The Indian Society of Agricultural Engineers
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Identification of Sensitive Parameters for Runoff Simulation in Santrod Watershed Using QSWAT
No full textIn this study, Soil and Water Assessment Tool (SWAT) was employed in conjunction with remote sensing and geographic information system to simulate runoff in Santrod watershed, located in Mahi River basin, in the north-west region of India. The model calibration was performed on a monthly time-step for 2000-2014 period with an initial 2-year warm-up period (1998-1999). Following calibration, the model was validated using observed runoff data for 2015-2019. Model calibration and parameter sensitivity analysis were performed using automatic calibration feature available in the SWAT Calibration and Uncertainty Procedures (SWAT-CUP) software. Sensitivity analysis showed that hydrological processes of the watershed are highly influenced by soil evaporation compensation factor, threshold depth for shallow aquifer and runoff curve number factor. The model performance was found good during calibration with values of coeffi cient of determination (R²) as 0.91, Nash-Sutcliffe efficiency (NSE) as 0.91, percent bias (PBIAS) as 7.2 and root mean square error to standard deviation ratio (RSR) as 0.3. Similarly, the model performance was found satisfactory during validation with values of R², NSE, PBIAS and RSR as 0.86, 0.89, 8.4 and 0.24, respectively. Findings of this study provide valuable insightsfor policymakers, water resource managers and environmental planners. The findings can further guide in sustainable water allocation strategies and watershed conservation efforts, to ensure long-term health of Santrod watershed and support in effective water management practices in the region
Safety in Agriculture for Reducing Health Hazards: Analysing Prevalence and Prevention Strategies
No full textHealth hazards and injuries are common for farm workers working in agricultural activities and are caused by many factors, such as humans, machines, or environmental factors. Understanding the magnitude of these hazards is essential for effective policymaking, public health interventions, and sustainable agricultural development. Incidents related to agricultural activities that occurred during the one-year period (July 2021–June 2022) were recorded from 20 villages each in three districts of Sangrur, Shaheed Bhagat Singh Nagar, and Ferozepur using a bilingual mobile application. Data reliability was ensured through field investigator validation and cross-checking with secondary records. A total of 226 agricultural incidents, including 15 fatalities were reported. Within the category of farm machinery, the reported incidence rates included 38 fatal and 495 non-fatal cases per 100,000 workers, resulting in a total injury rate of 533 per 100,000 workers. Incidents involving hand tools such as spades, sickles, and axes accounted for a total non-fatal incidence rate of 106 per 100,000 workers. Additionally, incidents from other sources, including snake bites and chemical exposures, showed a significantly higher total incidence rate of 772 per 100,000 workers, comprising 51 fatal and 721 non-fatal cases. Human factors were identified as the leading cause of agricultural incidents, accounting for 64.60% of the cases, followed by machine factors (19.03%) and environmental factors (16.37%). To improve agricultural safety and reduce incidents, key interventions must include the mandatory installation of Roll-Over Protective Structures (ROPS) on all tractors, enforcement of seat belt usage, and proper equipping of tractor-trailers with functional brakes, turning indicators, rear lights, and fluorescent Slow-Moving Vehicle (SMV) emblems
Analysis of Export and Import of Agricultural Machinery (2024-25)
No full textThe export and import data for agricultural machinery during April 2024 to March 2025 highlights India’s position as a major exporter of tractors but also reveals a dependence on imports in several other machinery categories. This analysis provides insights into the performance of key machinery segments
‘विकसित भारत’ के मूल में कृषिः सतत और समावेशी विकास को बढ़ावा
No full text‘विकसित भारत’ के मूल में कृषिः सतत और समावेशी विकास को बढ़ाव
Performance Evaluation and Optimization of a Power-Operated Peeling-cum-Cutting Machine for Shatavari (Asparagus Racemosus) Roots Using Response Surface Methodology
No full textShatavari (Asparagus Racemosus), a key Ayurvedic medicinal herb with tuberous roots, has a diverse range of therapeutic applications. The unit operations involved in processing of Shatavari involves labour intensive and time-consuming tasks such as manual washing, peeling, and cutting of its roots. Such operations are contamination prone too. Thus, a power-operated peeler-cum-cutter was developed to overcome these limitations. This study evaluated its performance through an optimization of process parameters. Parametric optimization was carried out using the Response Surface Methodology (RSM) with an optimal custom design that correlates independent parameters viz., batch load, motor speed, and peeling surface with dependent parameters, viz., washing efficiency, peeling efficiency, cutting efficiency, peel ratio, throughput capacity, and overall efficiency. Analysis of variance (ANOVA) was employed to verify the statistical reliability of the model. The best operating condition was obtained with a metal peeling surface, motor speed of 250 rpm and a batch load of 2 kg. Under these conditions, the optimum performance values achieved were 97.60% washing efficiency, 94.71% peeling efficiency, 97.57% cutting efficiency, a peel ratio of 0.068, a throughput capacity of 1.51 kg h-1, and an overall efficiency of 88.93%. The study revealed that washing efficiency, peeling efficiency, cutting efficiency, throughput capacity, and overall efficiency increased with motor speed and batch load up to optimal levels. In contrast, peel ratio followed a U-shaped trend, initially decreasing and then rising beyond the optimum speed. These findings establish optimal operating conditions for peeler-cum-cutter, leading to higher efficiency and lower processing costs, highlight the machine’s potential for small-scale applications and future adaptability for other medicinal roots
Optimization of Cryogenic Grinding Parameters for Ashwagandha Roots
No full textThis study aimed to optimize the cryogenic grinding process of Ashwagandha (Withania somnifera) roots, a medicinal herb used in the Indian subcontinent, to preserve quality by minimizing thermal degradation. The effect of moisture content, grinding temperature, and grinder speed on Ashwagandha powder quality was evaluated. Response Surface Methodology (RSM) with a Box–Behnken design guided the experiments. The optimization sought to reduce particle size and colour difference while retaining essential oil and total phenolic content. The results indicated that the optimal conditions for grinding were 6.58% moisture content, -119°C temperature, and 9477 rpm grinder speed, with a desirability of 0.92. The resulting particle size was 0.381 mm, with 43.99 mg 100g-1 of essential oil, 394.77 mg of total phenols (GAE 100g-1), and specific energy consumption of 1.596 kWh kg-1. Statistical analysis validated the optimized conditions. Thus, this study provides valuable information for the production of high-quality Ashwagandha powder for pharmaceutical applications. These optimized conditions provide a foundation for pilotscale trials and technoeconomic assessments aimed at industrial adoption
Improving Water Productivity and Soil Fertility in Mustard (Brassica juncea L.) through Deficit Irrigation and Nitrogen Management in Semi-arid Region
No full textA field experiment on deficit irrigation with nitrogen management in mustard was conducted at Anand, Gujarat, India during 2019-20 and 2020-21. Three main irrigation treatments based on IW/CPE (irrigation water/cumulative pan evaporation) ratio, namely, I1 (0.6 IW/CPE), I2 (0.8 IW/CPE), and I3 (1.0 IW/CPE) and five sub-treatments based on nitrogen levels, namely, N1 [100% recommended dose of nitrogen (RDN) through chemical fertilizer], N2 (100% RDN through vermicompost), N3 (75% RDN chemical fertilizer + 25% RDN vermicompost), N4 (50% RDN chemical fertilizer + 50% RDN vermicompost), and N5 (25% RDN chemical fertilizer + 50% RDN vermicompost + bio N-P-K consortium @ 1.0 L ha-1) were considered. The experiment followed a split-plot design with three replications. Pooled data analysis revealed that available soil phosphorus was significantly higher in treatment I3, while higher microbial counts were observed under treatment I2. Treatment N2 had a significant effect on soil available nitrogen (28 kg ha-1) and microbial count (130×107 cfu g-1). In treatment N2, soil quality parameters of pH and electrical conductivity (EC) showed a decrease, while organic carbon improved. On the other hand, available phosphorus and potassium improved in treatment N5. Interaction between irrigation levels and nitrogen treatments was found significant in case of soil available phosphorus. Also, a significant positive correlation was found between microbial count and available nitrogen content in the soil as revealed from the values of correlation coefficients for first year (71.32%), second year (76.9%) and pooled data (73.52%). Water productivity was found higher in treatments I1 (0.68 kg m-3) and N4 (0.68 kg m-3). This study concluded that optimization of irrigation schedule and adoption of balanced nitrogen management practices are essential for conserving resources, acclimatizing, enhancing soil health, and ensuring sustainable production in the long term
Development and Performance Evaluation of a Power-Tiller-Operated Long L-Shaped Blades for Ratoon Management
No full textThis study presents development of cost-effective sugarcane stubble shaving tynes integrated with a power tiller (SSTIPT), and evaluates their performance and techno-economic feasibility as compared to the existing stubble shavers in market. The low cost long L-shaped blades for ratoon management integrated with existing power tiller was developed considering minimum cutting energy required for cutting sugarcane stem with effective cutting of sugarcane (minimum cutting index). The blade was designed using optimum angles i.e., a bevel angle of 15°, an approach angle of 23°, and shear angle of 0°, with its thickness tapering from 10 mm at the integrated end (mounted on the tiller shaft) to 5 mm at the cutting edge. The maximum stubble shaving efficiency of developed SSTIPT was found to be 97.2% with 1.45 km h-1 forward operating speed of power tiller and four number of blades. The benefit-cost ratio of developed SSTIPT, and tractor-operated vertical-axis sugarcane stubble shaver (VASSS) and sugarcane stubble mulcher-cum-shaver (MSCMS) was found to be 0.81, 1.15 and 1.41, respectively. Though the benefit-cost ratio of SSTIPT is lower as compared to VASSS and MSCMS, but the construction cost of the SSTIPT is lower than that of the VASSS and MSCMS, making it a more suitable and economical option for small and marginal farmers who own a power tiller. The tractor operated VASSS and MSCMS were economical to provide custom hiring service for marginal and large field holding farmers
High-Resolution Spectral Reflectance-based Crop Classification and Chlorophyll Content Estimation Using Machine Learning
No full textPrecision agriculture progressively relies on remote sensing (RS) technologies to enhance crop classification and monitoring. Among various RS platforms, spectroradiometer offers the highest spectral precision, making them essential for validating the accuracy and performance of other RS methods. Each crop exhibits a unique spectral signature that corresponds to its biophysical characteristics. This spectral information plays a crucial role in accurately classifying crop types and assessing their health status, including water and nutrient availability. Specifically, evaluating crop chlorophyll content enables effective nitrogen management and yield optimization. This study focuses on collecting spectral data using a spectroradiometer (350-1050 nm) at a height of 30 cm above the crop canopy from eight crops, i.e., rice, finger millet, cotton, sunflower, sweet corn, broccoli, cauliflower, and brinjal, classifying the collected data, and measuring chlorophyll content using a Soil Plant Analysis Development (SPAD) meter and predicting the same using key spectral bands and machine learning (ML) techniques. Six supervised ML algorithms, i.e., Random Forest (RF), Support Vector Machine (SVM), K-Nearest Neighbor (KNN), Light Gradient-Boosting Machine (LGBM), Extreme Gradient Boosting (XGBoost), and Multi-Layer Perceptron (MLP) were employed for crop classification. The feature selection process revealed that the spectral range of 710-750 nm is the most significant for crop classification. The MLP model achieved the highest accuracy of 97% during training, 93% in testing, and 85% during validation stage, outperforming other ML classifiers. For chlorophyll content prediction, the RF demonstrated the best performance, with coefficient of determination values of 0.92 for training and 0.72 for testing stage. The ML-based framework, developed in this study, can be applied to various RS platforms, including satellites and unmanned aerial vehicles (UAVs), for crop classification and prediction of chlorophyll content. The developed modelling framework would assist government agencies and policymakers in identifying crop types accurately, enhancing agricultural planning, and optimizing resource allocation to support sustainable on-farm practices
Protected Horticulture: Opportunities and Challenges
No full textIntroduction Global vegetable production has reached approximately 1.17 billion metric tons, marking a significant increase over the past decade. India ranks as the second-largest producer of vegetables after China, contributing around 212.9 million metric tons from 11.11 million hectares, with an average yield of 18.47 tons per hectare. Over the last two decades, India has emerged as a major player in the global horticulture sector often referred to as the horticultural (fruit and vegetable) basket of the world. The country has achieved a record high horticultural production of 355.48 million metric tons, showcasing its growing dominance and potential in this sector