | 105 | 5 | 5 |
45 kg∙ha−1 | 100 | 105 | 5 | 5 | |
90 kg∙ha−1 | 101 | 105 | 4 | 3.9 | |
135 kg∙ha−1 | 103 | 105 | 2 | 1.9 | |
180 kg∙ha−1 | 105 | 105 | 0 | 0 | |
Mean | 2 | 1.9 | |||
RMSE | 1.69 |
aP-O = Predicted-Observed; RMSE = Root Mean Square Error.
Hybrids | Nitrogen Level (kg∙ha−1) | Observed | Predicted | aP-O | PD (%) |
---|---|---|---|---|---|
Hysun-33 | 0 kg∙ha−1 | 5877 | 4489 | −1388 | 23.6 |
45 kg∙ha−1 | 5887 | 6977 | 1090 | 18.5 | |
90 kg∙ha−1 | 6073 | 8556 | 2483 | 40.9 | |
135 kg∙ha−1 | 7622 | 9298 | 2576 | 38.3 | |
180 kg∙ha−1 | 7543 | 9890 | 2347 | 31.1 | |
S-78 | 0 kg∙ha−1 | 4867 | 4555 | −312 | −6.4 |
45 kg∙ha−1 | 6535 | 6841 | 306 | 4.8 | |
90 kg∙ha−1 | 7291 | 7944 | 658 | 9.0 | |
135 kg∙ha−1 | 8983 | 8464 | −512 | −5.8 | |
180 kg∙ha−1 | 9244 | 8768 | −476 | −5.4 | |
Mean | 676.5 | 14.9 | |||
RMSE | 1.60 |
aP-O = Predicted-Observed RMSE = Root Mean Square Error.
Hybrids | Nitrogen Level (kg∙ha−1) | Observed | Predicted | aP-O | PD (%) |
---|---|---|---|---|---|
Hysun-33 | 0 kg∙ha−1 | 2923 | 486 | −2437 | −83.4 |
45 kg∙ha−1 | 3078 | 1658 | −1420 | −46.1 | |
90 kg∙ha−1 | 3500 | 3315 | −185 | −5.2 | |
135 kg∙ha−1 | 3884 | 3944 | 60 | 1.5 | |
180 kg∙ha−1 | 3935 | 3915 | −20 | −0.5 | |
S-78 | 0 kg∙ha−1 | 3212 | 496 | −2716 | −84.6 |
45 kg∙ha−1 | 3406 | 2028 | −1378 | −40.4 | |
90 kg∙ha−1 | 3805 | 3314 | −491 | −12.9 | |
135 kg∙ha−1 | 4055 | 3671 | −384 | −9.5 | |
180 kg∙ha−1 | 4095 | 2932 | −1163 | −28.4 | |
Mean | −1013 | −30.9 | |||
RMSE | 191.81 |
aP-O = Predicted-Observed RMSE = Root Mean Square Error.
lated (3935 kg∙ha−1) and observed (3915 kg∙ha−1), value for achene yield was in hybrid Hyun-33 with nitrogen application 180 kg∙ha−1. In generally, all values are almost close to each other. However, maximum difference was in Hysun-33 without receiving of Nitrogen. The OILCROP-SUN model was also calibrate for hybrid S-78 and results showed the smallest difference between simulated (3671 kg∙ha−1) and observed (4055 kg∙ha−1), value for achene yield with nitrogen application 135 kg∙ha−1. In general, all values are almost close to each other. However, maximum difference was in S-78 hybrid in control treatment, where model over estimated similar approaches were explained by [
The OILCROP-SUN model simulated final total dry matter well and calibrated results described there was a small difference in total dry matter (TDM) between observed (11,586 kg∙ha−1) and simulate (10,970 kg∙ha−1) values for Sunflower 33and also minimum difference was noted between observed (9496 kg∙ha−1) and simulated (8623 kg∙ha−1) values of hybrid S-78. The OILCROP-SUN model also simulated total dry matter well and the calibration results described that maximum value for root mean error (RMSE) was observed 735 are shown in
The OILCROP-SUN model was able to simulate leaf area index well and calibration results described there was a small difference between observed and simulate value (0.19) of leaf area index in Hysun-33 with treatment level of (135 kg N ha−1). However, highest (1.6) difference was in control treatment where model over estimated. In general, model over estimated the value of LAI. The OILCROP-SUN model was able to simulated leaf area index well and calibration results described there was a small difference between observed and simulated value (1.26) of leaf area index in S-78 with application level of (135 kg N ha−1). However, highest (2.18) difference was in control treatment where model over estimated. In general, model over estimated the value of LAI as shown in
Hybrids | Nitrogen Level (kg∙ha−1) | Observed | Predicted | aP-O | PD (%) |
---|---|---|---|---|---|
Hysun-33 | 0 kg∙ha−1 | 7771 | 1212 | −6559 | −84.4 |
45 kg∙ha−1 | 8529 | 5097 | −3432 | −40.2 | |
90 kg∙ha−1 | 9725 | 8155 | −1570 | −16.1 | |
135 kg∙ha−1 | 11,123 | 9734 | −1389 | −124.8 | |
180 kg∙ha−1 | 11,586 | 10970 | −616 | −53.1 | |
S-78 | 0 kg∙ha−1 | 7518 | 1128 | −6390 | −85 |
45 kg∙ha−1 | 7676 | 5004 | −2672 | −34.9 | |
90 kg∙ha−1 | 8555 | 7492 | −1063 | −12.4 | |
135 kg∙ha−1 | 9496 | 8623 | −873 | −9.0 | |
180 kg∙ha−1 | 9722 | 8450 | −1272 | −13.0 | |
Mean | −2583.6 | −47.29 | |||
RMSE | 735 |
aP-O = Predicted-Observed, RMSE = Root Mean Square Error.
Crop modeling is becoming a valuable tool to understand and mimic climatic constraints and yield gaps. The outcomes of the study clearly depicted that DSSAT model is predicted crop growth and yield parameters of sunflower crop. This study also showed the OIL-CROP-SUN model served as a tool for determining the best nitrogen levels for growing sunflower under irrigated conditions in semi-arid environment in Pakistan. This study illustrates the potential for using crop simulations models as information technology for determining suitable management strategies for sunflower production in Sargodha, Punjab, Pakistan. Therefore, we can conclude that the OILCROP-SUN model could potentially assist resource-poor farmers in Pakistan and provide them with alternate management options.
Ahmad, M.I., Ali, A., Khan, A., Jamro, S.A., Sher, A., Rahman, S. and Rashid, A. (2017) OILCROP- SUN Model for Nitrogen Management of Diverse Sunflower (Helianthus annus L.) Hy- brids Production under Agro-Climatic Con- ditions of Sargodha, Pakistan. American Journal of Plant Sciences, 8, 412-427. https://doi.org/10.4236/ajps.2017.83028