Anand Agricultural University

Agricultural credit plays a vital role in supporting India’s rural economy and improving the livelihoods of small and marginal farmers. Although institutional credit to agriculture has increased substantially in recent years, equitable and effective access remains a persistent challenge. This paper adopts a systematic review approach based on 15 peer-reviewed studies published between 2021 and 2025 to examine the constraints affecting agricultural credit access in India. The review identifies five major categories of constraints: institutional/policy, economic, social/demographic, knowledge/behavioral, and structural/systemic. Key issues include gaps in policy implementation, stringent collateral requirements, bureaucratic delays, farmer indebtedness, disparities across social groups, limited financial literacy, and the continued dependence on informal lenders. The findings indicate that while initiatives such as Kisan Credit Cards, Joint Liability Groups, digital lending platforms, Farmer Producer Organizations, and crop insurance schemes offer partial solutions, a comprehensive and integrated approach is necessary. Strengthening last-mile delivery, simplifying procedures, enhancing awareness, and leveraging technology are critical for achieving inclusive and sustainable agricultural finance in India.

Understanding spatiotemporal changes in extreme rainfall is critically important in monsoon-dominated regions. This study investigates trends in heavy (HR), very heavy (VHR), and extremely heavy (EHR) rainfall events across Middle Gujarat and Saurashtra, India, using quality-controlled daily ERA5 reanalysis data for the period 1980–2022. Six climatically diverse districts Ahmedabad, Dahod, Panchmahal, Amreli, Junagadh, and Rajkot — were selected for analysis. Rainfall trends were assessed using linear regression and Sen's slope estimator, with statistical significance evaluated through the non-parametric Mann–Kendall test. Results reveal spatially heterogeneous rainfall behavior across the study region, with weak to moderate increasing tendencies observed in HR events and comparatively clearer increasing trends detected in VHR events at selected stations. EHR events, though rare, exhibit notable episodic increases in recent decades, particularly over urban and semi-arid areas. However, the majority of detected trends do not attain statistical significance at the 95% confidence level, largely attributable to strong interannual variability and the sporadic nature of extreme rainfall occurrences. Despite limited statistical significance, the observed shift toward higher-intensity rainfall events highlights growing hydroclimatic vulnerability across Gujarat, underscoring the urgent need for impact-based risk assessment, improved urban drainage design, and climate-resilient water resource planning strategies.

The research aims to develop a single-pass integrated machine that can simultaneously cut crops, spray pesticides, and sow seeds, replacing the need for separate machinery. The primary objectives are to minimise overall operating time and achieve significant labour savings for small to medium-sized farm operations. By utilising a single power unit for all three functions, the goal is to enhance fuel efficiency and reduce cultivation costs. The ultimate aim is to boost agricultural productivity by offering a user-friendly, adaptable, and energy-efficient solution. The machine is designed by combining various mechanisms powered by a single unit. A single DC motor operates both the seed feeder and the crop harvesting mechanisms simultaneously. This motor is powered by a rechargeable dry battery unit. To accommodate different field operations, the machine has two modes: high and low. The seed sowing mechanism employs a rotational drum feeder to ensure a consistent and measurable seed output, while the crop harvesting mechanism utilises the reciprocating motion of cutter blades. All these components are mounted on a compact frame, making the machine easy to operate, transport, and handle in the field. This compact design reduces costs while enhancing versatility for various operations. The system's calculated speed of 2 mph allows the Grass Cutter component, despite its smaller 2-foot width, to achieve a time of 123.75 minutes per acre, marking a notable 17% improvement over the average market push mower. This high travel speed also grants a significant advantage to the Sprinkler System, which is calculated to cover 1 acre in just 73 minutes and 24 seconds.

The increasing accumulation of single-use plastic cutlery poses a serious environmental threat due to its non-biodegradable nature and long persistence in landfills. This study aimed to develop and evaluate nutritionally enriched, eco-friendly edible cutleries using finger millet (Eleusine coracana L.) flour as a partial or complete substitute for wheat flour. Edible cutleries were formulated using varying proportions of wheat flour and finger millet flour (0, 25, 50, 75 and 100%), with jaggery as a natural sweetener and binding agent. The prepared cutleries were baked at 160°C for 20 minutes and assessed for physicochemical, textural, sensory, and nutritional characteristics. Proximate analysis revealed that the incorporation of finger millet significantly influenced the nutritional composition of the cutleries. The T2 formulation (50% finger millet flour) exhibited optimal nutritional properties, with moisture content of 6.40%, energy value of 355.89 kcal/100 g, carbohydrates of 78.50 g/100 g, protein of 8.02 g/100 g, fat of 1.09 g/100 g, fiber of 4.45 g/100 g, and ash content of 1.54 g/100 g. Statistical analysis using one-way ANOVA indicated significant differences (p < 0.001) among treatments for most parameters except fat content. Texture analysis demonstrated a progressive decrease in hardness with increasing finger millet content, attributed to reduced gluten strength. Sensory evaluation using a 9-point hedonic scale showed that the 50% finger millet sample (T2) achieved the highest overall acceptability despite lower hardness. Overall, the study concludes that finger millet-based edible cutleries are nutritionally superior, structurally stable, and sensorially acceptable, offering a sustainable and biodegradable alternative to conventional plastic cutlery while promoting the utilization of nutrient-rich traditional grains.

Aims: The study was carried out to standardize formulations and optimize the drying process parameters by tray drying technique for production of red-fleshed dragon fruit leather by using dragon fruit peel as a by-product waste utilization. Place and Duration of Study: Department of processing and food engineering, College of agricultural engineering, Godhra, Gujarat, between January to May 2024. Methodology: Tray dried red-fleshed dragon fruit leather was prepared by varying process variables, i.e., sugar (10, 20, 30, 40, and 50 g/100g), peel (10, 20, 30, 40, and 50 g/100), temperature (50, 55, 60, 65, and 70°C) and thickness (2, 3, 4, 5, and 6 mm) and its responses like vitamin C, acidity, protein content, total soluble solids, color value -- L*, a*, b*, overall acceptability of red-fleshed dragon fruit leather was analyzed by using Response Surface Methodology (RSM). Results: The optimum value of overall acceptability (7.95), vitamin C (39.08 mg/100g), and color value a*(18.26) of red-fleshed dragon fruit leather prepared by tray drying was found at process parameters of sugar (23.29 g/100g), peel (29.41 g/100g), temperature (69.9°C) and thickness (3mm) by using RSM.

Forty five genotypes of Indian mustard [Brassica juncea (L.) Czern and Coss] were evaluated for seed yield and quality traits in Randomized Block Design with four replications during the Rabi, 2019-2020. The analysis of variance revealed that the mean sum of squares due to genotypes was significant for all the eighteen characters studied indicating the presence of variability for all the traits among the genotypes under study. Low difference between genotypic and phenotypic variances revealed that the contribution of genotypic variance to total variance was more for all the traits except days to maturity and plant height. The high values of genotypic and phenotypic coefficient of variation for the number of branches per plant, seed yield per plant , myristic acid, palmitic acid and stearic acid which indicated the potential variability available for these traits. The high heritability estimates obtained in conjunction with high genetic advance were observed for the number of branches per plant, the number of siliquae per plant, seeds per siliqua, length of siliqua , 1000-seed weight , seed yield per plant , myristic acid , palmitic acid, stearic acid , linoleic acid , linolenic acid and glucosinolate suggesting the predominant role of additive gene action for their expression. Association analysis between seed yield per plant and other seventeen characters revealed significantly positive correlation of seed yield per plant with the number of siliquae per plant, seeds per siliqua, length of siliquam, myristic acid and erucic acid. Path analysis revealed positive direct effects of the number of siliquaeper plant and seeds per siliqua towards seed yield per plant while myristic acid, the number of branches per plant had a positive indirect effect on seed yield per plant via the number of siliquae per plant suggesting that the selection for such traits would be more effective for improving seed yield in Indian mustard

Sheep milk is a rich source of proteins with potential to generate bioactive peptides through microbial fermentation. However, limited studies have focused on the Panchali sheep breed of India and the multifunctional health properties of its fermented products. This study investigated the generation of bioactive peptides with antidiabetic, antioxidative, and anti-inflammatory properties through the fermentation of sheep milk using a potent LAB, Limosilactobacillus fermentum (KGL4, MTCC 25515), in combination with the yeast strain Saccharomyces cerevisiae (WBS2A, MG101828). Optimal bioactivity was observed after 48 h of fermentation at 30 °C, with antioxidant activity reaching 40.08%, α-amylase inhibition at 72.48%, and α-glucosidase inhibition at 75.96%. Proteolytic activity was assessed at varying inoculum concentrations (1.5, 2 and 2.5%) and incubation time (0, 12, 24, 36 and 48 h), with the highest activity (6.74 mg/mL) observed at a 2.5% inoculum after 48 h. Additionally, fermented milk effectively lowered the production of pro-inflammatory cytotoxins and ROS in LPS-induced RAW 267.4 macrophage cells, indicating its anti-inflammatory properties. Protein profiling through SDS-PAGE revealed bands between 15 and 70 kDa, while 2D electrophoresis identified 39 distinct protein spots associated with peptide production. Reverse-phase HPLC of ultrafiltered water-soluble extracts (WSEs) was used to separate peptide fractions, and identified sequences were assessed through comparison with BIOPEP database to confirm antidiabetic and antioxidative activities. The most potent selected peptide showed strong binding affinity and stable interaction within the active pockets of human α-amylase and α-glucosidase, as well as high HADDOCK and HPEPDOCK scores in molecular docking analyses. These findings indicate that fermented sheep milk is a promising source of multifunctional bioactive peptides with potential applications in functional foods targeting diabetes and inflammation. Further in vivo studies are warranted to validate physiological relevance, bioavailability, and health benefits.

The field experiment was carried out during the rabi season of 2021–22 at the College of Agricultural Engineering & Technology, Anand Agricultural University, Godhra. to evaluate the effect of pulse drip irrigation and different lateral spacing on the growth, yield, and water productivity of wheat (Triticum aestivum L.). A split-plot design was adopted with four pulse irrigation levels—continuous flow (P1), two pulses (P2), three pulses (P3), and four pulses (P4)—and three lateral spacings: 0.6 m (S1), 0.8 m (S2), and 1.0 m (S3), replicated three times. The experiment used 16 mm laterals with 0.4 m emitter spacing and a discharge rate of 4 lph. Irrigation was scheduled at an IW/CPE ratio of 0.8 at four-day intervals. The high-yielding wheat variety GW 496 was selected, sown on November 28, 2021, at a seed rate of 120 kg ha-1 using a seed-cum-fertilizer drill. The recommended fertilizer dose of 120:60:60 kg N: P: K per hectare was applied, with half the nitrogen and the full phosphorus and potash given as a basal dose. The results revealed that both pulse frequency and lateral spacing significantly influenced wheat growth and yield parameters. The highest plant height (70.5 cm), number of effective tillers (62.5 m-1), grains per spike (51.2), and grain yield (4228 kg ha-1) were recorded under P4, while P1 recorded the lowest. Among lateral spacings, S1 produced the highest grain yield (3913 kg/ha) and water productivity. The combined treatment P4S1 (four pulses with 0.6 m spacing) achieved the best overall performance, with a grain yield of 4854 kg ha-1, straw yield of 5163 kg ha-1 and a maximum benefit-cost ratio of 2.84. hence offering a sustainable and economically viable practice for enhancing wheat productivity in the water-scarce regions of Gujarat.

Abstract This paper presents a Radial Basis Function neural network based higher-order Sliding Mode Control for robust control of a dynamical system. A conventional sliding mode controller is suffering from a chattering problem, and the Super Twisting Algorithm is a special kind of higher-order Sliding Mode Control that has the capability of minimizing the chattering problem. There are also unknown model parameters and external disturbances that exert a negative influence on the control performance. To address the issues of model uncertainties and chattering, a Radial Basis Function (RBF) neural network based Super Twisting Algorithm is designed. The RBF neural network evaluates the model parameters and uncertainties, while the Super Twisting approach mitigates chattering, hence improving the controller’s overall performance. Lyapunov stability based adaptive laws are derived for online updating of the parameters of the neural network. The proposed control algorithm was tested on a 2-degree-of-freedom serial flexible joint robotic arm to investigate its efficacy. The controller has a lower control chattering amplitude, lower control energy consumption, and a good tracking response, when compared to the RBF based conventional Sliding Mode controller and simple STA controller, as shown by the results.