Journal of Agricultural Engineering (India)
The Journal of Agricultural Engineering (India) is a peer-reviewed Journal and publishes interdisciplinary basic and applied research manuscripts of engineering and technology to address the problems of agricultural, food, and biological systems. The journal publishes papers of both theoretical and applied nature, with a special focus on experimental research, new design criteria, mathematical modelling and innovative approaches relating to all fields of agricultural engineering and technology. This journal uses double-blind review process.
Indian Society of Agricultural Engineers
Specific Torque Requirement of Different Tractor PTO Operated Active Tillage Machinery
Section: Regular Issue Categories: Farm Machinery and Power Engineering (FMPE) Keywords: active tillage implements, regression analysis, specific PTO torque, torque modelling, tractor-implement matching The study aims to evaluate and compare the specific Power Take-Off (PTO) torque requirement of four active tillage implements - rotavator, double rotor rotavator, PTO-driven disc tiller, and power harrow under varying forward speeds and tillage depths. The findings intend to assist in optimal tractor-implement matching, enhance energy efficiency, and inform design improvements in tillage machinery. Field experiments were conducted on sandy loam soil using a New Holland 4010 tractor at three speeds (2.2, 3.6, and 4.8 km h-1) and depths (80, 100, and 120 mm). PTO torque was measured using a torque and power monitoring system. The experiment was laid out in a split-plot design with three replications. Statistical analysis was conducted, and regression models were developed using non-linear least squares optimization. Results revealed that specific PTO torque requirement significantly increased with both forward speed and tillage depth (p < 0.01). Among the implements, the rotavator exhibited the lowest average specific torque requirement (133.9 N-m m-1), while the power harrow and PTO-driven disc tiller showed the highest (168.9 and 164.8 N-m m-1, respectively) average specific torque requirement. Regression models indicated a quadratic relationship between forward speed and torque and a linear relationship with depth. The developed models exhibited high predictive accuracy, with R² ranging from 0.86 to 0.91 across the four implements. The torque requirement of active tillage implements is significantly influenced by implement type, forward speed, and tillage depth. These findings highlight the importance of selecting appropriate implements, and operating parameters to optimize energy use and reduce mechanical stresses on tractors. The developed regression models offer practical utility for estimating specific torque requirements under varying field conditions.
Farm Machinery and Power Engineering (FMPE)
Copyright (c) 2026 Journal of Agricultural Engineering (India)
Optimization of Counter-Rotating Cotton Stalk Puller Performance Using Response Surface Methodology and ANN-PSO Technique
Section: Regular Issue Categories: Farm Machinery and Power Engineering (FMPE) Keywords: cotton mechanization, hybrid ANN-PSO, particle swarm optimization, plant breakage, uprooting efficiency Cotton stalks, a by-product remaining after cotton picking, have significant industrial value. However, their removal is difficult due to the deep taproot system, making stalk uprooting labour-intensive. This study focuses on optimizing the uprooting efficiency of a counter-rotating drum-type cotton stalk puller (CSP) using Response Surface Methodology (RSM) and an integrated Artificial Neural Network-Particle Swarm Optimization (ANN-PSO) approach. The developed tractor-operated machine consists of counter-rotating tapered drums with adjustable, spring-loaded clearance to effectively grip and uproot stalks of varying sizes with minimal breakage, even under hard soil conditions. The machine's operational and design parameters were considered as independent variables, whereas uprooting efficiency, plant breakage, and plants left in the field were considered response variables. An experimental CSP unit was evaluated under field conditions at three forward speeds (1.37, 1.67, and 1.95 km h⁻¹), four drum speeds (250, 300, 350, and 400 rpm), and three drum inclination angles (0°, 10°, and 20°). Optimization using RSM indicated that a drum speed of 332.5 rpm, a drum inclination angle of 8.36°, and a forward speed of 1.37 km h⁻¹ were the optimal operating conditions. Under these conditions, the optimum values of uprooting efficiency, plant breakage, and plants left in the field were 96.6%, 2.8%, and 1.1%, respectively, with individual desirability values of 0.97, 0.85, and 0.89, indicating good agreement between the predicted and observed responses. The ANN-PSO model predicted the optimal operating parameters as a forward speed of 1.37 km h⁻¹, a drum inclination angle of 7.89°, and a drum speed of 331.45 rpm. The observed and predicted values of uprooting efficiency under these conditions were 96.72% and 94.84%, respectively. The results demonstrated that both RSM and the integrated ANN-PSO approach effectively predicted and optimized the performance of the CSP, with high accuracy. The optimization study provides valuable insights into the optimal combination of design and operating parameters for achieving enhanced uprooting efficiency with minimal plant breakage.
Performance Evaluation of Power-Operated Maize Sheller for Small and Marginal Farmers Based on Physiological and Subjective Workload Assessment
Section: Regular Issue Categories: Farm Machinery and Power Engineering (FMPE) Keywords: agricultural mechanization, grain damage, NASA-TLX, physiological workload, shelling efficiency This study evaluated the ergonomic suitability and operational performance of a power-operated (0.75 kW) maize sheller for small and marginal farmers under real on-farm conditions. An ergonomic assessment was conducted through physiological workload measurements, including heart rate, oxygen consumption rate, and energy expenditure, as well as a subjective workload evaluation using the National Aeronautics and Space Administration Task Load Index (NASA-TLX). Ten agriculturally experienced participants operated the machine under standardised conditions. The results indicated a moderate physiological workload, with an average working heart rate of 103 bpm, oxygen consumption rate of 0.50 L min-1, and energy expenditure of 15.46 kJ min-1, suggesting acceptable physical demand during operation. The NASA-TLX analysis showed higher temporal and mental demands than physical demands, indicating that task pacing and operator interaction influenced perceived workload more than physical effort. Users reported good portability, operational safety, and ease of use; however, dust generation during operation was identified as a factor affecting operator comfort. The machine achieved a shelling efficiency of 98.05%, a grain damage of 2.92%, and a shelling capacity of 119.4 kg h-1, demonstrating improved productivity while maintaining a manageable ergonomic workload. Overall, the findings indicated that the power-operated maize sheller can reduce labour drudgery and enhance post-harvest efficiency while maintaining an acceptable comfort and safety conditions for smallholder farming systems.
Performance and Economic Evaluation of a Tractor-Operated Deep Furrow Sugarcane Cutter Planter in Haryana
Section: Regular Issue Categories: Farm Machinery and Power Engineering (FMPE) Keywords: bud emergence, deep furrow planting, mechanized agriculture, payback period Sugarcane planting in India is highly labour-intensive and costly, and there is limited field-based evaluation of mechanized cutter planters under diverse agro-climatic conditions. A tractor-operated deep furrow sugarcane cutter planter was evaluated under field conditions at three locations in Haryana using three sugarcane varieties (CoJ 85, COH 119, and CO 118). The machine performs multiple operations in a single pass, such as, opening deep furrows, cutting whole cane stalks into setts, placing them in deep furrows, applying fertilizers and chemicals, and covering with soil. Trials were conducted on sandy loam to loamy sand soils with 11.8% to 13.1% moisture content. The planter achieved sett overlaps between 71 to 81 mm, with over 83% of setts placed within the desirable overlap range, and minimal bud damage (2.78% to 2.93%). It maintained consistent performance across sites, with field capacity of 0.19 to 0.21 ha h-1, field efficiency up to 60.6%, and fuel consumption between 24.05 to 25.89 L ha-1. Labour requirement was drastically reduced to ~20 man-hours ha-1, compared to 210 man-hours ha-1 under conventional planting, translating to over 90% labour savings. Operational costs were reduced by 61%, and mean bud emergence after 45 days was higher in mechanized planting (44.7%) than in the conventional method (39.2%). The sugarcane cutter planter demonstrated a break-even point of 95.73 h year-1, a payback period of 0.99 years, and a benefit- cost ratio of 1.38, indicating it as a cost-effective and profitable option for both individual use and custom hiring. The results indicate that the cutter planter ensures uniform sett placement, reduces labour dependency, and improves planting efficiency. Its ability to handle whole cane stalks and integrate multiple operations makes it a promising solution for large-scale, cost-effective, and timely sugarcane planting under diverse field conditions.
Optimizing Okra (Abelmoschus esculentus) Crop Establishment, Field Performance and Yield Attributes through Mechanized Precision Planting with PAU Multi-Row Seed Planter
Section: Regular Issue Categories: Farm Machinery and Power Engineering (FMPE) Keywords: mechanized planter, okra planting methods, seed germination, weeding intensity, weed management Okra (Abelmoschus esculentus var. Punjab Suhawani) locally known as lady’s finger is a major vegetable crop in India, where effective planting methods and weed management are essential for improving productivity while ensuring operator safety. Traditional practices of planting manually (with Khurpi) often impose high ergonomic burdens on operators, necessitating an integrated evaluation of agronomic performance and human factors. Two experiments were conducted to assess the effects of planting methods, spacing and weeding intensity on okra crop establishment, field performance and yield. Key growth and yield parameters recorded included seed germination, field efficiency, effective field capacity of planter, weed infestation, number of fruits per plant, average fruit weight, average fruit length and total yield. Results revealed that the PAU manual multi-row seed planter demonstrated superior performance, with the highest field efficiency (73.70%), effective field capacity (0.147 ha h-1) and seed germination (84.12%). It also reduced weed infestation (840 plants m-²) compared to manual planting (68.62% efficiency, 70.40% germination, 911 plants m-² weed density). Plant spacing significantly influenced yield attributes. Wider spacing (450 mm) improved fruit weight (12.38 g), fruit length (107 mm) and number of fruits per plant (12 fruits) due to reduced intra-plant competition, whereas closer spacing (150 mm) maximized total yield per hectare (7.72 t ha-1) through increased plant population. Weeding intensity emerged as the most critical factor. Multiple weeding produced the best outcomes in terms of fruit number (14 per plant), average fruit weight (13.43 g), fruit length (115.7 mm) and total yield (11.50 t ha-1), while no-weeding plots recorded only 4.11 t ha-1. Overall, the findings demonstrated that the mechanized planting with the PAU manual multi-row seed planter, combined with wider spacing and timely multiple weeding, can substantially enhance field performance, crop establishment and fruit yield in okra. These results provide practical guidance for growers to maximize productivity through integrated mechanization and agronomic practices.
Effect of Ultrasonication on the Hydration Behaviour of Paddy
Section: Regular Issue Categories: Processing, Dairy and Food Engineering (PDFE) Keywords: effective moisture diffusivity, hydration kinetics, Page model, saturation moisture content, total phenolic content This study examined the impact of ultrasonication at 20 kHz, and 90% of rated power on the hydration behaviour of paddy (var. BPT 5204) at a soaking temperature of 60ºC, and compared it with the conventional soaking methods at 30ºC and 60ºC using various kinetic models. Ultrasonication significantly accelerated hydration by inducing mechanical and cavitational effects, such as the sponge effect and inertial flow, resulting in enhanced water absorption and faster grain hydration. While conventional soaking required 33 hours at 30ºC and 9 hours at 60ºC to reach saturation moisture content (35 ± 1% w.b.), ultrasonication achieved the same in just 3 hours. Kinetic modelling revealed Page model provided the most accurate representation of the hydration process under ultrasonication. Application of ultrasonication at a hydration temperature of 60ºC, yielded approximately a two-fold increase in effective diffusion rates (1.18<!-- [if gte msEquation 12]><m:oMath><m:r><m:rPr><m:scr m:val="roman"/><m:sty m:val="p"/></m:rPr>×</m:r></m:oMath><![endif]--> <!-- [if gte vml 1]><v:shapetype id="_x0000_t75" coordsize="21600,21600" o:spt="75" o:preferrelative="t" path="m@4@5l@4@11@9@11@9@5xe" filled="f" stroked="f"> <v:stroke joinstyle="miter"/> <v:formulas> <v:f eqn="if lineDrawn pixelLineWidth 0"/> <v:f eqn="sum @0 1 0"/> <v:f eqn="sum 0 0 @1"/> <v:f eqn="prod @2 1 2"/> <v:f eqn="prod @3 21600 pixelWidth"/> <v:f eqn="prod @3 21600 pixelHeight"/> <v:f eqn="sum @0 0 1"/> <v:f eqn="prod @6 1 2"/> <v:f eqn="prod @7 21600 pixelWidth"/> <v:f eqn="sum @8 21600 0"/> <v:f eqn="prod @7 21600 pixelHeight"/> <v:f eqn="sum @10 21600 0"/> </v:formulas> <v:path o:extrusionok="f" gradientshapeok="t" o:connecttype="rect"/> <o:lock v:ext="edit" aspectratio="t"/> </v:shapetype><v:shape id="_x0000_i1025" type="#_x0000_t75" style='width:7.8pt; height:13.8pt'> <v:imagedata src="file:///C:/Users/chief/AppData/Local/Temp/msohtmlclip1/01/clip_image001.png" o:title="" chromakey="white"/> </v:shape><![endif]--> 10-10 m2 s-1) when compared to effective moisture diffusivity at 60ºC hydration temperature alone. The kinetic modelling of paddy hydration under the optimized ultrasonication conditions identified in this study can serve as a basis for improving the soaking process in industrial parboiling through suitable integration into large-scale grain processing. This approach has the potential to reduce energy consumption and processing time; however, further research is required to evaluate its scalability, applicability to other grains, and economic feasibility while ensuring the preservation of grain quality parameters.
Processing, Dairy and Food Engineering (PDFE)
Effect of Reheating on the Quality of Selected Starch-Based Foods: Steam-Based Reheating System Vs. Microwave Reheating
Section: Regular Issue Categories: Processing, Dairy and Food Engineering (PDFE) Keywords: food texture, food warmer, FTIR, IR imaging, wet-heat technology The present study evaluated the performance of a specially designed steam-based reheating system for retaining the quality of cooked food, which could serve as an alternative to microwave reheating. Rice, pasta, and flatbread were used as model food matrices and reheated after 6 hours of ambient storage. The various parameters of the selected foods, such as internal food temperature, moisture content, mass loss during reheating, texture, colour, temperature distribution, and possible chemical alterations, were measured before and after reheating. Steam reheating progressively increased the internal temperature of all foods to above 75°C, with rice reaching 74.6°C in 5 minutes and pasta reaching 75.2°C in 7 minutes, according to the Food Safety and Standards Authority of India (FSSAI) food safety specifications. The moisture content was retained better under steam-based reheating system with rice regained up to 76.9%, while moisture content of microwave-treated rice fell to 61.3%. Reheating loss was considerably lower in steam-treated samples (<0.5%) than in microwave-reheated samples (>0.8%) for all the reheated foods. Analysis of colour, textural, and sensory properties of the foods showed that steam-reheated foods exhibited less colour deviation, maintained structural integrity, and were more acceptable overall than microwave-treated counterparts. Infrared (IR) thermal images used to visualize the temperature distribution among the reheated food samples, revealed more uniform thermal pattern in case of the steam-reheated foods. Fourier Transform Infrared (FTIR) Spectroscopy analysis confirmed the absence of toxic substances, with all prominent peaks corresponding to naturally occurring biomolecules. This work identifies the benefits of wet heat technology as a safer, more effective alternative to microwave reheating, while maintaining the food quality.
Physical and Compositional Attributes and Predictive Mass Modelling of Sapota (Manilkara zapota L.) Fruits
Section: Regular Issue Categories: Processing, Dairy and Food Engineering (PDFE) Keywords: criteria projected area, ellipsoidal fruit volume, non-destructive fruit grading, regression-based mass estimation, size-mass relationship This study examined the physical and compositional characteristics of sapota fruits (variety Murabba) and developed predictive mass models based on physical attributes using linear, power, quadratic, and S-curve models. The pulp, peel, and seed contents of the fruits were found to be 85.66 ± 2.04%, 11.48 ± 1.70%, and 2.86 ± 1.02%, respectively. The average spatial dimensions, including the major (L), first minor (W), and second minor (T) axes, were 53.86, 52.06, and 50.20 mm, respectively. The average values for geometric mean diameter (Dg), sphericity (Φ), volume (V), ellipsoidal volume (Vellip), criteria projected area (CPA), and mass were recorded as 51.99 mm, 0.97, 70765.21 mm³, 74212.01 mm³, 2131.51 mm², and 67.22 g, respectively. The results of predictive mass modelling showed that nine models, namely, Dg-based quadratic, Dg-based power, Vellip-based linear, Vellip-based quadratic, Vellip-based power, CPA-based quadratic, CPA-based power, LWT-based linear, and PA-based linear performed better, with higher coefficient of determination (R2 >0.95), and lower root mean square error (RMSE ≤ 2.39 g), and lower mean relative deviation (MRD ≤ 2.48) values. These metrics compare favourably with established fruit mass models: kinnow mandarin (R2 = 0.93, RMSE = 4.2 g), guava (R2 = 0.94, RMSE = 3.1 g), and persimmon (R2 = 0.93, RMSE = 5.8 g), demonstrating superior predictive accuracy for sapota var. Murabba. The Dg-based power model was the best single-variable prediction model, whereas the Vellip-based quadratic model was the best volume-based one. Overall, this study recommends two multiple linear regression models for indirect mass estimation of sapota fruits: LWT-based linear model (-133.38+1.15L+1.91W+0.774T) and projected area-based linear model (-32.89+1.84PA1-0.114PA2+2.714PA3). These mass prediction models can be directly used for the design and calibration of non-destructive, size- and mass-based grading systems for sapota fruits in packhouses and processing units. Their adoption will standardise quality, reduce manual grading, and support mechanised pulp-processing of the Murabba variety.
Flow Behavioural Studies on Food Powders
Section: Regular Issue Categories: Processing, Dairy and Food Engineering (PDFE) Keywords: agglomeration, bulk properties, flowability, food powders, powder properties, porosity This study focuses on characterizing the bulk powder flow properties of four food powders, namely, tomato, onion, mango, and raw banana. The characterization includes particle size and its distribution, shape, moisture content, loose bulk density, tapped bulk density, and porosity. The flowability of these food powders was determined using Hausner Ratio, Carr’s Index, and flow function. The flow function and wall friction tests were conducted using an annular shear tester based on Jenike’s shear cell technology. The instantaneous flow function results showed that the powder flow behaviour of mango was free-flowing, while onion and tomato powders were easy-flowing, and banana was difficult-flowing. After 12 hours of consolidation time, mango powder's flow behaviour changed from free-flowing to easy-flowing, and the other three powders (banana, onion, tomato) moved towards cohesive difficult-flowing behaviour. The particle density of mango powder was the lowest (1389 kg m-3) and onion was the highest (1536 kg m-3). The particle size (d50) of easy-flowing mango powder and difficult-flowing banana powder was 165 µm and 50 µm, respectively. The determined flow properties of the food powders can be used to enhance its handling during commercial operations.
Cryoprotective Strategies for Probiotics in Diverse Food Matrices: From Dairy to Plant-Based Applications
Section: Regular Issue Categories: Processing, Dairy and Food Engineering (PDFE) Keywords: cryopreservation, freeze-drying, microencapsulation, smart delivery systems, vitrification Cryopreservation has emerged as a critical technique for maintaining the viability and functional efficacy of probiotics during industrial manufacturing and shelf life. This review explores the current advances, challenges, and future prospects of cryopreservation technologies for probiotics in dairy and plant-based food matrices. Cryoprotectants, such as dimethyl sulfoxide (DMSO) and glycerol, and natural compounds, such as sugars and proteins, play crucial roles in mitigating cellular damage during freezing by preventing ice crystal formation, maintaining osmotic balance, and inducing vitrification. Cryopreservation techniques, including slow freezing, vitrification, and lyophilization have been optimized to enhance probiotic survival; however, strain-specific responses require tailored protocols for optimal results. Synergistic cryoprotectant combinations and advanced encapsulation methods have further improved post-thaw viability and functionality. The application of cryopreserved probiotics in dairy products, such as yogurt, cheese, and ice cream, has shown promising results, with high survival rates and enhanced sensory attributes. Non-dairy probiotic foods, including plant-based milk alternatives, fermented vegetables, and cereal-based products, have also benefited from cryopreservation, offering novel health-promoting options for diverse consumer preferences. However, challenges such as loss of viability during processing, regulatory concerns, and consumer acceptance issues persist. Future research should focus on developing innovative cryoprotective formulations, smart delivery systems, and synbiotic combinations to optimize probiotic stability and efficacy in functional food matrices. Addressing these challenges will expand the commercial viability and health benefits of probiotic-enriched foods.
Precision Agriculture in Sugarcane Farming: A PRISMA-Based Systematic Review of Technologies, Adoption Gaps, and Sustainability Pathways
Section: Regular Issue Categories: Soil and Water Engineering (SWE) Keywords: biomass utilization, circular economy, precision agriculture, smart agriculture Sugarcane industry faces challenges from resource depletion, environmental degradation, and inefficient management. Precision agriculture (PA) offers a transformative solution through digital, geospatial, and automation technologies. This PRISMA (Preferred Reporting Items for Systematic reviews and Meta-Analyses) - based systematic review, critically evaluates the evolution, adoption, and sustainability implications of the PA in sugarcane farming. Key technologies such as laser land leveling, global navigation satellite systems, variable rate technology, hyperspectral imaging, unmanned aerial vehicles, internet of things, and machine learning improve yield prediction, soil health, water-use efficiency, and carbon footprint reduction. However, large-scale adoption of such technologies is limited due to their high costs, poor data integration, and limited farmer training. This study recommends policy support through subsidies, shared equipment hubs, and open-access digital platforms while suggesting capacity-building initiatives and public-private partnerships for technology diffusion among smallholders. Future studies should prioritize field validation, techno-economic evaluation, and life-cycle assessments. Integrating artificial intelligence-driven systems with circular bio-economy models will boost resilience and sustainability. This review outlines a pathway toward precision-driven, low-carbon sugarcane production.
Remote Sensing-based Indicators for Evaluating Impact of Micro-irrigation Systems on Tea Canopy Growth
Section: Regular Issue Categories: Soil and Water Engineering (SWE) Keywords: drip irrigation, land surface temperature, leaf area index, normalized difference vegetation index, sprinkler irrigation Water scarcity is emerging as a critical constraint for tea plantations in the Dooars region of West Bengal, India, where irrigation largely relies on groundwater resources and conventional overhead sprinklers often lack precision and uniformity. This study employed remote sensing techniques in sprinkler-irrigated and drip-irrigated plots in the Dooars during the pre-monsoon and post-monsoon seasons over a three-year period (2018-2020) to determine how the two different irrigation systems (sprinkler and drip) influence tea canopy growth. Correlations between canopy cover and its influencing factors, i.e., normalized difference vegetation index (NDVI), leaf area index (LAI), soil moisture content, and land surface temperature (LST) were assessed. Results showed that the mean NDVI increased by 11.14% in the pre-monsoon season and 6.17% in the post-monsoon season. These changes in the mean NDVI in the drip-irrigated plot indicated higher tea canopy growth due to adequate water availability in the root zone. The values of NDVI (0.47 to 0.55), LAI (2.79 to 3.14), and soil moisture (0.09 to 0.17 m3 m-3) were higher under drip irrigation system. Also, strong correlations among NDVI, LAI, LST and soil moisture parameters demonstrated that water availability in the root zone of the tea plantation under drip irrigation improved canopy growth driven by favorable soil-plant-water interactions. Therefore, drip irrigation outperformed sprinkler system in improving soil moisture retention and promoting tea canopy growth, making it a sustainable long-term solution for tea estates in the region.
Assessment of Soil Fertility and Nutrient Dynamics Using Multivariate and Geospatial Approaches in Himachal Pradesh, India
Section: Regular Issue Categories: Soil and Water Engineering (SWE) Keywords: correlation matrix, geographical information system, inverse distance weighting method, principal component analysis, soil fertility maps This study evaluated soil fertility at the experimental farm of the Regional Horticultural Research and Training Station, Jachh, Kangra, Himachal Pradesh, India. A total of 78 soil samples, collected during 2023 from 0-30 cm depth, were analyzed to determine soil physico-chemical properties i.e., pH, electrical conductivity (EC), organic carbon (OC)], macro-nutrients [i.e., nitrogen (N), phosphorus (P), and potassium (K)], micro-nutrients [i.e., iron (Fe), zinc (Zn), copper (Cu), manganese (Mn)]. Further, soil nutrient index was computed and soil fertility distribution map was generated using the inverse distance weighting method in the geographic information system. Soil pH ranged from 6.25 (slightly acidic) to 7.69 (slightly alkaline) with the mean of 7.01. EC was low (0.09 to 0.52) indicating non-saline soil with suitability for all crops. Soil OC ranged from 0.45% (medium) to 1.59% (high), though moderate variability was observed due to differences in land use/land cover and soil management. Available N was deficient (125.44 to 282.40 kg ha-1), whereas P and K were medium (12.38 and 156.02 kg ha-1, respectively) to high (110.27 and 418.18kg ha-1, respectively), suggesting imbalanced nutrient availability. Fe (4.50-18.77mg kg-1) and Cu (0.20-3.87mg kg-1) were in adequate quantities; however, Zn showed medium status (0.66-10.82 mg kg-1) with high variability, and Mn was deficient (0.87-6.35mg kg-1). Soil nutrient index indicated low fertility for N (1.35), high for OC (3.35), P (3.68), and K (3.17), and medium to high (1.86 to 3.27) for the micro-nutrients. Correlation matrix revealed significant relationships among pH, OC, macro-nutrients, and micro-nutrients, indicating that the common soil factors influence the nutrient distribution. Principal component analysis identified Fe, K, Zn, EC, pH and N as the key indicators, explaining 72.3% of the total variance. Overall, the study highlighted a good soil reaction and micro-nutrient status but emphasized on the need for improved N and Mn management to sustain soil fertility and crop productivity.
Modeling and Trend Analysis of Reference Evapotranspiration in Western Maharashtra, India
Section: Regular Issue Categories: Soil and Water Engineering (SWE) Keywords: artificial neural network, climate-based model, linear regression, Mann-Kendall test, Penman-Monteith equation In this study, reference evapotranspiration (ETo) was estimated over nine stations of western Maharashtra, India, using nine climate-based models, four linear regression (LR) models and four artificial neural network (ANN) models. None of the climate-based models replicated the spatial patterns of ETo as depicted by the FAO-56 Penman-Monteith (P-M) method. The P-M method based ETo values indicated an increase in ETo values from the central region toward the southeast part of the study area, with comparatively higher values also observed in the northeast area. The LR and ANN model outputs showed spatial patterns closely aligning with the P-M method. Overall, all LR and ANN models provided reliable ETo predictions. Hargreaves-Samani (H-S) and Pan Evaporation (PAN) models showed close ETo patterns, with ETo values of H-S model being higher (4.79-5.40 mm day-1) than that of PAN (3.22-5.11 mm day-1). Likewise, Jensen-Haise (J-H) and Turc models showed almost similar patterns, but ETo values of J-H model were higher (3.02-4.01 mm day-1) than that of Turc (1.68-1.87 mm day-1). Also, Priestly-Taylor (P-T) and Radiation (RAD) models showed spatial patterns differing from other climate-based methods, with ETo ranging from 3.92-4.39 mm day-1 and 5.72-6.02 mm day-1, respectively. Trend results using Mann-Kendall test indicated a decrease in ETo, estimated using the P-M model, at all stations. The slopes obtained from the P-M method estimated ETo indicated decreasing ETo trends at all stations. The climate-based models, SCS-BC, THOR, and Hargreaves-Samani (H-S) exhibited positive slope values across most stations, indicating a gradual increase in ETo. These findings highlighted the importance of developing region-specific ETo estimation tools to support effective irrigation planning, drought mitigation, and sustainable water resource management under conditions of climatic variability and limited facilities available to record meteorological observations. The LR and ANN approaches demonstrated reliable capability for ETo predictions and strong agreement with that of the P-M method, even under limited inputs.
Satellite-Based Assessment of Rooftop Rainwater Harvesting and Solar Energy Potential in Hamirpur City, Himachal Pradesh, India
Section: Regular Issue Categories: Soil and Water Engineering (SWE) Keywords: clean energy, climate change, GIS, Remote sensing, solar photovoltaic panel India faces a growing water crisis driven by pollution, inadequate infrastructure and climate change, while rising energy demand continues to strain fossil fuel resources. Innovative technological interventions such as rooftop rainwater harvesting (RWH) and solar photovoltaic (PV) systems offer integrated solutions to address the challenges of the water crisis. The present study, conducted during 2023-2024, analyzed potential of harvesting rainwater as well as solar energy from the rooftops of 260 buildings with a total digitized rooftop area of 53,235 m² that comes under the Municipal Committee of Hamirpur city in Himachal Pradesh, India. The city has a humid subtropical climate with a mean annual rainfall of 1,298 mm, concentrated mainly during the southwest monsoon season. The city-wide annual RWH potential is estimated at 1,479,118.5 m³, which was found to meet satisfactorily 47.68% of the current municipal water demand of the city. In addition, the rooftop potential of harnessing solar PV energy is computed as 0.226 million kW, which is sufficient to meet about 66.29% of the city’s electricity demand, if fully utilized. Benefit-cost ratio (BCR) indicated attractive economics, with a BCR of 3.0 for RWH and 5.6 for solar PV based on prevailing electricity tariffs and system costs. The findings of this study are useful to plan efficient utilization of the harvested rainwater and solar energy with improved productivity sustainably. Moreover, the methodology adopted in this study may be easily replicated in other places to obtain probable amounts of rainwater and solar energy that can be successfully harvested and better utilized in adverse climate settings.
Assessment of Efficiency and Environmental Impacts of Biomass-Fueled Conventional and Centralized Mushroom Substrate Sterilization Systems
Section: Regular Issue Categories: Energy in Agriculture Keywords: global warming potential, IoT, life cycle assessment, mushroom production, rice husk combustion, steam sterilization Simple and low-cost sterilization equipment is frequently used to disinfect the substrate in cottage-level mushroom production. This study evaluates the performance and environmental impacts of conventional and centralized mushroom substrate steam sterilization systems using biomass fuels. Two systems, namely, conventional steam sterilization equipment (ConSSE) and centralized steam sterilization equipment (CenSSE) were experimentally tested with wood fuel and rice husk under controlled conditions. Key performance parameters, including temperature, pressure, fuel consumption, water usage, and processing time, were measured, while environmental impacts were assessed using life cycle assessment (LCA) with selected midpoint indicators. The results showed that neither system achieved the recommended sterilization conditions of 120°C and 151 kPa, indicating limitations in current designs. However, the CenSSE with four sterilization units demonstrated superior performance, reducing total processing time by 68.5% compared to ConSSE. Rice husk combustion resulted in higher burner efficiency (18.8%–23.1%) than wood fuel (10.8%–11.2%), leading to lower biomass consumption and reduced environmental impacts. Among all combinations, ConSSE with wood fuel exhibited the highest global warming potential, while CenSSE with rice husk showed the lowest environmental impact. The findings highlight that the integration of improved burner design, appropriate material selection, and the use of rice husk as a renewable fuel can significantly enhance system efficiency and sustainability. The automation of CenSSE achieved the sterilization conditions of 118.5°C and 144 kPa. Further, automated control of blower speed and rice husk feeding rate reduced the time required to reach the target temperature by 38.7%, decreased the total sterilization time by 21.2%, reduced the rice husk consumption by 12.3% and improved the burner efficiency by 23,3%. Thus, integration of automation and real-time control using IoT has potential to enhance energy efficiency, and operational reliability.
A Gamma Test Driven Framework for Predicting Fluoride Adsorption Capacity of Biochar Using Multiple Artificial Intelligence Models
Section: Regular Issue Categories: Energy in Agriculture Keywords: data-driven modelling, defluoridation, environmental remediation, machine learning, sorption efficiency, sustainable adsorbents Adsorption of fluoride using biochar signifies a promising and innovative method under current study. The complexity of determining biochar's adsorption properties cannot be fully depicted by traditional mathematical modelling alone. This study presents a novel contribution by applying multiple artificial intelligence techniques to model fluoride adsorption. By considering both proximate and elemental properties of biochar as input variables, this research utilizes the Gamma test (GT) to identify ideal input combinations for the M5 Tree, SVM (Support Vector Machine), MARS (Multivariate Adaptive Regression Splines), MGGP (Multi-Gene Genetic Programming), and MM-ANN (Modular Multilayer Artificial Neural Networks) models. The comparative analysis of these predictive models was evaluated using various statistical metrics (Nash-Sutcliffe efficiency (NSE), Willmott's index of agreement (WI), root mean squared error (RMSE), mean absolute percentage error (MAPE), and Legates and McCabe's index (LM)). The MARS-4 model with four input variables exhibited the highest accuracy with MAPE = 102%, RMSE = 2.56 mg g-1, LM = 0.57, WI = 0.93, and NSE = 0.83 in predicting fluoride adsorption during the testing phase. The MARS-4 model was followed by M5Tree-4 model. These results highlight the MARS-4 model's effectiveness and its potential to offer valuable insights for optimizing biochar for fluoride removal. The study showed enhanced predictive accuracy for fluoride adsorption and guidance for future biochar engineering.
Optimization of Process Conditions for Production of Succinic Acid and Lactic Acids from Cake Waste Using Response Surface Methodology
Section: Regular Issue Categories: Energy in Agriculture Keywords: Box-Behnken design, food waste valorization, microbial fermentation, statistical modeling, sustainable bio-processing Food waste valorization into bio-based chemicals is an eco-friendly strategy to address environmental pollution and reduce reliance on fossil-based resources. This study explores the feasibility of bioconversion of cake waste into succinic acid (SA) and lactic acid (LA), through enzymatic hydrolysis and microbial fermentation. The compositional analysis revealed that, on a dry weight basis, cake waste contains 572.0 mg g⁻¹ carbohydrates, 495.0 mg g⁻¹ starch, and 69.3 mg g⁻¹ protein, making it a nutritionally rich substrate for fermentation and then it was hydrolyzed using α-amylase, glucoamylase, and protease to release fermentable sugars and amino nitrogen. Enzymatic hydrolysis yielded 41.50 g L⁻¹ glucose and 4.56 g L⁻¹ free amino nitrogen. The enzymatic hydrolysate was subsequently fermented using Escherichia coli and Bacillus coagulans for SA and LA production, respectively. High performance liquid chromatography (HPLC) was used to quantify organic acid concentrations. Process optimization was performed using Box Behnken Design under response surface methodology (RSM), with three independent variables, namely, temperature, pH, and incubation time. The highest succinic acid yield (0.2194 g g⁻¹ cake waste) was obtained at a temperature of 40°C, pH of 7.5, and an incubation time of 144 h, while the maximum lactic acid yield (0.3178 g g⁻¹ cake waste) was recorded at a temperature of 47°C, pH of 5.6, and an incubation time of 94 h. Results demonstrate that cake waste can serve as a promising low-cost substrate for sustainable production of succinic and lactic acids, highlighting its potential for efficient food waste valorization through microbial bioprocessing.
Catalytic Gasification of Coconut Shell for Producer Gas Yield Improvement: An Optimization Study with the Response Surface Methodology Approach
Section: Regular Issue Categories: Energy in Agriculture Keywords: biomass gasification, calcium oxide, catalyst, chicken eggshells Catalytic biomass gasification is gaining momentum due to enhanced producer gas yield and effective tar cracking. In this study, coconut shell (feedstock) and calcium oxide (catalyst) were used in a downdraft biomass gasifier to determine optimal conditions through the Response Surface Methodology (RSM) approach, aiming for better gas generation. Waste chicken eggshells-based calcium oxide (CaO) was used as catalyst to evaluate its effectiveness in achieving improved producer gas yield and fuel quality. In optimization, the effect of two key process variables viz., equivalence ratio (0.2-0.3) and CaO loading (5-30 wt.%) were assessed on producer gas and its hydrogen content. The catalyst has more significant effect on final product yield than equivalence ratio. The maximum producer gas yield was achieved as 2.4 m³ kg-1 during catalytic gasification process with optimized conditions of equivalence ratio of 0.25 and catalyst loading of 29.14%. The tar removal efficiency was found to be 83.7%. Additionally, it was observed that the hydrogen content was significantly enhanced (30.86%) in catalytic gasification compared to non-catalytic gasification (12.74%) under optimal process conditions.
Investigation on Temperature Phased Anaerobic Digestion (TPAD) of Dairy Industrial Fat-Rich Sludge
Section: Regular Issue Categories: Energy in Agriculture Keywords: biogas production, mesophilic digestion, methane yield, thermophilic digestion, two-phase digestion In the present investigation, a Temperature-Phased Anaerobic Digestion (TPAD) system was evaluated for treating dairy industry fat-rich waste sludge. Results showed that both biogas yield and methane content were higher than those obtained from a conventional anaerobic digester. The configuration of two reactors in series, with the thermophilic unit as the initial stage, succeeded by the mesophilic unit, was optimized for both thermophilic and mesophilic conditions. The second mesophilic stage finalizes the digestion process, transforming partially digested organics into methane and carbon dioxide, so totally recovering the energy by-product from dairy waste sludge. The pH value in the TPAD varied from 6.91 to 7.51. The maximum volatile solids (VS) removal efficiency of 39.6% achieved in the TPAD system as the thermophilic operation time was maintained initially for 10 days during the start-up of the batch TPAD experiment. The methane production increased from 220 to 435 ml of CH4 g-1 of VS, and the methane content varied from 51.9% to 62.4%. This value exceeded the yields attained by the conventional anaerobic digester at solids retention time (SRT) of 35 days obtained as 357 ml of CH4 g-1 of VS with 58.1% methane content. Using the TPAD technique, anaerobic digestion of dairy industrial waste sludge effectively recovered the energy as methane. As a result, in comparison to traditional anaerobic systems, the TPAD system allowed higher methane outputs and superior operational performance.