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ThesisItem Open Access Formulation of Crop Weather Calendar for Maize (Zea mays L.) Under Punjab Conditions(Punjab Agricultural University, Ludhiana, 2021) Sandeep Singh; Sidhu, Prabhjyot KaurThe study entitled “Formulation of crop weather calendar for maize (Zea mays L.) under Punjab conditions” has been carried out during Kharif 2019 at Research farm, Department of Climate Change and Agricultural Meteorology, Punjab Agricultural University, Ludhiana. The experiment was laid out in factorial randomized block design keeping four thermal environment (T1: 28th May, T2 : 6th June, T3: 15th June and T4: 24th June) and two cultivars (PMH-1 and PMH-2) replicated four times. Maize crop sown during 28th May took more days to attain maturity as compared to 6th June followed by 15th and 24th June sowings. Amongst the four sowing dates LAI, dry matter accumulation, PAR interception and heat use efficiency were higher and extinction coefficient was lower in 15th June sowing which may be due to profuse vegetative growth of crop. Also the yield attributing characters like number of cobs m-2, number of grains per cob, cob length, cob yield, grain yield and harvest index were higher in 15th June sowing. The actual productivity data for maize for Ludhiana, Ballowal and Amritsar were collected for the time period 2004-2018 and it was classified in high, medium and low yield crop years. Then for the high yield years, i.e. 2013, 2014 and 2015 for Ludhiana, 2014, 2016 and 2017 for Ballowal and 2006, 2007 and 2011 for Amritsar the effect of meteorological parameters were scrutinized. The analysis of weather data revealed that temperature above the normal during the month of August is not favorable for maize crop. Heavy rainfall and below average sunshine hours at the time of grain filling stage have directly reduced the maize yield. Further weekly climatic normal and their critical ranges for different growth stages were compiled to formulate the crop weather calendars. These calendars can be used for issuing agro-advisory and for prediction of high crop yield. Further weather based “Thumb Rule models” using the weekly meteorological data were formulated for predicting the yield of maize crop at three different locations of Punjab.ThesisItem Open Access Quantification of evapotranspiration using EEFLUX tool and comparison by empirical methods in maize (Zea mays L.)(Punjab Agricultural University, Ludhiana, 2022) Deepan R; Som Pal SinghEvapotranspiration (ET) is one of the most important parameter in agriculture and to water management and irrigation requirement. Under the present scenario of Climate change and Global warming, importance of ET measurement and its validation assumes a great significance. There are various techniques used to estimate actual measurement of ET in the field condition. However, researchers have developed state of the art instrument to measure it in the field condition and instruments of varying accuracy are available. The instrument can measure point value of ET for being placed at particular location in the field and therefore the spatial accuracy of the data is bound to reduce to a certain extent. On the other hand, the empirical estimation of ET has its own limitation owing to the requirement of huge data set to estimate the ET to near accuracy. Google EEFlux is a web-based tool which utilizes the satellite-based information to provide the ET rate on spatio-temporal scale. Therefore, an effort has been put forth to estimate ET using the Google EEFlux for maize crop. The ET has been estimated using the Google EEFlux for maize crop sown in the field experiment at the Research Farm, Department of Climate Change and Agricultural Meteorology, PAU during the kharif season of 2020-21. The ET was also computed using Penman’s equation geeSEBAL, NRSC-NHP, Cropwat 8.0 and FAO Ref-ET calculator for PMH-1 and PMH-2 varieties of maize during the same period grown under three sowing environments. The relationships were developed between ET (Google EEFlux), ET (geeSEBAL), ET(NRSCNHP) and ET (FAO-ETo calculator). The relationships indicated a significant association between the ET obtained by both these methods. The data generated can help the researchers to fine tune treatments and also to reorient the irrigation and management research programs.ThesisItem Open Access Computation and validation of different agroclimatic indices for wheat(Punjab Agricultural University, Ludhiana, 2023) Manpreet Kaur; Dhaliwal, L.K.The field experiment was conducted at the Research Farm, Department of Climate Change and Agricultural Meteorology, Punjab Agricultural University, Ludhiana during rabi season of 2021-22. The wheat varieties viz., PBW 1 Zn, PBW 725, Unnat PBW 343 and PBW 752 were sown on October 26, November 8, November 16 and November 23. The crop was sown in Randomised complete block design with four replications. The recommended Package of Practices by PAU were followed for raising the crop. The micrometeorological parameters viz. photosynthetically active radiation (PAR), canopy temperature and relative humidity within canopy were recorded at periodic intervals. Biometric observations such as leaf area index (LAI) and dry matter accumulation (DMA) were recorded periodically. The yield and yield contributing characteristics were recorded at the time of harvesting. The wheat yield data of Ludhiana district from 2000-2001 to 2021-22 were collected and corresponding meteorological data on different parameters were obtained from Agrometeorological Observatory. 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 rabi 2021-22. The results indicates that growing degree days, photo-thermal units, hygro-thermal units and relative temperature disparity were higher in October 26 sowing as compared to November 23 sowing. Whereas, helio-thermal units were higher in November 23 sowing. Heat use efficiency, helio-thermal use efficiency and photo-thermal use efficiency were higher in October 26 sown crop as compared to November 23 sown crop for total biomass and grain yield.The results showed that crop sown on November 23 experienced higher canopy temperature at reproductive stages as compared to October 26 sown crop. The grain yield was significantly higher in October 26 sowing (44.3 q ha-1) as compared to November 23 (39.2q ha-1) for variety Unnat PBW 343. Historical data on wheat yield and meteorological parameters were analysed from 2002-03 to 2021-22. The extreme heat wave years (2003-04, 2008-09 and 2021-22) indicates that maximum and minimum temperatures were higher than normal by 4 to 5°C during reproductive stage and no rainfall due to absence of western disturbances in the month of February and March was responsible for yield reduction. Temperature condition index was lower at reproductive phase and positively correlated with grain yield. Lower the values of temperature condition index, higher was the stress condition in the wheat crop and viceversa. The crop remained under stress in October 26 and November 8 sowing for 45 days whereas for November 16 and November 23 remained for 60 days. It means that late sown crop (November 16 and November 23) faced stress at heading stage and remained under stress for longer period as compared to early sowing (October 26 and November 8) which faced the moderate stress at anthesis stage.ThesisItem Embargo Assessing climatic and environmental implications of crop residue burning in Punjab using ground observations and satellite remote sensing(Punjab Agricultural University, Ludhiana, 2022) Yashi Singh; Kingra, P.K.The study entitled, “Assessing climatic and environmental implications of crop residue burning in Punjab using ground observations and satellite remote sensing” was conducted at the Department of Climate Change and Agricultural Meteorology, PAU, Ludhiana and Punjab Remote Sensing Centre, Ludhiana. Variability in meteorological variables (temperature, relative humidity, wind speed and sunshine hours), gases (NO2, SO2 and O3) and aerosols (PM2.5 and PM10) in wheat (March-May) and rice harvesting season (September-November) from 2017-21 was analyzed. In addition to this fire events data was collected through remote sensing (from VIIRS) for the same period. In Punjab, maximum burning points were observed in central region followed by south west region and north-east region. In central region, highest fire counts during wheat harvesting period were observed in 2019 (11602) and lowest in 2021 (7104), whereas for rice harvesting period they were highest in 2021 (40960) and lowest in 2019 (22548). Significant influence of crop residue burning was observed on the concentration of particulate matter in air as it increased drastically during crop harvesting period. During wheat harvesting season, Ludhiana experienced highest concentration of PM2.5 (85.66±26.49 µg/m3 ) and PM10 (160 ±43.49 µg/m3 ) during May 2018, whereas concentration of SO2 (15.54±4.24 µg/m3 ) and O3 (40.12±6.70 µg/m3 ) was observed highest in May 2019 and during rice harvesting season, Ludhiana experienced highest concentration of PM2.5 (140.83±49.37 µg/m3 ) and PM10 (305±97.45 µg/m3 ) during November 2017, whereas concentration of SO2 was observed highest (23.50±13.20 µg/m3 ) during 2018. However highest concentration of NO2 (47.12±15.33 µg/m3 ) was observed in October 2018 and of O3 (32.19±8.91) was observed in October 2020. Particulate matter (PM2.5 and PM10) depicted strong positive correlation with fire counts in all the agroclimatic regions of Punjab in the harvesting period of wheat and rice whereas somewhat variable relation was observed for NO2 and SO2. Mean temperature during November was found to be positively correlated while relative humidity and sunshine hours were observed to have negative correlation with fire events for most of the wheat and rice harvesting period. The results of the study indicated that crop residue burning is specifically responsible for increasing the amount of particulate matter in air which can have severe health implications.ThesisItem Embargo Optimizing subsurface drip irrigation and fertigation schedules in Bt cotton using crop simulation model(Punjab Agricultural University, Ludhiana, 2022) Simranjeet Kaur; Mishra, Sudhir KumarThe present study entitled “Optimizing subsurface drip irrigation and fertigation schedules in Bt cotton using crop simulation model” was conducted at Regional Research Station, Faridkot during Kharif 2020. The experiment was laid out in Randomized complete block design comprising of subsurface irrigation at 60 % ETc (I₁), 80 % ETc (I₂), 100 % ETc (I₃) along with fertigation of 75% RDN (F₁) and 100 % RDN (F₂): 112.5 kg N/ha]. Besides, surface flood irrigation with 100 % RDN (105 kg N/ha) and surface drip irrigation with 100 % RDN (112.5 kg N/ha) were considered as control. Various growth and yield attributes of cotton were found to be influenced with different fertigation treatments. Among the treatments, combination of 80 % ETc and 100 % RDN (I2F2) recorded highest seed cotton yield (3393 kg/ha) which was at par with fertigation of 100 % RDN with 100% ETc (I3F2). But, the seed cotton yield of treatment I2F2 was 32.3 % higher than surface flood (2565 kg/ha). Fertigation of 75 and 100 % RDN with 60 % ETc through subsurface drip recorded reduced seed cotton yield by 10.6 % and 4.8 %, respectively than surface flood irrigation with 100 % RDN. Similarly, (I2F2) improved the crop yield and quality attributes such as better lint yield (1182.9 kg/ha), seed yield (2210.7 kg/ha), ginning out turn (34.8 %), crop water use efficiency (5.80 kg/ha/mm) and apparent water use efficiency (12.26 kg/ha/m3). Thus, subsurface drip fertigation of 100 % RDN with 80 % ETc (I2F2) was not only profitable over surface flood irrigation but, it was also better than surface drip fertigation. Results depicted that more consumption of agroclimatic indices viz., GDD (2557°C day), HTU (17196°C day hour), PTU (33978°C day hour), SRDU (47977 MJ/ m2/ day) contributed to achieve better yield under 80 % ETc and 100 % RDN. Likewise, the DSSAT-CROPGRO-cotton model depicted higher d-stat remained above 0.958 for the simulation of various phenology, growth and yield parameters of cotton along with lower error values advocated for its application for varying inputs and management conditions.ThesisItem Embargo Simulating yield of canola (Brassica napus L.) cultivars using DSSAT-CROPGRO model under different growing environments(Punjab Agricultural University, Ludhiana, 2022) Jagjeet Kaur; Biswas, BarunThe Field experiments were conducted to achieve objectives of the present research entitled “Simulating yield of canola (Brassica napus L.) cultivars using DSSAT-CROPGRO model under different growing environments” at two locations of Punjab viz., experimental field of the Department of Climate Change and Agricultural Meteorology, Punjab Agricultural University, Ludhiana and PAU Regional Research Station, Gurdaspur, during rabi season 2020-21. The experiments were planned with five sowing dates (28th October (D1), 4th November (D2), 11th November (D3), 18th November (D4) and 25th November (D5)) and two cultivars (GSC 6 and GSC 7) in randomized complete block design with three replications. Periodic measurements of crop growth and performance were done to develop cultivar specific genetic coefficients for calibration of DSSAT-CROPGRO model. The crop performance, in terms of growth parameters and yield, was highest under D1, followed by D2, D3, D4 and D5. Significantly superior yield attributing characters (number of siliqua per plant, seed weight per plant, number of seeds per siliqua, 1000 grain weight) in early sown crop may be the reason of higher grain yield and harvest index of GSC 7 sown on 28th October as compare to cultivar GSC 6 and later sowing dates. The data generated during the field experiments was used for calibration of the DSSAT-CROPGRO model. The results showed good agreement between observed and simulated value with lower RMSE value for both locations. The DSSAT-CROPGRO model underestimated the days to emergence but over-estimated the days to anthesis and physiological maturity for Ludhiana. For Gurdaspur, the model under-estimated the days to emergence, but overestimated the days to anthesis and physiological maturity. The DSSAT-CROPGRO canola model well simulated the leaf area index for Ludhiana (R2 = 0.52) and Gurdaspur (R2 = 0.97). The grain yield and harvest index were over-estimated for both locations, but biological yield was under-estimated. Overall, the DSSAT-CROPGRO model was found to be applicable for the simulation of canola (Brassica napus L.) cultivars under different growing environments of Punjab.ThesisItem Embargo Applicability of medium range weather forecast in respect to growth and yield attributes of wheat in south-west Punjab(Punjab Agricultural University, Ludhiana, 2022) Tirath Singh; Raj Kumar PalThe current study evaluates the predictability of wheat production using forecast scenarios that were gathered from the IMD in order to evaluate the potential of the wheat season weather forecast. CERES-Wheat model was used to estimate crop phenology and wheat yield. In this regard, the experiment was carried out in a split-plot design at Punjab Agricultural University (PAU), Regional Research Station, Bathinda (30°36'09" N, 74°28'55" E) during the rabi season of 2021 with three replications. The main plot treatments included five sowing dates viz., October 25, November 04, November 14, November 24 and December 04 with four sub-plot treatments of variety which were HD 3086, PBW 725, HD 2967, PBW 658. All the cultural practices were followed as per the package of practices of Punjab Agricultural University except the experimental treatments. Model validation showed that simulated emergence, anthesis and maturity were deviated over observed by 1-3 days, 1-8 days, and 1-20 days, respectively, whereas anthesis, maturity, and yield were overestimated. Additionally, the simulated wheat yield differed from the observed yield by 0.5 to 12 per cent. Phenology and yield were found to have greater RMSE values, wider deviations between simulated and actual values, and less connection with delayed sowing. For the wheat growing season (2013–2021), rainfall, Tmax, and Tmin weather forecast were employed, which wereto assess the likelihood of wheat production at various sowing periods. The medium-range weather forecast and the actual weather data closely matched each other for wheat phenology and yield. The annual fluctuation in observed wheat yield as well as treatment-wise variations were more or less effectively reflected by the daily medium-range weather forecast data. The research's conclusions are very useful for making decisions in the study region, determining when to sow wheat and other agricultural inputs, and developing long-term plans for other agricultural chores.ThesisItem Embargo Delineating thermal and land suitability zones of cotton under changing climatic conditions in Punjab using geospatial techniques(Punjab Agricultural University, Ludhiana, 2022) Varinderjit Kaur; Som Pal SinghRise in temperature particularly in lower latitudes, could have a negative effect on cotton growth, development and yield. To evaluate this, a present study has been carried out at Regional Research Station, Bathinda of Punjab Agricultural University, Ludhiana, comprising four sowing dates (April 01, April 20, May 10 and May 30) and two cultivars (non-Bt: F 2228 and Bt: RCH 773) in factorial randomized complete block design during 2020 and 2021. Using phenological calendar from above experiment, spatio temporal analysis of accumulated growing degree days and thermal growing period was carried out for the past (1990-2020) and future scenarios (2021-2055). Results revealed that growing degree days showed a positive trend @ 0.11-17.73°C day/year for the past (significant 5%) and @ 1.70-2.39°C day/year under RCP 2.6 to 7.20-26.38°C day/year under RCP 8.5 (significant 0.1%) for the future scenarios. Declining trend was observed for the thermal growing period @ 0.04-2.44 days/year for the past and @ 0.09-0.41 days/year under RCP 2.6 and @ 0.36-1.07 days/year under RCP 8.5 for future climate. Results of the crop simulation studies showed that future climate will increase the days taken to anthesis by 3.53% and 9.57%, maturity period by 0.30% and 3.63% and decrease the seed cotton yield by 13.75% and 34.23% under RCP 2.6 and RCP 8.5 in contrast to baseline period on account of elevated temperature and precipitation. Future land suitability analysis showed that there will be decrease in area under highly suitable zone in SBS Nagar (14.21%) and not suitable zone in Ferozepur (9.07%) and Bathinda (10.77%) districts. Results also showed that there will be increase in the area under suitable zones in SBS Nagar (10.66%) and Bathinda (10.8%) and in Ferozepur (7.51%) under the marginally suitable zone owing to increase in the temperature and rainfall of these regions.ThesisItem Embargo Identification of major abiotic bottlenecks in rice (Oryza sativa) productivity in Punjab(Punjab Agricultural University, Ludhiana, 2021) Yogesh Kumar; Sidhu, Prabhjyot KaurThe field experimenton rice was conducted during kharif 2020 at the Research farm, Dept of Climate Change and Agricultural Meteorology, PAU, Ludhiana to generate phenological field data for formulation of crop weather calendar under Punjab conditions. The rice was sown with four thermal environments i.e., T: 18h June, T2: 24t June, T3: 1s July and Ta: 8" July using four cultivars, i.e. PR-123, PR-124, PR-126 and PR-127. The experiment was laid out in split plot design with three replications, keeping thermal environments in main plot and four cultivars in sub plot. The rice crop transplanted during Ti took more days to complete their life cycle as compared to that sown during T2 followed by T3 July and Ta. Among the transplanting dates, LAI,number of tillers, dry matter accumulation, PAR interception and plant height were higher in early transplanted (T1) crop as compared to late transplanted (T4) crop which may be due to profuse vegetative growth. Among the yield attributes characters, T transplanted rice crop produced higher number of seed/panicle, seed yield, panicle length, biomass yield and 1000 seed weight. For the formulation of crop weather calendar the weekly and monthly normal of different historical meterological parameters was computed from daily weather data for Ludhiana, Patiala and Amritsar, kharif 1970 2019. These climatic normals were used for comparing the actual data (2000 -2019) to study the effect of meteorological parameters on yield of rice crop. The results revealed that temperature above and below normal in the months of July and August for continuous period is not favourable for rice productivity. Heavy rainfall in the months of September at flowering and grain filling stage with below normal sunshine hours have directly reduced the rice productivity.The actual meteorological data of high yield crop years over the past 20 years were analyzed for different growth stages of rice to work out the critical ranges of meteorological parameters. Crop weather calendar were formulated for rice crop by compiling the weekly climatic normals and critical limits of meteorological parameters for different growth stages and these can be used for agro-advisory service and for prediction of potential crop yield. Along with that weather based "Thumb Rule models'" using the weekly meteorological data were formulated for predicting the yield of rice at 3 locations in Punjab state. Further the major constraint in the productivity of rice was formulated from low yield years. Then complete Agrometeorologyot rice was developed. Keywords: Rice, Thermal environment, Meterological parameters, Growth parameters, Yield and Yield attributes, cropweather calendar, Thumb rulemodel, agrometeorology of rice.
