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2022 - 20232
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Subject: Agricultural Meteorology × Start date: 2022 × Type: Thesis × Thesis Type: Ph.D ×
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    Weather based forewarning of wheat diseases using artificial neural networks under Punjab conditions
    (Punjab Agricultural University, 2023) Shubham Anand; Sandhu, Sarabjot Kaur
    The field experiments were carried out at the Research Experiment Farm, Department of Climate Change and Agricultural Meteorology, Punjab Agricultural University, Ludhiana and Regional Research Station, Gurdaspur during rabi seasons of 2021-22 and 2022-23. The experiment was laid out in Split Plot Design with three wheat varieties viz., PBW 725, HD 2967 and HD 3086 sown on different dates (14th-15th October, 8th-9th November and 3rd-4th December) with two microclimate modification levels M1 (recommended irrigation) and M2 (additional water sprays) with four replications. The micrometeorological parameters viz., photosynthetically active radiation (PAR) and relative humidity within crop canopy were recorded at different phenological stages. Weekly observations on severity of yellow rust, brown rust, foliar blight and incidence of Karnal bunt at harvest were determined under different treatments. Among the three different sowing dates, the yellow rust severity in variety HD 2967 was reported to be highest (56.14%, 56.17%) at Ludhiana and Gurdaspur (56.75%, 58.42%) in early sowing under M2 than other treatments during rabi 2021-22 and 2022-33, respectively. The brown rust severity was higher (65.44%, 68.21%) at Ludhiana and Gurdaspur (61.76%, 63.5%) in early sowing under M2 than other treatments during rabi 2021-22 and 2022-33, respectively. It was observed that early date of sowing (15th October) recorded higher foliar blight severity (28.52%, 29.35%) at Ludhiana and Gurdaspur (21.69%, 30.65%) in variety HD 3086 in M2 than other treatments during rabi 2021-22 and 2022-23. The Karnal bunt disease incidence was relatively higher at Ludhiana (17.9% and 11.6%) and Gurdaspur (21.4% and 15.9%) in variety PBW 725 under M2 during normal sowing than other treatments during both the years of study, respectively. From correlation coefficient and regression analysis, it was concluded that temperature (maximum and minimum), sunshine hours and rainfall were observed as key parameters in spread of wheat diseases. Grain yield during rabi 2021-22 and rabi 2022-23 were higher in early sowing (43.3q/ha, 48.1 q/ha) at Ludhiana and Gurdaspur (44.5 q/ha, 50.8 q/ha) than other dates of sowing during both the years under study. In variety x microclimate modification levels treatments, grain yield was higher (43.1q/ha, 47.2q/ha) at Ludhiana and Gurdaspur (44.0 q/ha, 50.2 q/ha) in variety PBW 725 under M1 than other treatments during both years under study. Early date of sowing recorded more yield losses followed by late and normal sowing and losses were more at Gurdaspur as compared to Ludhiana. Average yield losses during rabi 2022-23 were higher i.e. 5.6% and 7.1% as compared to 1.6% and 2.3% during rabi 2021-22 at Ludhiana and Gurdaspur, respectively. From in vitro study, it was observed that urediniospore germination of pathotypes of Puccinia striiformis and Puccinia triticina was maximum at 15°C and 20°C, respectively at pH 7.0 and 1250 lux light intensity. So, if high temperatures along with sunny days prevail rust can flourish in wheat fields. The random forest regression (RF) for February month, support vector regression (SVR) for March month, SVR and BLASSO for 15 February to 15 March period and random forest for overall period surpassed the performance than other models for forewarning of Karnal bunt. From the CART analysis, it can be inferred that maximum yellow rust severity can occur if >9.2 sunshine hours/day and >9.1oC minimum temperature occurs or, dew point temperature is >14oC and mean temperature is <15oC or dew point temperature is < 14oC and humid thermal index is <2.4.
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    ThesisItemOpen Access
    Optimizing productivity of maize under emission based climate scenarios by mid and end of 21st century in Punjab
    (Punjab Agricultural University, Ludhiana, 2022) Kothiyal, Shivani; Sidhu, Prabhjyot Kaur
    The study was conducted to analyse the maize yield and phenology under the future scenarios at different zones in Punjab. The CERES-Maize model was used to analyse the yield trend and observe the deviation of yield and phenological stages of two cultivars PMH1 and PMH2 during the mid-century (2021-50) and end-century (2066-95) from the baseline period (2010-2020). The CERES-Maize model was calibrated for the crop data collected under the mandatory trial of the “All India Co-ordinated Research Project on Agrometeorology” during 2018 and validated for the same trial during 2019. The calibration and validation results showed the simulated model results to be close to the observed with a low NRMSE (%) for both the cultivars PMH1 (1, 0.8, 3, 11.7) and PMH2 (0.9, 0.7, 2, 9) for anthesis, maturity, grain yield and LAI, respectively. The yield and LAI showed a polynomial relationship with the sowing window (20th May to 30th June) in Punjab with high grain yield peaks/ LAI during 20 May to 7 June as 5200-6000 kg ha-1/ 2.9-3.2 and 4200-5400 kg ha-1/ 2.8-3.0 respectively for varieties PMH1 and PMH2, respectively. The calibrated and validated model was used to study the future maize yield trend, deviation of yield and phenology from the baseline and optimization practices to avoid the negative effects. The maize yield and phenology of both the cultivars was analysed under the four scenarios RCP2.6, RCP4.5, RCP6.0 and RCP8.5 using the weather data of four GCMs (CSIRO-Mk-3-6-0, FIO-ESM, IPSL-CM5A-MR and Ensemble). The simulated maize yield trend for the current sowing dates showed a strong deviation at agroclimatic zone II (upto 94% and 77%), III (95% and 90%), IV (92% and 88%) and V (92% and 90%) for PMH1 and PMH2, respectively while the maturity for all the zones shortened by 25 days during the end-century under RCP8.5. The optimized sowing window (10th May to 14th July) was evaluated and the results showed the late dates of sowing to perform well at agroclimatic zone II and III while early sowing dates at V (Faridkot).The optimization of nitrogen doses (lower: 65kg ha-1; higher: 185 kg ha-1) showed slight yield increment at higher doses for agroclimatic zone II, III and V (Faridkot). Amongst the four GCMs, the FIO-ESM model overestimated the yield while the CSIRO-Mk-3-6-0 under estimated the yield. The optimization practices if used efficiently can help avoid climate change impact on maize crop in Punjab but only during mid-century under all the scenarios while under RCP8.5 during end-century no yield increment was observed.