Thumbnail Image

Thesis

Browse

2019 - 201912020 - 20231
Reset filters
Author: Shubham Anand × Type: Thesis ×
Reset filters

Search Results

Now showing 1 - 2 of 2
  • Thumbnail Image
    ThesisItemRestricted
    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.
  • Thumbnail Image
    ThesisItemRestricted
    Role of meteorological parameters in incidence of rice brown planthopper
    (Punjab Agricultural University, Ludhiana, 2019) Shubham Anand; 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.