A Journal published by Indian Society of Agricultural Sciences, IARI, New Delhi an umbrella society for Agricultural sciences. NAAS Rating: 4.62
Leveraging predictive models for accurate crop yield forecasting-smart harvest approach
This research introduces Smart Harvest, a data-driven forecasting system developed to predict the yield of key crops such as sugarcane, wheat, rice, and maize. By combining historical yield records with rainfall statistics, the model captures the intricate relationship between crop production and climatic variation. The study evaluates several predictive techniques, including ARIMA, ARIMAX, Support Vector Regression (SVR), Random Forest, and Artificial Neural Networks (ANN). Through a comparative performance analysis using metrics like RMSE, MAE, and MAPE, the results highlight the effectiveness of rainfall-integrated models in improving forecasting accuracy. The findings provide a robust foundation for enabling timely, informed agricultural planning and risk management strategies.
Path coefficient studies in marigold (Tagetes spp.)
Path analysis studies were carried out among twelve genotypes of marigold for twenty quality and yield attributing traits contributing towards total flower yield. The present study was conducted at Botanical Garden. Bihar Agricultural University, Sabour, Bhagalpur, Bihar, India during winter season, 2021-22. The experiment was laid out in Randomized Block Design with three replications. The results revealed that path coefficient result revealed that characters like number of flowers per plant (0.716, 0.715), number of leaves per plant (0.856, 0.858) and average fresh weight of flower (0.708, 0.708) showed direct positive effect towards flower yield per plant at both phenotypic and genotypic level, respectively through which the selection of superior marigold genotypes may be obtained.
Rancidity in pearlmillet (Pennisetum glaucum): biochemical mechanisms, genetic variability and mitigation strategies
Pearlmillet is a nutritionally rich and climate-resilient cereal crop widely cultivated in arid and semi-arid regions. However, its utilization in processed food systems is limited by the rapid development of rancidity in the flour after milling. Rancidity in pearlmillet flour is predominantly enzymatic, initiated by endogenous triacylglycerol lipases that release free fatty acids, followed by oxidative reactions mediated by lipoxygenase and non-enzymatic pathways, resulting in the formation of volatile compounds responsible for development of off-flavour during storage. Although numerous studies have independently investigated biochemical indicators, genetic variability and processing-based mitigation strategies, the available information remains fragmented and lacks an integrated synthesis linking enzymatic mechanisms with genetic regulation and technological interventions. Recent advances in metabolomics, transcriptomics and functional genomics have improved understanding of lipid catabolism and flavour deterioration in pearl millet flour. However, these findings have not yet been comprehensively evaluated in the context of breeding and industrial processing. Integration of biochemical understanding, genetic improvement and optimized post-harvest processing strategies is essential for enhancing flour shelf stability and expanding the utilization of pearl millet in modern food systems.
Effect of pre- and post-emergence herbicides on crop growth, yield and profitability of greengram under western arid region of Rajasthan
A field experiment was conducted at SKRAU Bikaner during kharif, 2022 on loamy sand soil to evaluate the effect of pre- and post-emergence herbicides on crop growth, yield and profitability of green gram [Vigna radiata (L.) Wilczek] under western arid region of Rajasthan. The experiment was designed in a randomized block design, with 10 treatments and three replications. The experiment comprises of ten treatments viz., weedy check, weed free, pendimethalin 750 g ha-1 PE, diclosulam 20 g ha-1 PE, flumioxazin 75 g ha-1 PE, pendimethalin + imazethapyr (30+2) 800 g ha-1 PE, imazethapyr 50 g ha-1 PoE, quaizalofop + imazethapyr (7.5+15) 65 g ha-1 PoE, imazethapyr + imazamox (35+35) 50 g ha-1 PoE and sodium acifluorfen + clodinafop (16.5+8) 240 g ha-1 PoE. Among all the weed management practices, weed free treatment recorded highest plant height, dry matter accumulation, number of branches and dry weight of nodules. Among different herbicides, pre-emergence application of pendimethalin + imazethapyr (30+2) 800 g ha-1 PE recorded highest growth parameters, yield attributes viz. pod plant-1, seed pod-1, test weight (g) and seed yield followed by pendimethalin 750 g ha-1 PE. pendimethalin + imazethapyr (30+2) 800 g ha-1 PE also recorded highest net returns (Rs. 54130) and B:C ratio (3.01). The minimum growth parameters, yield and yield attributes found in weedy check and diclosulam 20 g ha-1 PE.
Effect of integrated weed management on weed dynamics and performance of wheat (Triticum aestivum L.) + mustard (Brassica juncea L.) intercropping
A field experiment was undertaken during Rabi 2022-23 and 2023-24 at the Agricultural Research Farm of J.V. College, Baraut (Baghpat), Uttar Pradesh to evaluate the effect of integrated weed management practices on weed dynamics and productivity of wheat (Triticum aestivum L.) + mustard (Brassica juncea L.) intercropping system. The experiment was laid out in split plot design comprising two factors: main plot treatments included Sole Wheat (I1), Sole Mustard (I2), Wheat + Mustard (6:1) (I3) and Wheat + Mustard (9:1) (I4), while sub plot treatments consisted of Weed free (W1), Two hand weeding at 30 & 45 DAS (W2), Pendimethalin @ 1 kg ha-1 as PE + Clodinafop 60 g ha-1 as PoE (W3), Pendimethalin @ 1 kg ha-1 as PE + Hand weeding at 30 DAS (W4) and Weedy check (W5). The findings revealed that weed free & two hand weeding at 30 & 45 DAS (W2) recorded maximum weed control efficiency at 45 DAS, 90 DAS and at harvest, followed by pendimethalin @ 1 kg ha-1 as PE + hand weeding 30 DAS (W4), and both were significantly superior over remaining treatments during both years. Wheat sole gives the maximum grain yield of wheat, among cropping systems, Wheat + Mustard (9:1) (I4) produced highest grain yield of wheat (4.65 & 4.82 t ha-1) and minimum seed yield of mustard (4.1.0 &4.8 q ha-1), which remained statistically at par with Wheat + Mustard (6:1) (I3). Under weed management treatments, Next to weed free W2 resulted in maximum grain yield of wheat (4.65 & 4.84 t ha-1) and mustard (16.6 & 17.1 q ha-1), closely followed by W4 and W5. The study indicated that two hand weeding at 30 - 45 DAS can be considered an efficient and practical weed management approach in wheat– mustard intercropping.
Effect of nitrogen and weed management on weed dynamics, and mustard yield and profitability in semi-arid Afghanistan
An experiment was conducted at the experimental farm of Afghanistan National Agricultural Sciences and Technology University (ANASTU), Kandahar during spring 2020 to study the effect on nitrogen and weed management practices in mustard under semi-arid region. Experimental treatments comprised four weed management practices (WMPs) in main-plot [viz. Weedy-check (WC), Weed-free check (WFC), Pendimethalin pre-emergence @ 1.0 kg ha-1 and Pendimethalin @ 0.75 kg ha-1 pre-emergence followed by one hand-weeding at 30 DAS and four N levels [120, 80, 40 and 0 kg ha-1] as sub-plot treatments. The experiment was laidout in a split-plot design with three replications. Among WMPs, the WFC recorded zero population of weeds, while significantly lower number of weeds (NLWs + BLWs) was recorded with WMPs, Pendimethalin 0.75 kg ha-1 (PE) followed by (fb) hand-weeding at 30 DAS (51.9 m-2). The highest number of weeds (NLWs + BLWs) was recorded with WFC (76.2 m-2). Among N management practices (NMPs), the significantly lower (p<0.05) number of weeds (NLWs+ BLWs) was recorded with 0 kg N ha-1 (36.5 m-2) followed by 40 kg N ha-1 (41.5 m-2) and 80 kg N ha-1 (47.0 m-2). The significantly lower dry weight of weed was observed with 0.75 kg ha-1 Pendimethalin (PE) followed by (fb) hand-weeding at 30 DAS (15.63 g m-2) fb Pendimethalin 1 kg ha-1 PE (16.88 g m-2) and higher weed dry weight (NLWs + BLWs) was observed with treatment, WC (20.91 g m-2). The results showed that significantly higher weed control efficiency was recorded with WMPs, 0.75 kg ha-1 Pendimethalin (PE) herbicide fb hand-weeding at 30 DAS (23.6 %), followed by Pendimethalin 1 kg ha-1 PE (14.1%). The higher WCE was recorded with NMPs, 0 kg N ha-1 followed by 40 kg N ha-1. The significantly higher plant height, leaf area index, dry matter accumulation, seed yield of mustard was recorded with WFC, then 0.75 kg ha-1 Pendimethalin (PE) herbicide followed by hand-weeding at 30 DAS. In among the NMPs significantly higher plant height, leaf area index, dry matter accumulation, seed yield and net returns of mustard was recorded with application of 120 kg N ha-1 followed by 80 kg N ha-1 and 40 kg N ha-1. Based on the experimental results, it is inferred that weed free-check and pre- emergence application of Pendimethalin 0.75 kg ha-1 fb hand-weeding at 30 DAS along with 120 kg N ha-1 resulted in higher crop growth, productivity and profitability of mustard crop in semi- arid region of Kandahar, Afghanistan.
Effect of groundnut-based millet intercropping systems on growth and productivity of groundnut
A field experiment was conducted during kharif 2024 at S.V. Agricultural College, Tirupati, to evaluate the effect of groundnut-based millets intercropping systems on the growth and yield of groundnut. Ten treatments, including sole and intercropping systems with foxtail, finger, and little millets in 5:2 and 5:4 row ratios, were assessed using a randomized block design. Growth parameters such as plant height (52.0 cm), leaf area index (6.5), and dry matter (4638 kg ha-1) were significantly higher in the sole crop of groundnut. Results of the experiment indicated that higher groundnut pod and haulm yields were recorded in the sole crop of groundnut (2295 kg ha-1 and 3016 kg ha-1, respectively). Among the intercropping treatments, significantly higher pod and haulm yield (1976 kg ha-1 and 2689 kg ha-1, respectively), total number of pods plant-1 (22.1), number of filled pods plant-1 (16.3), 100-pod weight (110g), kernel weight (69 g) were recorded in groundnut + finger millet in the row proportion of 5:2. Intercropping with millets at a 5:2 ratio showed better compatibility and resource utilization. The study concluded that groundnut + finger millet (5:2) is the most effective system for maximizing yield under sandy loam soils in the Southern Agro-Climatic Zone of Andhra Pradesh.
Effect of irrigation scheduling and nitrogen fertilization on physiological growth indices of Chandrasur (Lepidium sativum L.)
A two-year field experiment was conducted during 2018–19 and 2019–20 at Krishi Vigyan Kendra, Sawai Madhopur to evaluate the effect of irrigation scheduling and nitrogen fertilization on growth parameters of Chandrasur (Lepidium sativum L.). The results revealed that three irrigations (25, 50 and 75 DAS) recorded the highest plant height at 60, 90 DAS and at harvest (60.28 cm, 91.08 cm and 102.01 cm, respectively), which was significantly superior to two irrigations (I2) and one irrigation (I1). Among nitrogen levels, the maximum plant height was observed with application of 80 kg N ha-¹, which was significantly higher than that recorded with 60 kg N ha-¹. In terms of dry matter accumulation (g plant-¹) at 30, 60, 90 DAS and at harvest, crop growth rate (g m-² day-¹), and relative growth rate (g g–¹ day-¹), the interaction effect of three irrigations (25, 50 and 75 DAS) in combination with 80 kg N ha-¹ was found to be superior over two irrigations (25 and 50 DAS) with 60 kg N ha-¹. The findings indicate that appropriate irrigation scheduling combined with optimum nitrogen fertilization significantly enhances growth performance and physiological efficiency of Chandrasur.
Yield performance of different pearlmillet varieties under organic nutrient management
A field experiment entitled “Yield performance of different pearlmillet varieties under organic nutrient management” was conducted at Agronomy farm, S.K.N. College of Agriculture, Jobner (Rajasthan) during the Kharif season, 2023 on loamy sand soil. The pearlmillet crop under the influence of variety RHB-233, being at par with RHB-234 significantly enhanced plant height, number of leaves plant-1 and dry matter accumulation plant-1 at harvest, LAI at 40 DAS, LAR at 30-60 DAS and NAR 30-60 DAS stage over RHB-223 and HHB-299. In variety RHB-233, improvement manifested in the production of higher effective tillers (2.67), ear-head length (20.79 cm) and 1000 grains weight (8.32 g) with the concomitant increase in productivity in terms of grain (2388 kg ha-1), stover (5960 kg ha-1) and biological yield (8348 kg ha-1). Results showed that application of 100% RDN through vermicompost + 3% panchgavya significantly improved growth parameters viz., plant height, number of tillers plant-1, number of leaves plant-1 and dry matter accumulation plant-1 at successive growth stages and yield attributes viz., effective tillers (2.77), earhead length (21.29 cm) and 1000-grains weight (7.90 g) thereby grain (2484 kg ha-1), stover (6147 kg ha-1) and biological yield (8632 kg ha-1) of pearlmillet crop over rest of the treatments.
Influence of potassium management and stress mitigating chemicals on yield, nutrient uptake and quality of mungbean [Vigna radiata (L.) Wilczek]
In the kharif season of 2022, a field experiment was carried out at S.K.N. College of Agriculture, Jobner, Rajasthan, using a factorial randomized block design to examine the impact of varying potassium levels and stress mitigating chemicals on yield attributes and nutrient uptake by mungbean cultivated in loamy sand soil. The study involved sixteen treatment combinations, each replicated three times, with four potassium levels (control, 20, 30 and 40 kg K2O/ha) and four stress mitigating chemicals (control, KNO3 @ 100 ppm, Thioglycolic acid @ 100 ppm and Kinetin @ 50 ppm). The application of 40 kg K2O/ha significantly increased number of pods/plant, number of seeds/pod, test weight and concentration of nitrogen in both seed and straw showing significant superiority to control and other preceding levels of potassium. The application of 40 kg K2O/ha remaining at par with 30 kg K2O/ha led to higher phosphorus and potassium concentration in seed and straw over control. Among stress mitigating chemicals tested, foliar application of TGA @ 100 ppm, applied at 30 and 45 days after sowing, reported significantly greater yield attributes and concentration of nitrogen and phosphorus in both seed and straw compared to control and KNO3,though it showed similar results to Kinetin @ 50 ppm. All stress mitigating chemicals did not have an impact on the potassium content in seed and straw but increased the total potassium uptake compared to the control while remaining comparable to one another.
Effect of split application of vermicompost and zinc sources on yield and nutrient uptake of greengram [Vigna radiata (L.) Wilczek] in semi-arid eastern plain of Rajasthan
Zinc deficiency and poor nutrient management are major constraints in arid and semi-arid region. For efficient nutrient management strategies involving vermicompost and zinc fertilization are required to improve soil fertility and crop yield. So the experiment was conducted during Kharif season of 2024 at S. K. N. College of Agriculture, Jobner, Jaipur (Rajasthan). The experiment consisting of four treatments of split application of vermicompost (Control, 100% RDV at sowing, 75% RDV at sowing + 25% RDV at 15 DAS and 50% RDV at sowing + 50% RDV at 15 DAS) and four sources of zinc application (Control, 5 kg Zn ha-1 through Zn-EDTA as soil application, 5 kg Zn ha-1 through ZnSO4.7H2O as soil application and 2.5 kg Zn ha- 1 through Zn-EDTA as soil application + 2.5 kg Zn ha-1 through ZnSO4.7H2O as soil application). The experiment was laid in a factorial randomized block design with three replications. The split application of vermicompost @ 75% RDV at sowing + 25% RDV at 15 DAS and zinc sources@5 kg Zn ha-1 through ZnSO4.7H2O as soil application, increased significantly (P=0.05) the grain yield, stover yield and biological yield, nutrient content and uptake in grain and stover of greengram. The interactive effect of N, P, K and Zn uptake in grain was significantly higher with combined application @ 50% RDV at sowing + 50% RDV at 15 DAS and 5 kg Zn ha-1 through ZnSO4.7H2O as soil application compared to other treatments. However, the increase was significant upto 75% RDV at sowing + 25% RDV at 15 DAS and 5 kg Zn ha-1 through ZnSO4.7H2O as soil application (VC2Zn2) which was found to be statistically at par with VC3Zn2 (50% RDV at sowing + 50% RDV at 15 DAS and 5 kg Zn ha-1 through ZnSO4.7H2O as soil application (VC3Zn2). We concluded on the basis of experimental findings that the combined application of 75% RDV at sowing + 25% RDV at 15 DAS + 5 kg Zn ha-1 through ZnSO4.7H2O as soil application with recommended dose of fertilizer.
Optimization of nitrogen and phosphorus nutrition for improved phenology, root dynamics, resource-use efficiency and profitability of red bean (Phaseolus vulgaris) in the semi-arid region of Afghanistan
An experiment was conducted at the experimental farm of Afghanistan National Agricultural Sciences and Technology University, Kandahar during Kharif 2020 to optimize nitrogen (N) and phosphorus (P) nutrition in irrigated red bean (Phaseolus vulgaris) for improved crop phenology, root dynamics, yield and resourceuse efficiency in semi-arid climate. Experimental treatments comprised of 4 different N-doses (0, 40, 80, 120 kg N/ha) and 04 different P-doses (0, 30, 60, 90 kg P2O5/ha) using split-plot design replicated thrice. In general, application of 120 kg N ha-1 and 90 kg P ha-1 had significantly effect on days taken for different phonological stages (maximum flowering stage, pod formation stage & physiological maturity stage) over control. Root length and dry root weight were significantly higher under treatment 120 kg N ha-1 and 90 kg P ha-1 at maximum flowering stage. Red bean seed yield (2.50; 2.46 t ha-1) was significantly higher under treatment 120 kg N ha-1 and 90 kg P ha-1, respectively. Again, the 120 kg N ha-1 and 90 kg P ha-1 exhibited maximum gross returns (AFN 180340; 177380 ha-1); net returns (AFN 115540; 111180 ha-1), respectively. The resource-use efficiency in terms of production and monetary– efficiency and water-use efficiency followed the similar trend as that of grain yield with highest magnitude under treatment 120 kg N ha-1 and 90 kg P ha- 1. Partial factor productivity of applied-N (PFPN) was significantly higher at N @ 40 kg ha-1 thereafter it showed a gradual decline till N @ 120 kg ha-1. The PFPP was significantly higher at P @ 30 kg ha-1. Overall, it was revealed that increase in N and P levels had positive impact on crop phenology with consistent and significant increase in red bean root parameters, productivity, profitability and resource-use efficiency with highest values in treatment 120 kg N ha-1 and 90 kg P ha-1. In nutshells, N @ 120 kg ha-1 and P @ 90 kg ha-1 may be recommended to the farmers for improved phenology, root dynamics, resource-use efficiency and profitability in semi-arid region of Afghanistan.
Precision nitrogen management for improved root architecture, micronutrient acquisition, and rice productivity in the northeastern hill region of India
Agriculture is the primary source of livelihood in the North-Eastern Hill (NEH) region of India, where rice, the staple food crop, holds paramount importance for farmers. However, declining productivity and low nutrient use efficiency have emerged as major constraints in the region. Most farmers continue to follow blanket fertilizer application practices, particularly for nitrogen (N), resulting in uneven and inefficient nutrient use. Precision nitrogen management (PNM), through the use of N-stress sensing tools, offers a promising solution by synchronizing N supply with crop demand. Further enhancement in N use efficiency (NUE) can be achieved by integrating nano-fertilizers, which to some extent allow for reduced N application rates without compromising crop performance. In this context, a field experiment was conducted at the ICAR Research Complex, Meghalaya, to evaluate the effects of PNM and nano-urea (NU) on rice productivity, root dynamics and micronutrient uptake. Results indicated that SPAD (Soil plant analysis development) and LCC (Leaf color chart) based N management save N, improves root quality, micronutrient uptake and grain yield, which was comparable to soil test crop response (STCR) based recommendations, where maximum N was applied. Notably, in the treatment 75% RDN+ 2NU spray, a 25% reduction in the recommended dose of N (RDN) was achievable, as the reduced N dose was effectively supplemented through two foliar sprays of NU, resulting in crop performance comparable to that obtained with 100% RDN. Overall, the study demonstrates that PNM and NU, to some extent, offer a sustainable and efficient strategy for improving rice productivity, root parameters and micronutrient uptake in the NEH region of India.
Evaluation of soil suitability for sugarcane in the State of Punjab – a case study
Agriculture accounts for a significant share of the country’s GDP and is a major source of income for millions of rural households. Cash crops play a crucial role in enhancing farm incomes and supporting overall economic growth. Among the cash crops, sugarcane is one of the important cash crops in India. In Punjab the natural resources are diminishing due to dominant rice-wheat based cropping system. Therefore, some alternate crops are need of time. Hence the present study was conducted to study the soil resources of Punjab for assessing the soil suitability for cultivation of sugarcane. The obtained results revealed that a 44.62% area is suitable for cultivation of sugarcane followed by 39.69% area revealed moderate suitability and 1.68% area revealed marginal suitability. Considering the results of study it can be concluded that the sugarcane crop is a promising alternate land use option for the local farmers in Rajpura block of Patiala district of Punjab.
Current and potential soil suitability of barley for crop diversification in IGP region of India: a case study
Soil resources of the study area were evaluated for current and potential soil suitability of barley under existing soil-site regime. Current soil suitability (actual suitability) revealed that 44121.0 ha area evaluated to be highly suitable (S1), whereas remarkable increase (22.9%) in S1 areas has been observed under potential soil suitability regime. Moreover, maximum acreage found to be moderately suitable (S2) for barley production under both current and potential suitability evaluation scenario. Potential soil suitability evaluation recorded significant increase in class S2 area (45.0%) over the existing acreage. The study identified the production constraints and suggested need based intervention including the apt agronomic measures to ensure best utilization of marginally suitable (S3) and presently unfit areas (N1) in due course of time. LMUs based soil management strategies, land evaluation enabled crop planning, and integrated approaches for nutrient and water management, application of soil amendments such as gypsum in salt-affected areas and farm forestry practices need to be included in the research and policy domains to ensure efficient utilization of land resources for sustainable barley production in the study area of IGP region.
Evolving trends in smart home activity recognition with edge computing and ethical best practices
Human Activity Recognition (HAR) in smart homes is a vital breakthrough in constructing intelligent systems for monitoring Activities of Daily Living (ADL). It improves healthcare, security, and minimize energy requirements. This study utilizes ARAS data to construct and test sophisticated predictive models for multiresident activity systems based on state-of-the-art machine learning classifiers, ensemble approaches, and deep neural network structures. We utilize advanced feature extraction and selection methods such as Information Gain, Recursive Feature Elimination (RFE), and Random Forest Importance to balance model performance and computational efficiency. Our work involves incorporating edge computing paradigms with ethical frameworks to respond to privacy issues and real-time processing needs. The hybrid architecture we put forth showcases improved performance with accuracy of 99.6% and 99.8% for households A and B respectively, while being low in latency and energy consumption. Additionally, we present thorough ethical guidelines and privacy-preserving methods to promote ethical deployment of HAR systems in home environments. Experimental verification on a variety of scenarios ensures the scalability and robustness of our method, qualifying it as a potential solution for next-generation smart home systems.
Relational analysis of farmers’ profile with their perception on capacity needs under NICRA villages
This study investigated the link between farmers’ personal and farming characteristics and their perception on capacity needs under the NICRA programme in Kerala and Karnataka. Data were collected from 160 farmers across four villages using interviews and analysed with descriptive statistics, correlation, and regression. Results showed that most farmers were smallholders, male, and had limited education, with marginal landholdings and mixed or diversified farming systems. Farmers’ perception of capacity needs was mainly influenced by extension contact, participation in training, education, and association with KVK activities. Extension contact was the strongest factor, especially in Karnataka, while education and KVK linkages were more important in Kerala. The findings suggest that frequent extension interaction, practical training, and suitable educational support are key for building farmer capacity in climate-resilient agriculture.
national innovations on climate resilient agriculture
Assessment of smallholder agrarian systems and the adoption of veterinary services and government schemes in Mirzapur, Uttar Pradesh
Livestock sustains rural livelihoods in Vindhyan region’s Mirzapur District, UP, where dairy dominates over secondary goats, sheep, and poultry, whose contributions to income, nutrition, and risk mitigation remain underexplored despite South Asian smallholder patterns. This survey of 576 households assesses their structure, management, inputs, and veterinary/government service adoption via structured data on ownership, breeds, production, feeding, and breeding, analyzed descriptively. In the study Vindhyan region’s Mirzapur District reveal dairy as the primary livestock pillar (52% priority), with goats (20% owners, mostly 1-2 indigenous animals for meat/milk at low yields of 0.5-2L/day sold Rs.40-60/L), sheep (>92% none, small flocks for meat/wool Rs.50-200/kg), and poultry (>90% none, backyard desi birds with sporadic eggs/meat) as marginal, subsistence assets amid high data gaps. Management relies on low-input feeds (berseem 30%, straws 36%, grazing 8.5%), mixed breeding (AI 31%, natural 23%), but veterinary use splits (29% formal, 46% informal/self), and government schemes remain low (<5% for insurance/credit/Kamdhenu yojna). These patterns emphasize needs for breed/feed/health upgrades and outreach to elevate small ruminants/poultry productivity and resilience. Based on these findings, improved smallholder livestock management—through breed enhancement, better feeding/health practices, and expanded veterinary/insurance access—can boost productivity, nutrition, and resilience, playing a crucial role in achieving sustainable development goals in Vindhyan region’s rural livelihoods.
Flower quality parameter as affected by moisture content during value addition through flower drying
Moisture content studies were carried out among sixteen flowers including selection of quality floral raw material for dehydrated value addition and product preparation. The results revealed that optimum floral moisture content directly influenced the quality, natural colour retention and shelf life of dry flowers. Moisture content varied 6.81% (helichrysum) to 15.23% (dahlia) based on flower texture, size and utility. In dry flowers, high moisture content (12 to 15%) than optimum levels lead to more shrinkage and microbial infestation with lesser shelf life, whereas very low levels of moisture (less than 5%) causes flower brittleness and shattering. Hence an optimum moisture content on dry weight basis (7-9 percent) was found optimum for quality dry flowers selection with higher shelf life of more than four years.
Yield and economics of safflower as influenced by different varieties and nitrogen levels under irrigated and rainfed conditions
A field experiment was carried out to study the Response of Safflower Varieties to Different Nitrogen Levels Under Irrigated and Rainfed Condition at College Farm, N. M. College of Agriculture, Navsari Agricultural University, Navsari during rabi 2022-23. The experiment comprised with sixteen treatments consisting irrigation conditions (I1-irrigated and I2- rainfed) and four levels of nitrogen (N1- 0 kg N ha-1, N2- 30 kg N ha-1, N3- 60 kg N ha-1 and N4- 90 kg N ha-1) as main plot treatment and two varieties (V1-PBNS- 12 and V2- PBNS- 86) in sub-plot with three replications in a split-split plot design. The results revealed that the seed yield (1466 kg ha-1), stover yield (3300 kg ha-1), gross return (Rs 92971 ha-1), net return (Rs 56116 ha-1) and B:C ratio (2.52) recorded significantly superior under irrigated condition as compare to rainfed condition. Among the different levels of nitrogen application, the seed yield (1490 kg ha-1), stover yield (3278 kg ha-1), gross returns (Rs 94224 ha-1) and net returns (Rs 57987 ha-1) with benefit cost ratio of 2.60 was recorded significantly superior with the application of 90 kg N ha-1. In case of variety, the seed yield (1302 kg ha-1), stover yield (2972 kg ha-1), gross returns (Rs 82779 ha-1) and net returns (Rs 46962 ha-1) with benefit cost ratio 2.31 were recorded significantly superior in variety PBNS-12 than PBNS-86.
Correlation and path analysis studies on yield and its component traits in greengram (Vigna radiata L.)
In the present investigation, 31 mungbean genotypes were evaluated for different quantitative traits to determine relationships among yield and some yield components using direct (variability, heritability, and genetic advance) and indirect selection parameters (correlation and path coefficient analysis). Significant genetic variations were observed among the genotypes for pods/plant, days to 50% flowering, days to maturity, plant height, 100-seed weight, and seed yield/plant. The magnitude of correlation revealed that seed yield/plant had a positive and highly significant correlation with plant height, number of primary branches, number of clusters per plant, number of pods per plant, biological yield, and 100-seed weight. Path coefficient analysis indicated that 100- seed weight, number of primary branches, plant height, and pod length had the maximum direct positive effect on seed yield/plant. Consequently, based on the genetic parameter correlation and path analysis, a number of effective branches, pods/plant, and 100-seed weight should be given significant precedence while formulating a selection strategy for effective improvement of mungbean varieties.
Response of pearlmillet (Pennisetum glaucum L.) hybrids to different doses of fertilizer on yield and economics under irrigated condition in Western Rajasthan
A field experiment was conducted during Kharif, 2022 at the Instructional Farm, College of Agriculture, Swami Keshwanand Rajasthan Agricultural University, Bikaner to study the response of pearlmillet (Pennsisetum glaucum L.) hybrids to different doses of fertilizer under irrigated condition in western Rajasthan. The treatments comprising four fertility levels (control, 60:40:20, 80:50:30 and 100:60:40 N:P:K kg ha-1) in main plots and five hybrids (RHB-177, HHB-299, MPMH-17, 86M90 and KPH-6277) in sub plots making 20 treatment combinations was laid out in split plot design with three replications. The results showed that in fertility level of 80:50:30 N:P:K kg ha-1 significantly higher yield attributes, grain and stover yield as well as net return and B: C ratio over rest of the fertility levels but it was remained statistically at par with fertility level of 100:60:40 N:P:K kg ha-1 in this regard. Further data showed that highest fertilizer use efficiency of fertility level recorded with 80:50:30 N:P:K kg ha-1 followed with increased the fertility level decreased the fertilizer use efficiency. Among pearl millet hybrids KPH-6277 recorded significantly higher grain and stover yield, net returns and B:C ratio over rest of the hybrids but 86M90 hybrid was found significantly at par in this regard. Interaction effect of fertility levels and pearl millet hybrids also found significant on grain and stover yield, gross and net returns and B:C ratio which were significantly higher under application of 80:50:30 N:P:K kg ha-1 along with KPH-6277 hybrid as compared to all other treatment combinations and it was at par with 100:60:40 N:P:K kg ha-1 along with KPH-6277 hybrid. Based on a one-year finding, it is determined that under irrigated condition in western Rajasthan, pearl millet hybrid KPH-6277 when fertilized with 80:50:30 N:P:K kg ha-1 proved its advantage by registering a higher B:C ratio and yielding grain and stover at a level consistent with fertility level of 100:60:40 N:P:K kg ha-1.
Effect of potassium and plant geometry on the growth and yield of cumin (Cuminum cyminum L.) in Helmand Afghanistan
A field experiment was carried out at the research farm of Helmand University, Afghanistan during December 2021 to April 2022 to investigate the effect of different potassium levels (0, 40, 80,120,160 and 200 kg K2SO4 ha-1) and plant geometries (20 cm×10 cm and 30 cm ×10cm) on the growth and yield of cumin (Cuminum cyminum L.). The experiment was laid-out in a randomized complete block design (RCBD) replicated three times. The results revealed that wider spacing (30 cm×10 cm) exhibited greater plant height (33.56 cm), seed yield 472.6 kg ha-1, 1000-seed weight (3.55 g), dry matter accumulation (3.79 g plant-1), umbels plant-1 (26.1), seeds umbel-1 (23.7), umbellate umbel-1 (5.11), straw yield (767.16 kg ha-1), biological yield (1252.9 kg/ha), harvest index (37.5 %), and B: C ratio (2.73), production efficiency (4.29 kg ha-1 day-1), water-use efficiency (1.02 kg ha-1 mm-1) and monetary efficiency (756.3 AFN ha-1 day -1). Application of potassium at the highest rate (200 kg K2SO4 ha-1) recorded the highest growth, yield attributes, yield, economics and resource-use efficiencies (production efficiency, water-use efficiency and monetary efficiency). Likewise, plots that were treated with wider spacing and the highest rate of potassium (200 kg K2SO4 ha-1) produced higher yield, and yield components (200 >160 >120 >80 >40 > control). However, the difference between 160 and 200 kg K2SO4 ha-1 was not significant. Overall, results of this study showed that cumin growth, yield and yield components increased with wider spacing (30 cm × 10 cm) and with the application of 160-200 kg K2SO4 ha-1 potassium level; seed yield and important yield attributes did not increase significantly beyond 160 K2SO4 ha-1. Thus, the study suggests that cumin should be planted at (30 cm × 10 cm) and fertilized with 160 K2SO4 ha-1.
LeafNet-CBAM: a lightweight attention-enhanced network for weed image classification
Accurate weed identification is essential for precision cotton farming, as early-stage weed infestation significantly affects crop yield and resource efficiency. This study proposes LeafNet (L-Net), a lightweight and stable convolutional neural network (CNN) designed for cotton-weed image classification under real-field conditions. L-Net integrates depth wise separable convolutions with Convolutional Block Attention Module (CBAM) and residual connections to enhance discriminative feature learning while maintaining low computational complexity. A cotton field image dataset was collected under varying illumination and background conditions and augmented to improve robustness. Experimental results demonstrate that L-Net outperforms EfficientNet-B0, ResNet-50, and MobileNet, achieving an accuracy of 98.99%, a recall of 99.17%, and an F1-score of 99.00%, with minimal false classifications. Ablation and confusion matrix analyses confirm the effectiveness of attention and residual learning in improving model stability and generalization. The proposed L-Net architecture offers a reliable and efficient solution for real-time and edge-based weed detection in precision agriculture.
Smart harvest: a multicrop, rainfall-integrated model comparison framework for yield prediction
This work introduces Smart Harvest, a predictive analytics model for predicting rice, wheat, jowar, and bajra crop yields. The model investigates the rainfall impact on yield through the use of historical production and climatic data. ARIMA, ARIMAX, SVR, ANN, and Random Forest models are considered and compared for performance and accuracy. The findings indicate the robustness of rainfall-integrated models in enhancing prediction accuracy. This method facilitates data-driven farm planning and risk management.
Inter-trait relation studies for quantative production of marigold
Correlation studies were carried out among twenty important parameters of marigold for different yield attributing traits in order to differentiate the contribution made by each parameter towards total flower yield. The results revealed that the genotypic correlation were higher than the phenotypic correlation for the characters obtained, indicating the high heritable nature of the characters. Number of leaves per plant number of primary branches per plant, number of flowers per plant and average fresh weight of flower were reported highly significant and positive correlation with flower yield per plant, whereas stem diameter and 100 seed weight were found significant and positive correlated with flower yield per plant at both genotypic and phenotypic level. Since these association are in desirable direction, hence selection of these traits may ultimately improve the total flower yield.
Morphological, physiological and bio-chemical characterization of amaranth (Amaranthus spp.) genotypes
The Present investigation was carried out with 12 amaranth genotypes including two check variety (Pusa Kirti and Pusa Kiran) during Rabi 2022-2023 in RBD with three replications at Field Experimentation Centre, Department of Genetic and Plant Breeding, Naini Agriculture Institute, Sam Higginbottom University of Agriculture, Technology and Sciences, Prayagraj, (U.P.), to evaluate Amaranth (Amaranthus spp.) genotypes for Morphological, Physiological and Bio-Chemical parameters. Analysis of variance showed highly significant differences among 12 Amaranth genotypes for 13 Morphological, 2 Physiological and 2 Bio- Chemical characteristics. Genotype IC-35578 was identified as the best genotype for 7 Morphological and 2 Physiological characters, and genotype IC-35583 was identified as the best genotype for 9 Morphological and 2 Bio-Chemical characters.
Micro-irrigation for climate-smart agriculture: environmental footprints, greenhouse gas mitigation, and policy pathways
Micro-irrigation, such as drip and sprinkler, is at the cutting edge of modern water resource development, with the current challenges of climate change, the shortage of water resources, and the increasing greenhouse gas emissions from agriculture sector. This comprehensive literature review synthesizes data on the efficacy of precision drip micro-irrigation in reducing CO2 emissions due to energy consumption with respect to flood and sprinkler irrigations, indicating a significant reduction in N2O emissions due to optimal soil moisture maintenance, thereby reducing denitrification. In flood-dominated rice ecosystems prevalent in large parts of India; subsurface drip irrigation can significantly lower methane emissions by encouraging a rhizosphere rich in oxygen, in turn, favouring methanotrophic bacteria. In the Indo-Gangetic Plains (IGP), with rice-wheat cropping in Punjab and Haryana having exploited deep groundwater aquifers to their extent, estimates of CO2-equivalent emissions per hectare annually are substantial. With sustained increases in crop productivity gains and with economically advantageous benefit-cost ratio (BCR) values because of subsidies in Pradhan Mantri Krishi Sinchayee Yojana, this initiative is important to harness what is achievable through this system from a technical potential perspective. Life cycle energy studies show that drip irrigation uses much less total energy than sprinkler systems. Scaling-up pathways of PM-KUSUM solar pumping, Digital Agriculture Mission IoT platforms, can lead to a faster and wider diffusion of drip irrigation. A large scale adoption of micro-irrigation can make agriculture environmentally safe, productive and sustainable.
Assessing the impact of climate change on agricultural productivity in Farah Province, Afghanistan – A case study
This research investigates the impact of climate change on agricultural productivity. To analyze this impact, factors such as farmers’ awareness of climate change, sustainable farming methods, access to financial resources, and farmers’ experience were examined. The statistical population of this research included farmers and agricultural experts in the target region, from whom 385 individuals were randomly selected. Statistical methods such as multiple linear regression, Cronbach’s alpha test, Kolmogorov-Smirnov test, and ttests and F-tests were used for data analysis. The results of the multiple linear regression showed that 61.2% of the changes in agricultural productivity are explained by the variables of awareness of climate change, the use of sustainable farming methods, access to financial resources, and farming experience (R2=0.612). The F-statistic was 78.451 with a significance level of p-value = 0.000, indicating the significance of the regression model. The t-tests for awareness of climate change (t = 4.205, p-value = 0.000), sustainable farming methods (t = 3.753, p-value = 0.000), access to financial resources (t = 3.112, p-value = 0.002), and farmers’ experience (t = 2.014, p-value = 0.045) showed that all these factors significantly affect agricultural productivity. Furthermore, the Cronbach’s alpha test showed a value of 0.876, indicating high reliability of the research instrument. Overall, the findings of this research suggest that increasing farmers’ awareness, using sustainable farming methods, providing access to financial resources, and leveraging farmers’ experience can help improve agricultural productivity and reduce the negative effects of climate change. Consequently, to address the adverse impacts of climate change and enhance agricultural productivity, it is recommended that farmers benefit from more training, adequate financial resources, and modern technologies.
The role of organic agriculture in sustainable development – A case study of Farah Province, Afghanistan
Organic agriculture, as a sustainable production method, has garnered significant attention in recent years. This research investigates the role of organic agriculture in sustainable development by evaluating its impacts on the conservation of natural resources, reduction in chemical inputs, and improvement in the quality of agricultural products. A linear regression method was employed to analyze the data collected from a statistical population of 385 farmers actively involved in organic agriculture. The results indicate that the adoption of organic farming methods and the conservation of natural resources are significantly correlated with sustainable development. The coefficient for the adoption of organic farming methods was 0.65, and the coefficient for the conservation of natural resources was 0.55, demonstrating a positive and substantial influence of these factors on sustainable development. Furthermore, the use of natural fertilizers showed a significant impact on sustainable development with a coefficient of 0.40. In contrast, the reduction in pesticide use had a minimal and statistically insignificant impact on sustainable development (coefficient of 0.15). The ANOVA test revealed that the regression model is statistically significant overall, explaining 63% of the variance in sustainable development. Based on these findings, organic agriculture, through the conservation of natural resources, reduction in chemical use, and improvement in product quality, can play a crucial role in achieving sustainable development goals.