Thesis

Browse

Search Results

Now showing 1 - 9 of 22

Restricted
Effect of defoliation and row direction on microclimate and diseases in raya (Brassica juncea)
(Punjab Agricultural University, Ludhiana, 2020) Dharampal; Dhaliwal, L.K. Dhaliwal
The research experiment entitled “Effect of defoliation and row direction on microclimate and diseases in raya” was conducted at Research Farm, Department of Climate Change and Agricultural Meteorology, Punjab Agricultural University, Ludhiana during rabi 2019-20. The experiment was conducted with two varieties (PBR 91 and PBR 357), two row direction (North-South and East-West) and three defoliation treatments (1st defoliation, 2nd defoliation and control means no defoliation) in factorial-split plot design with four replications. The Package of Practices as recommended by PAU was followed for raising the crop. The PAR intercepted was higher in variety PBR 357 as compared to PBR 91 due to higher leaf area index. Maximum PAR interception was recorded under North–South direction compared as to East–West direction. In defoliation treatments, PAR interception was maximum in the defoliated plots than control. High relative humidity was observed in E-W direction as compared to N-S direction. Among the modification treatments the first defoliation (at flowering stage) proved very effective against the alternaria blight as well as white rust. The disease severity was low under defoliation treatments than control. Alternaria blight severity was higher in E-W row direction and lower in N-S direction. Similarly white rust severity was higher in E-W row direction and lower in N-S direction. Variety PBR 91 showed higher area under disease progress curve (AUDPC) as compared variety PBR 357 for alternaria blight and white rust. Among different defoliation treatments, the area under disease progress curve (AUDPC) was maximum in control treatment followed by 2nd defoliation and 1st defoliation. Seed yield was more (20.4 q/ha) in N-S direction compared to E-W direction (18.2 q/ha). Variety PBR 357 variety gave higher (19.7 q/ha) yield than PBR 91 (18.9 q/ha). Under the modification treatment defoliated crop (Defoliation 1) recorded the higher yield (20.2 q/ha) than control (18.4 q/ha).
Open Access
Impact of climate change on productivity of wheat and cotton in south west Punjab
(Punjab Agricultural University, Ludhiana, 2020) Ramandeep Kaur; Gill, K.K.
The study entitled "Impact of climate change on productivity of wheat and cotton in south west Punjab" was conducted to assess the shift, variation and deviation in climate of Punjab during 37 year (1981-2017) in Bathinda and 17 years (2001-2017) in Faridkot using correlation regression techniques and estimating the possible effects of climate and technology on the productivity of cotton (Gossypium spp.) and wheat (Triticum aestivum L.) crops. Three different statistical models i.e. Basic Model (Model 1), Modified Model (Model 2) and SPSS Software (Model 3) were used. The results showed that in case of maximum temperature at Bathinda, more variation has been found in fourth decade as compared to others and at Faridkot the variation was observed more during second pentad. More variation in minimum temperature has been found in fourth decade and third pentad at Bathinda and Faridkot, respectively. In case of rainfall at Bathinda, more variation has been found in fourth decade as compared to others. At Faridkot, the variation was more during second pentad. GStat was used for the development of multiple regression equation and correlation was developed for the sensitive crop periods in model I or basic model. The basic model is then modified through inclusion of an assumed composite index while other independent variables are kept constant. SPSS software was used as a model for wheat and cotton for forecast analysis. The use of basic model (model 1) has shown that the maximum temperature during 2nd and 3rd weeks of wheat growing season had negative effect on wheat yield at Bathinda district. At Faridkot, minimum temperature during 2nd week showed negative effect on wheat yield. The three models (i.e. basic model, modified model and SPSS software) predicted wheat and cotton yield and the error per cent of all these models was remained 30 per cent for two districts (Faridkot and Bathinda) of south west Punjab. For American cotton and desi cotton grown in Bathinda and Faridkot districts, SPSS software (model 3) was best fit as R2 value was highest for American cotton by 83 % ( Bathinda district) and 97% (Faridkot district), whereas, for desi cotton it was 82 % and 96 % for Bathinda and Faridkot district, respectively. For wheat grown in Bathinda, SPSS software was best fit as R2 value was 97 % while wheat grown in Faridkot, modified model (model 2) was best fit (95 %).
Open Access
Analysis and prediction of daily climate variables in central Punjab using machine learning and geospatial techniques
(Punjab Agricultural University, Ludhiana, 2020) Bora, Sony; Kingra, P.K.
The climate science community faces the signiﬁcant challenge of dealing with a continuously changing observing system. Huge datasets offer a high degree of statistical power coupled with untapped opportunities for data miners. The advent of machine learning has made data mining facile by providing algorithms that autonomously identify patterns with minimal human interference. For the trend analysis, the Sen’s slope for daily maximum air temperature, daily minimum air temperature, daily maximum soil temperature, daily minimum soil temperature, daily morning relative humidity, daily evening relative humidity, daily open pan evaporation and daily sunshine hours of all the months for 50 years, from 1970 to 2019 were calculated and observed highest slope magnitude on 20th March (0.093 oC/year), 18th May (0.127 oC/year), 15th April (0.167 oC/year), 2nd January (0.061 oC/year), 14th May (0.345 percent/year), 18th January (0.789 percent/year), 2nd May (-0.104 mm/year) and 2nd January (-0.159 hr/year) respectively. It concluded that the variability in maximum and minimum air temperature will cause decrease in yield by 7.17% (405 Kg/ha) and 4.86% (262 Kg/ha) respectively by 2050. To calculate LST the archive satellite data of Landsat-5 TM for the years 1994, 1996, 1998, 2008, 2010, Landsat -7 ETM+ for the year 2000, 2002 and Landsat -8 for the year 2014, 2016, 2018 were used. The air and soil temperature can be predicted from LST by using equation Ta = 0.775 Ts and TS = 0.884 Ts respectively (where Ta is air temperature, TS is soil temperature and Ts is land surface temperature). A good correlation was observed between LST and AET for maize (R² = 0.856) and wheat (R² = 0.897). The big climate data was mined using hierarchical clustering. Decadal comparison from 1970 – 2019 was carried out between mean maximum and minimum, soil and air temperature and pan evapotranspiration with soil and air temperature using Regression analysis technique wherein, a linear and an exponential relationship was observed respectively.
Restricted
Formulation of crop weather calendar for sunflower (Helianthus annuus L.) under Punjab conditions
(Punjab Agricultural University, Ludhiana, 2019) Jaspal Singh; Sidhu, Prabhjyot Kaur
The field experiment was conducted during rabi 2018 at the Research farm, Department of Climate Change and Agricultural Meteorology, PAU, Ludhiana to generate phenological field data for formulation of crop weather calendar under Punjab conditions. The sunflower was sown with four thermal environments; early sown (T1: 5th January), normal sown (T2: 15th January and T3: 25th January) and late sown (T4: 4th February) using two cultivars (PSH 996 and PSH 1962). The experiment was laid out in split plot design with four replications, keeping thermal environments in main plot and two cultivars in sub plot. The sunflower crop sown during 5th January took more days to complete their life cycle as compared to that sown during 15th January followed by 25th January and 4th February. Among the sowing dates, LAI, dry matter accumulation, PAR interception, radiation use efficiency (RUE) and plant height were higher and extinction coefficient was lower in early sown crop as compared to late sown crop which may be due to profuse vegetative growth. Among the yield attributes characters, early sown (T1: 5th January) and normal sown (T2: 15th January) sunflower crop produced higher number of seed / head, seed yield, stalk yield, biomass yield, but 1000 seed weight. Then for formulation of crop weather calendar the weekly and monthly normal of different historical metrological parameters was computed from daily weather data for Ludhiana, Ballowal Saunkhri and Amritsar, rabi 2003-2017. These climatic normals were used for comparing the actual data to study the effect of different meteorological parameters on yield of sunflower crop. The analysis of meteorological parameters at different locations revealed that temperature above normal in the months of March for continuous period is not favourable for sunflower productions. Heavy rainfall in the months of April and May at grain filling stage with below normal sunshine hour have directly reduced the sunflower productivity. The actual meteorological data of high yield crop years over the past 15 years were analysis for different growth stages of sunflower to work out the critical ranges of meteorological parameters. Crop weather calendar were formulated for sunflower 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. Further weather based “Thumb Rule models” using the weekly meteorological data were formulated for predicting the yield of sunflower at 3 locations in Punjab state.
Restricted
Effects of microclimatic modifications on phenological development and seed cotton yield using CROPGRO-cotton model
(Punjab Agricultural University, Ludhiana, 2019) Dhir, Abhishek; Raj Kumar Pal
The Present study entitled “Effects of microclimatic modifications on phenological development and seed cotton yield using CROPGRO-cotton model” was carried out at two Locations viz., Punjab Agricultural University (PAU) Regional Research Station, Bathinda, (latitude 30°58‟N, 74°18‟E longitude and altitude 211m above mean sea level) and Faridkot (latitude 30°40‟ N, longitude 74°44‟ E and altitude 200m above mean sea level) during the kharif 2018. The soil of the both the experimental sites is sandy loam. The experiments were laid out with Bt cotton hybrid RCH 773 BGII and sown at three dates i.e. April 30, May 15 and May 30 with two row orientations (North-South: N-S and East-West: E-W) and three plant spacings (67.5cm×45.0cm, 67.5cm×60.0 cm and 67.5cm×75.0cm) in factorial split-plot design with three replications. The study indicated that the days taken to achieve various phenophases like emergence, first square, anthesis, boll opening and maturity (DAS) were found to be decreased with delayed sowing and recorded more days to attain various phenophases with 30th April sown crop. Delay in sowing from April 30 to May 15 reduced the cotton yield by 6.0% at Bathinda and by 13.1% at Faridkot and further delayed sowing from May 15 to May 30 reduced the seed cotton yield by 17.4% and 8.7% at Bathinda and Faridkot, respectively. Moreover, delay in sowing time of one month from April 30 to May 30, caused reduction in seed cotton yield by 22.36% and 20.37% at Bathinda and Faridkot, respectively. Besides, crop sown in East–West row orientation reported highest seed cotton yield than North–South direction at both the study regions. Similarly, among plant spacings, wider plant spacing of 67.5cm×75.0cm produced more seed cotton yield due to proper aeration and light distribution within the canopy. Among weather parameters, higher variation was observed between sowing dates, while lesser variation was recorded among row orientations and plant spacings. Furthermore, the model output in terms of seed cotton yield was found in good agreement over observed having higher value of R2 (0.75 for Bathinda and 0.83 for Faridkot) and lesser RMSE (253.8 kg ha-1 for Bathinda and 198.3 kg ha-1 for Faridkot). Similarly, simulated phenology of the crop was also shown close proximity over observed value having R2 value of 0.49, 0.51 and 0.61 at Bathinda and 0.59, 0.43 and 0.87 at Faridkot for emergence, anthesis and maturity. Hence, the CROPGRO-cotton model can be used as research tool for the prediction of cotton phenology and yield of the crop.
Open Access
Role of meteorological parameters in incidence of rice brown planthopper
(Punjab Agricultural University, Ludhiana, 2019) Anand, Shubham; Dhaliwal, L. K.
A field experiment was conducted at the Research Farm, Department of Climate Change and Agricultural Meteorology, PAU, Ludhiana during kharif 2018. Two rice varieties (PR 121 and PR 126) were transplanted on 20th June and 30th June. Variety Pusa Basmati 1121 was transplanted on 5th July and 15th July under three spacings (25 cm x 12 cm, 20 cm x 15 cm and 30 cm x 10 cm). The experiment was laid out in Split-Split Plot Design for rice crop and Factorial-RCBD Design for basmati rice in four replications. The micrometeorological data on photosynthetically active radiation (PAR) and relative humidity were recorded at different phenological stages. The periodic biometric observations on leaf area index were recorded. At harvesting, the yield and yield contributing characters (number of effective tillers, number of grains/panicle, 1000-grain weight, grain yield etc.) were recorded. The results indicate that PAR interception was higher under wider spacing (30 cm x 10 cm) followed by closer spacings (20 cm x 15 cm and 25 cm x 12 cm). The higher relative humidity was recorded in closer spacing (25 cm x 12 cm) than wider spacing (20 cm x 15 cm and 30 cm x 10 cm). Leaf area index was higher in 30 cm x 10 cm spacing followed by 20 cm x 15 cm and 25 cm x 12 cm spacing. The higher grain yield (58.65 q/ha) was recorded in rice varieties transplanted under wider spacing (30 cm x 10 cm) in comparison to closer spacings of 20 cm x 15 cm (55.70 q/ha) and 25 cm x 12 cm (53.40 q/ha). In Pusa Basmati 1121, grain yield was higher (30.57 q/ha) in 30 cm x 10 cm spacing followed by 20 cm x 15 cm (29.25 q/ha) and 25 cm x 12 cm (26.89 q/ha) spacings. The peak incidence of brown planthopper incidence was observed in 25 cm x 12 cm spacing (3.1 brown planthopper population/hill) as compared to 20 cm x 15 cm spacing (2.9 brown planthopper population/hill) and 30 cm x 10 cm (2.4 brown planthopper population/hill).The brown planthopper incidence data from 2014 to 2016 and 2018 indicated that the highest incidence at Ludhiana was observed in 2016 and the lowest in 2018. Correlation and regression analysis were carried out between different meteorological parameters and brown planthopper incidence. Using brown planthopper data (in field) of different years stepwise regression models were developed. Minimum temperature and relative humidity (morning and evening) were found to be important parameters in incidence of brown planthopper. Agroclimatic indices viz. growing degree days (GDD) and humid-thermal ratio (HTR) were calculated for brown planthopper. Agroclimatic indices based model was developed using brown planthopper incidence data from 2014 to 2016. RHe/Tmax and RHe/Tmin based model gave lowest error (%) when validated with 2018 brown planthopper data. According to present study, the favourable temperature for brown planthopper incidence was 30.2-33.4 oC (maximum temperature) and 20.6-22.5 oC (minimum temperature) while relative humidity was 86-90 per cent in the morning and 48-60 per cent in the evening. Hot, cloudy and humid conditions are conducive for brown planthopper multiplication. The crop-weather-brown planthopper-calendar was prepared on the basis of four-year brown planthopper data. This calendar can be used in agro-advisory for giving forewarning of brown planthopper to the farmers.
Open Access
Studying the impact of climate and technology variables on maize productivity in Punjab using GIS
(Punjab Agricultural University, Ludhiana, 2019) Gill, Gurpreet Kaur; Som Pal Singh
Climate change has resulted in the variation of temperature and precipitation, affecting the crop production and productivity. A study therefore has been planned to examine the impact of climate and technology variables on maize productivity in Punjab using GIS. Long-term data (1971-2017) on maize yield, fertilizer consumption and maize gross irrigated area was collected from statistical abstracts of Punjab and long-term climatic data on maximum temperature, minimum temperature and rainfall during the maize growing period was collected from Department of Climate Change and Agricultural Meteorology, Punjab Agricultural University, Ludhiana, different research stations of PAU, India Meteorological Department, New Delhi and different websites. The maize yield increased in all the districts and the rate of increase was highest at Patiala (74.3 kg year-1). Significant increase has been observed in minimum temperature during maize growing period in all the maize growing districts, whereas no significant trend has been observed in maximum temperature and rainfall, although large year to year variations have been observed. Significant increase in fertilizer consumption in all the districts of the state was observed except Amritsar, where no trend was observed. Significant decrease has been observed in maize gross irrigated area in all the maize growing districts except Hoshiarpur and Roopnagar where the trend increased. The Mann-Kendall test results revealed that long term (1971-2017) seasonal variability showed the increase in minimum temperature in Gurdaspur, Hoshiarpur, Kapurthala and Roopnagar @ 0.04°C year-1 and increase in maximum temperature in Hoshiarpur, Kapurthala, Patiala and Roopnagar @0.03°C year-1. Temporal seasonal variability showed the decrease in maximum temperature in Jalandhar @ -0.14°C year-1 and increased in Patiala @ 0.10°C year-1 during 2001-2010. Increase in minimum temperature in Gurdaspur @ 0.37°C year-1 was observed during 2001-2010. Stepwise regression showed that 95.3 per cent of the variance in maize yield was explained by minimum temperature and 2.8 per cent by fertilizers. Inverse distance weighted method in Arc GIS 10.4 was used to show the spatial variability in maize productivity, technology variables and weather parameters during its growing period.
Restricted
a Study of micro-Climate and crop response of soybean (Glycine max L.) Using a Iine source sprinkler system
(Department of Agricultural metrology College of Agriculture PAU, Ludhiana, 1995) Kaur, Pavneet; Hundal, S. S
Restricted
Spatio-temporal variability in evapotranspiration and moisture availability in different agroclimatic regions of Punjab
(Punjab Agricultural University, Ludhiana, 2019) Aatralarasi S; Kingra, P. K.
Water scarcity is faced by the state of Punjab due to depletion of groundwater resources. This situation urges more detailed study, in terms of region-wise water availability over long-term period. A number of studies have been conducted in the past examining the supply side of hydrological cycle i.e precipitation. But the current study deals with demand side i.e reference evapotranspiration (ETO), a parameter directly relating climate change in terms of water requirements. In addition to this, two other parameters viz. Aridity Index (AI) and Moisture Index (MI) were also studied. Computation of ETO was done by HS method, MI by Krishnan and Singh method and AI by UNESCO method. Trend analysis was studied with Mann- Kendall test and classical statistical procedures. Spatial interpolation was done in Arc GIS 10.4 software. The results concluded that annual ETO increased in north-east region and south-west @ 1.46 mm year-1 and 0.97 mm year-1 respectively. Rabi season ETO increased in north-east region @ 1.27 mm year-1. Annual MI was observed to be dry during first decade (1971-80), there was increase in water availability during the next two decades and again dry from 2000 onwards. Annual and seasonal AI values were observed to be highest in north-east followed by Central and lowest in south-west. A critical analysis of the study indicated decreased ETO till 2000 contributed to higher AI & MI values denoting more moisture availability till 2000 and decreased thereafter annually as well as seasonally due to higher ETO. The results also indicated spatial variability in moisture availability in the state from north-east to south-west. There was prominent difference in moisture ranges during earlier decades, but this difference was reduced in recent decades which might be due to huge impact of climate change in the north-east region. To conclude, south-west region faced severe water crisis even from earlier decades, but under recent conditions of climate change north-east region is also coming under the stress situation. This alarms the need for judicious water management in all regions of state.

Thesis

Browse

Thesis Type

Type

Author

Date

Subject

Search Results