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Quantification of crop bio-physical parameters in rice (Oryza sativa L.) varieties under different establishment methods using CROPWAT model
(Punjab Agricultural University, 2023) Harmanpreet; Som Pal Singh
A field experiment was conducted at the Research Farm, Department of Climate Change and Agricultural Meteorology, PAU, Ludhiana and Rice Section of Department of Plant Breeding &Genetics during kharif 2022. Three rice varieties (PR 121, PR 126, PR 128) of different age seedlings (20 days,30 days and 40 days) were transplanted on different establishment methods-flat and ridge transplanting method. The experiment was laid out in factorial Split Plot Design. The results indicated that PAR interception was higher in ridge planting method as compared to flat method of transplanting with 30 days old age seedlings. The grain yield was recorded highest in ridge (73.8 q/ha) as compared to the flat method (71.0 q/ha). In the case of varieties, the highest grain yield was recorded in PR 126 (77.0 q/ha) followed by PR 128 (73.4 q/ha) and PR 121 (66.9 q/ha). In the case of 30 days old age seedlings transplanted (74.2 q/ha) were recorded as highest followed by 20 days old age seedlings (73.9 q/ha) and then 40 days old age seedlings (69.1q/ha). Total water productivity was recorded higher in ridge method of transplanting (0.42 kg/m3) as compared to flat method of planting (0.37 kg/m 3 ). In case of genotype, total water productivity recorded higher in PR 126 (0.46 kg/m3) followed by PR 128(0.38 kg/m3) and PR 121 (0.34 kg/m3) and in case of old age seedlings,30 days old age seedlings recorded highest water productivity (0.41 kg/m3) followed by 20 days and 40 days old age seedlings.
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 Singh
Evapotranspiration (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.
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.
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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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Identification of heat and cold wave period and its effect on cotton-wheat yield in south-west Punjab using geospatial technology
(Punjab Agricultural University, 2023) Gawai, Anjusha Sanjay; R.K. Pal
The present study focused on Bathinda district in extreme South-West Punjab, analyzing a 23-year span (2000-2022) of heat and cold wave occurrences. Noteworthy heat wave years were (2000, 2010 and 2022), displayed a pattern of rising instances followed by fluctuations and decline while severe heat waves exhibited sporadic variations. Concentrated heat waves were observed during wheat growing seasons (March-April), while cotton faced higher frequencies during May-June. Cold wave instances showed decreasing trend consistently, with prominent years (2008, 2005, 2012) marked by heightened occurrences. Notably, yield simulations using CERES-wheat and CROPGRO-cotton models accurately matched observed yields, demonstrating predictive potential (wheat: R2=0.72, RMSE=336.5, d-stat=0.90; cotton: R2=0.67, RMSE=407.1, d-stat=0.84).The observed associations between Land Surface Temperature (LST) and air temperature during heat waves (R2=0.80), as well as the negative correlations between LST and Normalized Difference Vegetation Index (NDVI) (R2=0.69) during the same periods. On the other hand, the relationships established between LST and minimum air temperature during cold waves (R2=0.49), as well as between LST and NDVI (R2=0.14) during cold wave periods. Six wheat growing and five cotton growing period showcased below-normal yields and prominent heat wave occurrences, confirmed by a significant correlation (R2=0.71 and R2=0.78) between their yield and NDVI. Three years experienced below-normal wheat yields during cold wave events surpassing the normal threshold. The implications of these findings extend to projections (2023-2050), predicting potential wheat yield losses due to heightened heat wave occurrences and reduced yields stemming from intensified cold wave days as well as cotton yield due to increased heat waves. This study provides a comprehensive exploration of the intricate relationship between heat and cold wave occurrences and their profound influence on cotton and wheat yields, augmented by a visionary glimpse into potential future scenarios, thereby illuminating the challenges that lie ahead for South-West Punjab's agricultural landscape.
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Simulating the yield of wheat under futuristic climate change scenarios in lower Shivaliks of Punjab
(Punjab Agricultural University, 2023) KuldeepKaur; Navneet Kaur
The study was conducted during the rabi season 2020-21 and 2021-22 at Regional Research Station, BallowalSaunkhri to produce field data for the calibration and validation of the CERES-wheat model using seven wheat cultivars (HD3226, Unnat PBW 343, Unnat PBW 550, PBW Zn1, PBW 725, PBW 660 and PBW 752) sown during 11th November (D1) and 15th December (D2). The daily future data (2010-2095) for lower shivaliks of Punjab (BallowalSaunkhri) was downloaded from Marksim weather generator using outputs of CSIRO-Mk3-6-0 climate model under four RCP scenarios (RCP 2.6, RCP 4.5, RCP 6.0 and RCP 8.5). The bias correction of model data (temperature, rainfall and solar radiation) was done by developing correction functions (using model and observed data from 2010-2015) from different bias correction methods (difference method, Leander and Buishand method, modified difference method, linear scaling, variance scaling and quantile mapping). The difference method was used for further correction of data as this method gave good statistical results with low error and high efficiency. Further, the model data (2016-2020) was corrected using the best bias correction method which was then validated against the observed data (2016-2020). The validation of the correction function by reduced the biases between model and observed data. The correction of the future data (2021-2095) and further projections on annual, seasonal and monthly basis was done using the difference method of bias correction.The study revealed that the annual maximum temperature by the end of 21st century is likely to increase by 1.3°C, 6.8°C, 6.3°C and 8.3°C and minimum temperature increased by 0.7 °C, 1.7 °C, 1.3°Cand 2.6 °C under RCP 2.6, RCP 4.5, RCP 6.0 and RCP 8.5 respectively. The annual rainfall may decrease under RCP 2.6 (-22.4 mm) whereas increased under RCP 4.5, RCP 6.0 and RCP 8.5(147 mm, 291.6 mm and 30.1 mm) respectively. The analysis of the corrected data on annual basis revealed that solar radiation may increase by 0.6 MJ/ m2 /day, 0.7 MJ/ m2 /day, 1.0MJ/ m2 /day and 0.9 MJ/ m2 /day under RCP 2.6, RCP 4.5, RCP 6.0 and RCP 8.5 respectively. For the annual, kharif, rabi, winter, pre-monsoon, monsoon and post-monsoon maximum temperature would rise by 0.01 to 0.06, 0.01 to 0.05, 0.01 to 0.06, 0.01 to 0.07, 0.01 to 0.06, 0.01 to 0.06 and 0.01 to 0.05°C per year under different RCP scenarios by the end of 21st century. Similarly, minimum temperature would increase by 0.01 to 0.07 °C for annual, kharif,rabi, monsoon and post-monsoon respectively while 0.01 to 0.08°C for winter and 0.01 to 0.06°C for pre-monsoon increases per year under different RCP scenarios. The rainfall under different RCP scenarios would change by 1.75mm, -1.98mm, 0.25mm, 0.27mm, -0.01mm, -1.55mm and -0.48mm for annual, kharif, rabi, winter, premonsoon, monsoon and post-monsoon per year respectively. For the annual, kharif, rabi, winter, pre-monsoon, monsoon and post-monsoon solar radiation would rise by 0.01 MJ/m2/day under different RCP scenarios per year. The calibration and validation of the CERES-wheat model showed good agreement between the observed and simulated values with NRMSE value of 0.5 and 0.4 for anthesis and maturity respectively, and 9.0 and 8.4 for grain yield and biomass yield respectively. The simulation of phenology and yield using CERES-wheat model under projected climate scenarios showed the significantly decreasing duration 6 to 31 days for 11 November and 3 to 15 days for 15 Decemberand grain yield 259 to 1981 days for D1 sowing and 85 to 1285 days D2 sowing datesof wheat crop under different RCP scenarios in BallowalSaunkhri, Punjab. The reduction in the maturity period is more under RCP 8.5 (30 days for HD 3226; 31 days for Unnat PBW 550 and 30days for PBW 660) followed by RCP 4.5 (17 days for HD 3226; 18 days for Unnat PBW 550 and 16 days for PBW 660), RCP 6.0 (19 days for HD 3226; 20 days for Unnat PBW 550 and 19 days for PBW 660) and RCP 2.6 (7 days for for HD 3226; 5 days for Unnat PBW 550 and 6 days for PBW 660).The higher temperature may be the reason behind the more grain yield reduction because the physiology of the crop is adversely affected under high temperature conditions. The study concluded that more decrease in grain yield was more in 11th November sowing as compared to the 15th December sown crop, therefore delaying the sowing time in December will be helpful in combating the effect of increasing temperatures on crop duration and yield of wheat crop in the future.
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Effect of microclimate on white rust of mustard under open and poplar plantation
(Punjab Agricultural University, 2023) Bhushan Kumar; Sandhu, Sarabjot Kaur
The present study entitled “Effect of microclimate on white rust of mustard under open and poplar plantation” was conducted at the Research Farm of Department of Climate Change and Agricultural Meteorology and Research Farm of Department of Forestry and Natural Resources, Punjab Agricultural University, Ludhiana, during the rabi season of 202122. The experiment was conducted under split plot design with 3 replications having three dates of sowing (10th October, 5th November and 1st December) and two varieties (PBR-91 and Giriraj) in main plot with three nitrogen levels treatment (N1: Recommended N, N2: Recommended N+25%, N3: Recommended N+50%) in sub plots. Incidence and severity of white rust was recorded from 5th to 12th standard meteorological week under both the growing environments. The micrometeorological parameters like PAR interception, canopy temperature and relative humidity within crop were observed at periodic intervals under both the growing environments. Among micrometeorological parameters, PAR interception (76.3% in open and 56.2% under poplar plantation) and relative humidity (69.2% in open and 72.7% under poplar plantation) was maximum in 10th October sown crop, while canopy temperature (25.5ºС in open and 24.5ºС under poplar plantation) was maximum in 1st December sowing. The mustard variety (PBR-91) had highest white rust incidence (55%) in 1st December sowing, which was 10.0 per cent higher than the 5th November sown crop and 14.0 per cent higher than the 10th October sown crop in open condition. Similarly, Giriraj sown on 1st December had the highest white rust incidence (51%), which was 6.0 per cent higher than the 5th November sown crop and 16.0 per cent higher than the 10th October sown crop in open condition. Similarly, the crop sown on 1st December had the highest white rust incidence (50%) under poplar plantation, than the 5th November and 10th October sown crop. The grain yield was maximum (17.93 q/ha) in 10th October sowing followed by 5th November (16.27q/ha) and 1st December (13.77q/ha) sown crop under open conditions. Whereas, under poplar plantation, grain yield was comparatively lesser than open conditions. The grain yield was maximum (15.81q/ha) in 10th October sowing followed by 5th November (14.01q/ha) and 1st December (11.27q/ha) sown crop under poplar conditions. Among different varieties, PBR 91 gave higher grain yield under open and poplar conditions.
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Productivity of French bean genotypes as influenced by microclimatic modifications
(Punjab Agricultural University, 2023) Komal Rani; Gill, K.K.
Modification of microclimate is a measure factor that can affect growth and productivity of French bean. A study conducted at Ludhiana, Punjab, India to find out the effect of microclimatic modifications on production of French bean. The two experiments were conducted during winter and spring. It comprised of four treatments: open conditions, whole season covered (with polythene sheet), covered at vegetative stage (with polythene sheet) and covered at reproductive stage (with polythene sheet) during winter season. On the other hand, treatments during spring season were: open conditions, whole season covered (with shade net), covered at vegetative stage (with shade net) and covered at reproductive stage (with shade net). Two cultivars; FBP-1 and Kentucky Wonder were used during both the experimental seasons. During both the seasons, high chlorophyll content, more vegetation growth and reproductive was observed that contributed to higher yield. Higher pod yield (167.0 q/ha) was obtained from whole season cover conditions as compared to open conditions (130.7 q/ha) during winter season. However, during spring season overall yield was less due to rise in temperature as compared to winter season but among the studied treatments under spring season, yield was higher (94.8 q/ha) under covered conditions than in open conditions (56.3 q/ha). Apart from this, Agrometeorological indices i.e., GDD (861oC days) and PTU (9133 oC day hour) were also higher under covered conditions during whole season. On the other hand, value of GDD (1027oC day) and PTU (12257oC day hour) was higher under covered condition during reproductive stage only. Besides these, radiation use efficiency was also higher under covered conditions (18.5 g/MJ and 5.2 g/MJ)) during both seasons. The study concludes that among the cultivars, FBP-1 (168.8 q/ha), performed better than Kentucky Wonder (128.7q/ha) and the analysis of growth, yield attributes and agrometeorological indices, revealed that the winter season is the best season as compared to spring season.
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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.

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