Optimizing irigation schedule for wheat (Triticun aestivıum L) through field and simulation studies
| dc.contributor.advisor | Brar, AS | |
| dc.contributor.author | Sukhpreet Singh | |
| dc.date.accessioned | 2024-01-03T10:33:28Z | |
| dc.date.available | 2024-01-03T10:33:28Z | |
| dc.date.issued | 2021 | |
| dc.description.abstract | The present study "Optimizing irrigation schedule for wheat (Triticum aestivum L.y" through field and simulation studies" was carried out at Punjab Agricultural University, Ludhiana and Krishi Vigyan Kendra, Ropar during 2017-18 and 2018-19. Experiment I was conducted in split plot design, keeping factorial combinations of three sowing dates 2s" October (D), 10" November (D,) and 25" November (D)}and two cultivars {Unnat PBW 550 (V) and PBW 725 (V)} in main plots and four irrigation schedules {irigation at CuluAo (L.) 50 (1) and PAU recommended irrigation schedule (L4)} in sub plots. The results revealed that J0d decreased by 8.2 and 3.8% from D, to D, and 18.0 and 11.5% from D, to D, during 2017-18 and 110 respectively. The correspondıng figures for Ropar were 6.1 and 1.3% and 17.6 and 12.5% during 017.18 and 2018-19, respectively. The variety PBW 725 produced 9.5 and 11.6% higher yield as compared Unnat PBW 550 during 2017-18 and 2018-19, respectively at Ludhiana and 9.8 and 11.5% at Ropar. respectively. However, the results showed the variety Unnat PBW 550 performed better under late sown conditions as compared to PBW 725. The highest grain yield was obtained in I, which was significantly better than all other depletion-based irigation treatments but statistically at par with L4. The grain yield in I, was 31.4 and 28.5% higher as compared to I; during 2017-18 and 2018-19, respectively whereas at Ropar it was 314 and 43.1%, respectively. The grain yield and ETc in I, and LĻ were at par, but crop and apparent water productivity was significantly higher in I, as compared to CP. The DSSAT-CERES-Wheat model performed well [as revealed by high correlation coefficient (r), low root mean square error (RMSE) and low mean absolute percentage error (MAPE)] in simulating the days to anthesis (r=0.95 and 0.92; RMSE-4.27 and 4.99 days; MAPE-3.60 and 4.20%), maturity (r-0.96 and 0.94; RMSE-6.02 and 7.51 days; MAPE=3.41 and 4.35%), leaf area index (r=0.92 and 0.84; RMSE-0.16 and 0.15; MAPE=4.58 and 4.50%), grain yield (r=0.94 and 0.96; RMSE=133.3 and 214.6 kg ha'; MAPE=2.66 and 4.87%), biological yield (r-0.92 and 0.93, RMSE=130.6 and 397.1 kg ha': MAPE=1.12 and 2.87%), ETc (r-0.95 and 0.91; RMSE=114 and 10.2 mm; MAPE-3.31 and 3.18%) and CWP (-0.88 and 0.85, RMSE-0.07 and 0.09 kg ha'; MAPE-4.50 and 5.60%) during 2017-18 and 2018-19, respectively. Experiment II was also conducted in split plot design, keeping three irigation timings {three irrigations at crown root initiation, booting and milking (CBM); four irigations at crown root initiation, tillering, flowering and milking (CTFM) and five irrigations at crown root initiation, tillering, booting, flowering and dough (CTBFD)} in main plots and factorial combinations of 3 depths of first ITigation {65 mm (F): 75 mm (F.) and 85 mm (F)} and 3 depths of subsequent irigations {55 mm (S): 65 mm (S.) and 75 mm (S)} in sub plots. There was significant increase in grain yield, apparent and crop water productivity when number of irigations were increased from 3 in CBM to 5 in CTBFD. The grain yield increased significantly when depth of first irrigation was increased from 65 to 75 mm whereas further increase Tesulted in numeric increase only. Similarly, the effect of depth of subsequent irigations was significant only p tO 0 mm. The grain yield was maximum in the treatment CTBFD with 75 mm depth of first irrigation but S Was Statistically at par with the treatment CTBFD with 55 and 65 mm irrigation depth of first irrigation. e DSSAT-CERES-Wheat model performed well in simulating the days to anthesis (RMSE-1.19 and 1.94 days; 1MAPE-0.94 and 1.799%), maturity (RMSE=1.59 and 1.86 days: MAPE=0.90 and 1.02%), leaf area index na 0.86; RMSE-0.39 and 0.,13: MAPE=2.33 and 3.43%), grain yield (r=0.94 and 0.98; RMSE=160.6, Kg ha ; MAPE=3.43 and 3.51%), biological yield (r-0.93 and 0.95; RMSE494.0 and 362.7 kg ha PEF3.63 and 2.86%). ETc (r=0 94 and 0.96: RMSE=8.28 and 11.73 mm; MAPE-2.34 and 3.49%o) and TesU.04 and 0.79; RMSE-0.12 and 0.14 mm: MAPE=8.03 and 9.18%) during 2017-18 and 2018-19, respectively. The study finally concluded that simulation modelling along with field experimentation may help in determining , optimum sowing time of different cultivars and optimizing irigation water use in wheat. | |
| dc.identifier.citation | Sukhpreet Singh (2021). Optimizing irigation schedule for wheat (Triticun aestivıum L) through field and simulation studies (Unpublished Ph.D. Dissertation). Punjab Agricultural University, Ludhiana, Punjab, India. | |
| dc.identifier.uri | https://krishikosh.egranth.ac.in/handle/1/5810205422 | |
| dc.keywords | CERES-wheat | |
| dc.keywords | simulations | |
| dc.keywords | sowing date | |
| dc.keywords | depth of irigation | |
| dc.keywords | water use. yield | |
| dc.language.iso | English | |
| dc.pages | 231 | |
| dc.publisher | Punjab Agricultural University | |
| dc.research.problem | Optimizing irigation schedule for wheat (Triticun aestivıum L) through field and simulation studies | |
| dc.sub | Agronomy | |
| dc.theme | Optimizing irigation schedule for wheat (Triticun aestivıum L) through field and simulation studies | |
| dc.these.type | Ph.D | |
| dc.title | Optimizing irigation schedule for wheat (Triticun aestivıum L) through field and simulation studies | |
| dc.type | Thesis |