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20235
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Subject: Soil and Water Engineering × End date: 2023 × Start date: 2023 × Type: Thesis ×
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    Standardizing supplemental lighting for improved strawberry cultivation in soilless media under protected cultivation
    (Punjab Agricultural University, 2023) Pardeep Kaur; Mahesh Chand Singh
    A study was carried out at Punjab Agricultural University, Ludhiana to standardize the supplemental lighting for improved strawberry cultivation in soilless media inside a naturally ventilated greenhouse. For supplemental lighting, full spectrum LED grow lights were used. The experimental treatments included three levels of supplemental lighting viz. 235, 169, 132 μmol m-2s-1, and 3 levels of photoperiod viz. 12, 14 and 16-h. The treatments were replicated thrice in a factorial CRD layout. After transplanting, the strawberry plants were fertigated with fresh nutrient solution throughout the growing season using drip irrigation system. Electrical conductivity and pH of the nutrient solution were maintained in the range 1.5-2.7 dSm-1 and 5.5-6.5, respectively. Crop related data (plant height, leaf chlorophyll content, leaf area index, etc.) were recorded at weekly interval. Climatic data (mainly light, temperature and relative humidity) were recorded continuously at a 5-minute interval through development of a low-cost IoT-based real-time climate monitoring system. The fruit related data (fruit diameter, fruit weight, number of fruits and yield per plant) were recorded at the time of each harvesting. The quality parameters viz. titratable acidity, total soluble solids, total sugar, reducing sugar, ascorbic acid and phenol content were analysed twice in the growing season (7th February and 25th March, 2022). The performance of strawberry was significantly affected by time-differential supplemental lighting in terms of its effects on different plant growth parameters, fruit parameters and yield. The supplemental lighting of 132 μmol m-2s-1 for a photoperiod of 16-h recorded the highest fruit yield of 450.0 g/plant with an average value of 408.9 g/plant. The results indicated a significant increase in yield, WUE and FUE of Camarosa strawberry with decrease in supplemental lighting from 235 to 132 μmol m-2s-1 and an increase in photoperiod from 12 to 16-h. The average benefit-cost ratio (B:C) was obtained as 2.35 and 2.27 with and without subsidy, respectively. Supplemental lighting of 132 μmol m-2s-1 for a photoperiod of 16-h resulted in highest B:C value of 2.74 with 50% subsidy and 2.68 without subsidy. Thus, subjecting strawberry plants to light in the range of 362.5-430.6 μmol m-2s-1 including supplemental light of 132 μmol m-2s-1 for about 16 hours in a day is desired to record the optimal plant growth, fruit yield and quality of camarosa strawberry, when cultivated in soilless media inside a naturally ventilated greenhouse.
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    Evaluation of tapering fertigation schedules for dripirrigated potato crop
    (Punjab Agricultural University, 2023) Koundal, Nitesh; Thaman, Sudhir
    A research experiment was carried out at University Seed Farm Ladhowal of Punjab Agricultural University, Ludhiana, during the Rabi season of 2021-2022 to study the effect of basal fertilizer dose and tapering fertigation schedules on growth and yield attributes of the drip-irrigated potato crop. The experiment was laid out in randomized block design (RBD), consisting of seven treatments with three replications. All treatments had the equivalent recommended dose of fertilizer (RDF), i.e. N: P: K :: 150: 50: 50 kg ha-1. The treatments comprised seven fertilizer application schedules, viz. T1: FYM + 25% RDF as basal + fertigation in 18 tapering splits with 75% RDF, tapering at a difference of 0.05X; T2: FYM + 25% RDF as basal + fertigation in 18 tapering splits with 75% RDF, tapering at a difference of 0.1X; T3: FYM + 25% RDF as basal + fertigation in 18 tapering splits with 75% RDF, tapering at a difference of 0.15X; T4: FYM + fertigation in 18 tapering splits with 100% RDF, tapering at a difference of 0.05Y; T5: FYM + fertigation in 18 tapering splits with 100% RDF, tapering at a difference of 0.1Y; T6: FYM + fertigation in 18 tapering splits with 100% RDF, tapering at a difference of 0.15Y; T7: FYM + fertigation with 20 % RDF in 7 equal splits + 80% RDF in 13 equal splits (Control). X and Y are 18 equal splits of 75% and 100% RDF, respectively. The same irrigation depth was applied to all treatments on the basis of the Penman-Monteith method. The data of the field experiment was analysed statistically using CPCS1 software of the Department of Mathematics and Statistics, PAU, Ludhiana. Different tapering fertigation schedules had a significant impact on yield parameters, viz., average tuber weight and tuber yield per plant. The treatment T2 recorded the highest average tuber weight (28.4 g) and tuber yield per plant (317.6 g). Tuber yield in treatment T2 (24.4 t ha-1) recorded significantly higher tuber yield than other treatments except for treatment T1. The tuber yield in treatment T2 was 15.2% higher than in treatment T7 (control).
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    Land Use and Land Cover Change Analysis in District Shaheed Bhagat Singh Nagar of Punjab Using Geospatial Technology
    (Punjab Agricultural University, 2023) Sohal, Jaskaran Singh; Kaushal, Arun
    Land use and land cover (LU/LC) is observed to be the primary factor of environmental change on a worldwide scale. Timely and accurate information on LU/LC is very important for efficient planning and management activities. The present study on “land use and land cover change analysis in district Shaheed Bhagat Singh Nagar of Punjab using geospatial technology” was carried out at the Department of Soil and Water Engineering, PAU and PRSC, Ludhiana from 2021-2023 to classify LU/LC and to analyse decadal change in the study area from year 2012-2022. Satellite data of IRS P6 LISS-III (2012 , 2022) and IRS LISS-IV (2022) were analysed for LU/LC mapping using visual interpretation techniques. The study area was divided into seven LU/LC classes i.e.: agriculture, built-up, waterbody, forest/tree clad area, riverine sand, algae bloom and fallow land /barren land/waste land in which agriculture covers maximum while riverine sand covers minimum area. In decadal change the alterations encompass positive trends such as increased agricultural area (31.29 %), as well as negative trends including decreased algae bloom (59.82 %). Overall accuracy for LISS-III 2012, LISS-III 2022 and LISS- IV 2022 were 88.3 %, 86.66 % and 93.3 %, respectively with kappa coefficient value as 0.86, 0.83 and 0.91 , respectively. Hotspot areas with major changes were seen in Block Nawanshahr with major increase in built-up area, as well as in Block Saroya and Balachaur of study area with major decrease in Forest area. Highresolution data of IRS LISS-IV gives better accuracy as compared to IRS P6 LISS-III.
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    Developing Artificial Intelligence Algorithm for Identification and Classification of Abiotic Stresses in Maize
    (Punjab Agricultural University, 2023) Goyal, Pooja; Sharda, Rakesh
    Cereal crops like maize are seriously affected by the abiotic plant stresses, which cause substantial reduction in crop yields. New age Artificial Intelligence (AI) and Deep Learning (DL) techniques offer a non-invasive and a practical way for precise detection of these stresses in real time. The present study was planned to develop an AI-based algorithm for identification and classification of abiotic stresses in maize. Three consecutive experimental trials i.e. spring maize (2021), kharif maize (2021) and spring maize (2022) were conducted at the Research Farm of Department of Soil and Water Engineering, PAU, Ludhiana in a split-plot design with varieties in main plot and fertigation treatments in sub-plot. The subplots covered three types of nutritional deficiencies of nitrogen (N), phosphorus (P) and potassium (K), one water deficit plot and one plot with 100% irrigation and fertigation. Data regarding the plant growth and yield attributes were observed at different growth stages and a total of 6035 RGB images were captured throughout the crop growing seasons. These images were classified into five classes according to stress levels to build a DL-based Convolutional Neural Network (CNN) model. Two classification models were built, the first was a binary classification model for drought stress detection, and the second was a multi-class classification model to classify all the abiotic stresses. Further, 2 modelling approaches i.e. custom-CNN model and a transfer learning (TL) approach using 5 state-of-the-art architectures were used. Both ResNet50 and EfficientNet121 models performed the best, achieving a test accuracy and F1-score of 99.26% and 99.22% respectively in case of binary classification model. The ResNet50 model also achieved the highest average weighted accuracy and F1-score of 98.36% and 98.35% respectively for overall abiotic stress detection in maize. The custom-CNN model, with much lesser number of parameters compared to the transfer-learned networks, achieved an acceptable F1-score of 98.44% and 97.04% for drought and abiotic stress classification respectively. Therefore, the custom-CNN model was recommended for real-time abiotic stress assessment in maize crop especially on resource constrained devices.
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    Assessment of groundwater vulnerability in Muktsar district of Punjab using GIS based DRASTIC model
    (Punjab Agricultural University, 2023) Karmakar, Saikat; Garg, Sunil
    Groundwater serves as a vast reserve of freshwater. The geogenic processes within the Earth's crust, combined with the infiltration of water through the surface, result in notable alterations in the quality of groundwater reserves. To effectively handle groundwater resources, assessing the vulnerability of aquifers through prediction and monitoring proves to be a valuable approach. The aim of this study was to employ DRASTIC model in GIS environment for estimating the groundwater vulnerability in Muktsar district of Punjab, which covers almost 2,615 km2 area. In this region, the vulnerability index of groundwater was modelled using both primary and secondary datasets, considering various input variables in ArcGIS software. The calculated DRASTIC index value ranged between 141 to 192 which were further classified in low, medium and high vulnerability classes. Results showed that the high vulnerability was at the northern part of the district with area share of 8.19%. Map removal sensitivity analysis was performed which showed depth to water table as the most influential parameter in vulnerability assessment with mean variation index of 2.63% followed by topography, net recharge and aquifer media. The weights of the model parameters were modified based on the variation indices and a modified DRASTIC model was obtained. The validation test revealed that the output of the modified model was better correlated with both historical and current Total Dissolved Solidss (TDS) concentration map of the study area compared to the conventional model thus making it preferable to assess groundwater vulnerability in the study region.