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ThesisItem Restricted Development of agroclimatic model for prediction of wheat phenophases and yield by using ICT tools(Punjab Agricultural University, Ludhiana, 2020) Mehta, Purnima; Dhaliwal, L. K.The field experiments were conducted at the Research Farm, Department of Climate Change and Agricultural Meteorology, Punjab Agricultural University, Ludhiana during rabi seasons of 2017-18 and 2018-19. The wheat varieties viz., PBW-725, PBW 677 and HD 3086 were sown on 25th October, 15th November and 5th December. Different agroclimatic indices viz., growing degree days, heliothermal units, photo-thermal units, pheno-thermal index, hygro-thermal units and relative temperature disparity were computed at different phenological stages. Heat use efficiency, helio-thermal use efficiency, photo-thermal use efficiency and radiation use efficiency were computed during both the years.The canopy temperature based different indices viz.,average canopy minus air temperature (TcTa) and summation stress degree days (SDD) were also calculated during both the crop seasons. The results indicated that growing degree days, hygro-thermal units and relative temperature disparity were higher in 25th October sown crop followed by 15th November and 5th December sown crop for variety PBW 677 during both the years. Whereas, helio-thermal units and photo-thermal units were higher in 5th December sown crop in comparison to 25th October sown crop for variety PBW 677 than PBW 725 and HD 3086. Heat use efficiency, helio-thermal use efficiency and photo-thermal use efficiency were higher in 25th October sown crop followed by 15th November and 5th December sown crop for biomass and grain yield during both the years. The results showed that crop sown on 5th December experienced higher canopy temperature at reproductive stages as compared to 25th October and 15th November sown crop. Higher negative stress degree days (SDDs) were observed under 25th October sowing as compared to 15th November and 5th December sowing reflects that canopy temperature was lower this means that the crop is healthy and without any stress.The grain yield was significantly higher in 25th October sowing (50.8 q/ha and 52.2 q/ha) as compared to 15th November (48.3 q/ ha and 49.9 q/ha) and 5th December sowing (42.1 q/ha and 43.3 q/ha) during both the crop seasons. Based on historical data, agroclimatic indices based regression models were developed for grain yield prediction at vegetative and reproductive stages under different dates of sowing. At the reproductive stage, accumulated growing degree days (AGDD) based model for 25th October sowing gave 16 per cent error followed by 15th November sowing with 5.7 per cent error. The AGDD based model for yield prediction is the best model with a minimum 5.7 per cent error under 15th November sowing.The Agromet wheat app is an android based app and android studio 3.5 is used for coding, backend core Java language is used and database is created through firebase. Agromet wheat mobile app was developed to give information to the users in English and regional language Punjabi. This app gives information about wheat management viz., varieties, sowing methods, irrigation, fertilizers, plant protection and recent advisories to the farmers about weather warning, insect and disease warning. Growing degree days calculator was developed to predict the phenological stages and yield of wheat crop.ThesisItem Open Access Impact of western disturbances on wheat (Triticum aestivum L.) crop in Punjab(Punjab Agricultural University, Ludhiana, 2020) Satinder Kaur; Gill, K.K.The present study entitled “Impact of western disturbances on wheat (Triticum aestivum L.) crop in Punjab” was carried out using and analyzing historical data, conducting field experiment and validating data using SPSS software. Data pertaining to historical weather parameters were studied for different districts of Punjab- Amritsar, Ludhiana, Bathinda, Ballowal, Faridkot and Patiala which showed that on an average for all the districts under study maximum onset and withdrawal of monsoon was observed in October and May, respectively. Further, total number of western disturbances was observed maximum in Day 1, followed by Day 2 and decreases subsequently. In addition to this it was also found that western disturbances was higher in January, February and March in comparison to other months of the growing season mostly in all the districts. Field experiment was conducted for two consecutive years during the rabi seasons of 2017-18 and 2018-19 at three locations, namely, Ballowal Saunkri, Ludhiana and Faridkot. The experiment was replicated thrice in a factorial split plot design with nine combinations of dates of sowing (25th October, 15th November and 5th December) and three varieties (WH1105, Unnat PBW550 and PBW590) in the main plots and two levels of irrigation (recommended and recommended± forecast based) in the subplots. Crop phenology was observed by visual observations. Micrometeorological parameters were recorded within the crop canopy at different phenological stages while biometric observations were recorded at 20 days interval. The results revealed that crop growth, yield and yield attributing characters were found highest under 15th November sowing at all the locations. Cultivar PBW590 found out to be poor performer when compared to other two varieties. Regression equations among different weather parameters and green yield of wheat were developed using SPSS software for different districts of Punjab in which R2 value ranged from 82.9 in Ludhiana to 99.9 in Bathinda. Further calibration and validation of data resulted in minimal error.ThesisItem Restricted Impact of El Nino and La Nina events on climatic conditions and rice-wheat productivity in Punjab(Punjab Agricultural University, Ludhiana, 2019) Chand, Shivani; Dhaliwal, L.K.Agriculture in India is mostly rainfed and is greatly influenced by Indian Summer Monsoon Rainfall (ISMR). It contributes to about 75 per cent of the total annual rainfall. El Nino, a phenomenon during which unusually warm water appears in the eastern Pacific Ocean has inverse relation with Indian summer monsoon rainfall. The historical data of different meteorological parameters (maximum temperature, minimum temperature, relative humidity, sunshine hours and rainfall) for different locations of Punjab viz. Amritsar (1971-2017), Ballowal Saunkhri (1984-2018), Bathinda (2001-2018), Ludhiana (1971-2018) and Patiala (1971-2018) were collected from the Department of Climate Change and Agricultural Meteorology, PAU, Ludhiana and Met Centre, India Meteorological Department. The rice-wheat productivity data were collected from indiastat.com and Statistical Abstract of Punjab. The data related to groundwater table (1998-2017) were collected from the Central Ground Water Board, Punjab. The El Nino/ La Nina events data were retrieved from Golden Gate Weather Services.The decade wise monthly analysis of maximum temperature showed increasing trend at Ballowal Saunkhri, Ludhiana and Patiala during all months except January, June and September whereas at Amritsar and Bathinda decreasing trend was observed in most of the months. The minimum temperature was found to be increasing at all the locations. The mean relative humidity showed increasing trend at Amritsar, Ballowal Saunkhri, Bathinda and Patiala whereas at Ludhiana few months showed negative mean relative humidity. The increasing trend in rainfall was observed at Amritsar and Ludhiana during all months except May, July, November and December whereas Ballowal Saunkhri and Patiala showed decreasing trend in most of the months. Inter season rainfall variability during kharif season mostly occurred in El Nino years at all locations except at Ballowal Saunkhri. The heavy rainfall events occurred more frequently compared to very heavy and extremely heavy rainfall events at different locations. Intra season rainfall variability between different seasons was highest during post monsoon season followed by pre monsoon season. Drought indices standardized precipitation index (SPI) and aridity index (AI) were calculated. SPI showed that El Nino year was more related with annual and kharif deficit years. Aridity index showed that El Nino years were warm and dry compared to La Nina and neutral years and in recent years Ballowal Saunkhri showed shift towards warm and dry conditions. The ground water table level showed significant decrease at different locations of Punjab. The relationships between groundwater table and rainfall indicated that continuous deficit rainfall years led to decline in groundwater table. The correlation between wheat grain yield and diurnal range of temperature was negative at all the locations except at Ballowal saunkhri.ThesisItem Restricted Impacts of climate change on spatio-temporal variability in cropping patterns over trans-gangatic plains(Punjab Agricultural University, Ludhiana, 2018) Baljeet Kaur; Som Pal SinghIn the present study, analysis of spatial and temporal variation in climatic parameters and cropping patterns in trans-gangetic plains was carried out. The historical climatic data and data pertaining to area and productivity of wheat, rice and maize crops for the period 1971-72 to 2015-16 were employed for the investigation. The climatic data was analysed on the basis of decades, years and season using Mann Kendall and Sen’s slope statistics to examine the variability and trends over the study area. Spatial and temporal interpolations using Inverse Distance Weighted (IDW) method were used to develop the gradient of the data. Relative change in area of wheat, rice and maize was determined decade-wise. Step-wise regression was used to study the impact of climate change on wheat, rice and maize productivity. Under future climatic scenario RCP8.5, InfoCrop model was evaluated to project the wheat, rice and maize yields. During rabi season, higher rate of maximum and minimum temperature was observed for Haryana and central zone of Punjab. No trend was observed in rainfall in trans-gangetic plains. Rate of increase in maximum temperature was 0.063 oC for Haryana, 0.04 oC for northern Rajasthan and 0.049 oC for Delhi. Rate of increase in minimum temperature was 0.031oC for Punjab and 0.045 oC for Haryana. Area under wheat over TGP increased at the rate of 468 ha per decade significantly (R2 =0.92). It has increased by 24.68%, 80.93%, 9.39% and 39.80% in Punjab, Haryana, northern Rajasthan and TGP; respectively whereas area under wheat in Delhi decreased by 57.78% as compared with 1971-80. The analysis of area under rice and maize revealed that area under maize declined over the trans-gangetic plain region by 70.7% in 2016 compared with 1980. Per cent change in rice area was 157.6 in TGP. Wheat and maize productivity was affected negatively mostly by minimum temperature alone. Rice productivity showed positive relationship with increasing trends of temperature. Future projection of wheat, rice and maize showed that wheat productivity will decrease more in Punjab (R2=0.76) followed by Delhi (R2=0.72) and Haryana (R2=0.66). Decline in rice yield will be more in northern Rajasthan (R2=0.62) followed by Delhi (R2=0.58). More declines in maize will be in Haryana (R2= 0.77) under future climatic scenario.ThesisItem Restricted Assessment and management of climatic variability impact on evapotranspiration and water productivity of Maize (Zea mays L.) in Punjab(Punjab Agricultural University, Ludhiana, 2018) Harleen Kaur; Kingra, P.K.ABSTRACT The field experiment entitled, “Assessment and management of climatic variability impact on evapotranspiration and water productivity of maize (Zea mays L.) in Punjab” was carried out at the Research Farm of the Department of Climate Change and Agricultural Meteorology, Punjab Agricultural University, Ludhiana for two consecutive kharif seasons of 2016 and 2017. The field experiment comprising of 12 treatments was carried out in split plot design with 3 replications having three dates of sowing (D1-Third week of May, D2-Second week of June and D3- First week of July) in main plots and two irrigation levels i.e. irrigation at IW: CPE of 1.00 (I1) and 0.75 (I2) and two mulch levels viz. mulch @ 5 t ha-1 (M1) and no mulch (M2) in the sub-plots. The soil of the experimental site was loamy sand in texture with normal pH and electrical conductivity and low in organic carbon. PAR interception and relative humidity was highest in D2 as compared to D1 and D3 and among irrigation and mulch treatments in I2 and M1. The canopy temperature was highest in D3 as compared to D1 and D2 and among irrigation and mulch in I1 and M2 treatments at reproductive stage of crop. Higher plant height, dry matter and LAI was observed in the crop sown during second week of June and among irrigation and mulch treatments in I2 and M1. The total water use was more in D1 (540.5 and 477.5 mm) as compared to the D2 (493.3 and 399.0 mm) and D3 (415.1 and 316.3 mm) in 2016 and 2017, respectively. Among mulch and irrigation levels, the total water use was more in non-mulched crop (M2) and under IW/CPE=1.00 (I1).The yield attributing characters under D2 were statistically at par with D1 and significantly higher than D3 and among mulch and irrigation treatments in M1 and I2. During 2016, difference in grain yield under different dates of sowing was found to be non-significant. During 2017, the grain yield under D2 (52.37 q/ha) was at par with D1 (50.86 q/ha) but was significantly higher than D3 (41.04 q/ha). During 2017, among mulch levels, the grain yield was significantly higher in mulch applied crop (50.71 q/ha) as compared to non-mulched crop (46.14 q/ha). The water, heat and radiation use efficiency of maize was also found to be higher under D2, I2 and M1, during both the years. The priestley-taylor method gave higher ETo in all three dates of sowing and was closer to open-pan evaporation except in first date of sowing during 2016, in which ETo was higher in FAO-56 (602.4 mm). The crop coefficients calculated by Papadakis method were comparatively higher as compared to that calculated by other methods. Good agreement was observed between actual and simulated yield (R2=0.77 each) and water productivity (R2= 0.43 and 0.44) during both the crop growing seasons. Simulation results showed that water productivity of maize increased with increase in CO2 concentration and decreased with increase in temperature, but this decrease could be compensated by simultaneous increase in CO2 concentration.ThesisItem Restricted Crop-Weather-Aphid Interaction In Raya (Brassica Juncea L.) Under Different Hydro-Thermal Environments(Punjab Agricultural University ;Ludhiana, 2002) Dhaliwal, Lakhvir Kaur; Hundal, S. S.ThesisItem Open Access Radiation Use Efficiency Of Brassica Cultivars Under Varying Environments And Validation Of ``Brassica`` Model(Punjab Agricultural University ;Ludhiana, 2004) Nigam, Rahul; Hundal, S. S.ThesisItem Open Access Radiation Water Use Efficiencies And Phenological Study In Summer Mungbean (Vigna Radiata L. Wilczek) Under Varied Hydrothermal Regimes(Punjab Agricultural University ;Ludhiana, 2002) Ravi Kiran; Bains, G. S.ThesisItem Restricted Diagnosis of thermal and nutrient stresses in wheat (Triticum aestivum L.) using remote sensing techniques and their management(Punjab Agricultural University, Ludhiana, 2016) Sukhjeet Kaur; Som Pal SinghField investigations focusing on “Diagnosis of thermal and nutrient stresses in wheat (Triticum aestivum L.) using remote sensing techniques and their management” were carried out during Rabi seasons of 2013-14 and 2014-15 at Research Farm, School of Climate Change and Agricultural Meteorology, Punjab Agricultural University, Ludhiana (Long 75.48’E, Latitude 30.56’N and 247 abmsl). The experiment was laid out in Split- split plot design with three replications having three temperature regime (D1= October 30, D2= November 15 and D3= November 30) in main plot, three nitrogen level (N1=RDF (Recommended dose of N), N2=125% RDF (25% more than recommended N), N3=150% RDF (50% more than recommended N) in sub plot and four post- anthesis strategies (P0=Control, P1= Water sprayed, P2= Foliar spray of ZnSO4.7H20 (0.5%), P3= Thiourea (10 mM) at anthesis and 20 days after anthesis in sub-sub plot during both years. The crop sown on October 30 having 150% RDF and foliar spray with ZnSO₄.7H₂O (0.5%) at and 20 days interval after anthesis experienced low canopy temperature. The PAR interception and relative humidity was higher in October 30 sowing as compared to November 15 and November 30 sowing. The vegetation indices (NDVI, GNDVI, DVI, RVI and GI) computed from spectral reflectance data with the increased in crop biomass, attained a maximum value at anthesis (90 DAS) and thereafter decreased. All the vegetation indices values were improved by spraying the crop with ZnSO₄.7H₂O (0.5%) followed by Thiourea (10 mM) and water over control although differences recorded were non significant. The significantly higher values of these indices were recorded in Oct 30 sowing with 150% RDF as compared to other treatments. The periodic plant height, LAI, dry matter production, tiller production were significantly higher in October 30 sowing with 150% RDF. The significantly higher biological, straw and grain yield were recorded under crop sown on October 30 as compared to November 15 and November 30 although biological, straw and grain yield of October 30 sowing was statistically at par in November 15 sowing. The delayed sowing resulted in the increase in N, P and K content in November 30 as compared to November 15 and October 30 sowing but uptake of N, P and K was more in October 30 sowing because of longer duration of crop. The N, P and K content and uptake increased in 150% RDF than other nitrogen levels. The foliar spray of ZnSO₄.7H₂O (0.5%), Thiourea (10 mM) also improved the N, P and K content as well as uptake than control plots. The quality parameters (protein content, grain hardness and appearance) were significantly better in October 30 sowing with 150% RDF. The quality parameters (protein content, grain appearance and hardness) were significantly improved in October 30 with 150% RDF and foliar application of ZnSO₄.7H₂O (0.5%). The productive environmental variables (GDD, SDD and HUE) were combined with vegetation indices (NDVI, DVI, GNDVI, RVI, GI) and biological variable (LAI, Dry matter production) and reflected the overall good correlation with yield and dry matter, showing their potential use for crop weather models and yield forecasting.
