Modern Agricultural Practices Research Articles

Impact of Mechanized Crop Establishment Techniques on Growth, Yield, and Microbial Dynamics under Rice-Wheat Cropping System: A Review

The rice-wheat cropping system, predominant across the Indo-Gangetic plains, generates a substantial volume of crop residue, with an annual yield of 7-9 tonnes per hectare of rice residue. Effective management of this residue, whether in-situ or ex-situ, has become an urgent necessity. However, the economic feasibility of transporting residue beyond 20 km from the field is limited. Consequently, in-field residue management through the adoption of specialized machinery has emerged as an imperative solution. The narrow window between paddy harvesting and wheat sowing, compounded by labor scarcity during peak periods, underscores the need for mechanized crop establishment techniques. Machines such as happy seeders, super seeders, turbo seeders, spatial drills, and seed-cum-fertilizer drills are crucial tools in this regard. This paper examines the benefits of mechanized crop establishment techniques on wheat growth, productivity, and soil biological health within the rice-wheat cropping system. These techniques have revolutionized agricultural practices by significantly influencing growth dynamics, yield parameters, and microbial ecology. The adoption of precision seed drills and mechanized tillage equipment has transformed traditional farming methods, facilitating efficient seed placement, soil preparation, residue incorporation, and weed management. This has resulted in improved crop growth parameters, enhanced yield dynamics, better root development, increased nutrient uptake, and overall plant vigor. Furthermore, reduced soil disturbance and decreased weed pressure associated with mechanized operations have created a conducive environment for beneficial microbial communities to thrive. The integration of mechanized crop establishment techniques has a positive impact on both crop productivity and sustainability, highlighting their importance in modern agricultural practices within the rice-wheat cropping system of the Indo-Gangetic plains.

A study on nickel application methods for optimizing soybean growth

Fertilization with nickel (Ni) can positively affect plant development due to the role of this micronutrient in nitrogen (N) metabolism, namely, through urease and NiFe-hydrogenase. Although the application of Ni is an emerging practice in modern agriculture, its effectiveness strongly depends on the chosen application method, making further research in this area essential. The individual and combined effects of different Ni application methods—seed treatment, leaf spraying and/or soil fertilization—were investigated in soybean plants under different edaphoclimatic conditions (field and greenhouse). Beneficial effects of the Soil, Soil + Leaf and Seed + Leaf treatments were observed, with gains of 7 to 20% in biological nitrogen fixation, 1.5-fold in ureides, 14% in shoot dry weight and yield increases of up to 1161 kg ha−1. All the Ni application methods resulted in a 1.1-fold increase in the SPAD index, a 1.2-fold increase in photosynthesis, a 1.4-fold increase in nitrogenase, and a 3.9-fold increase in urease activity. Edaphoclimatic conditions exerted a significant influence on the treatments. The integrated approaches, namely, leaf application in conjunction with soil or seed fertilization, were more effective for enhancing yield in soybean cultivation systems. The determination of the ideal method is crucial for ensuring optimal absorption and utilization of this micronutrient and thus a feasible and sustainable management technology. Further research is warranted to establish official guidelines for the application of Ni in agricultural practices.

Legal Frameworks for the Assessment of Agricultural Lands

This study examines the legal frameworks governing the assessment of agricultural lands, focusing on the challenges and implications of existing regulations and suggesting improvements for more effective land management. Assessing agricultural land is crucial for determining its value, taxation, and eligibility for government subsidies, which directly impacts agricultural productivity and sustainability.The research methodology involves a comparative analysis of legislation in different jurisdictions, highlighting best practices and identifying gaps in current legal frameworks. Through this analysis, the study addresses how legal provisions align with the practical needs of agricultural development and land conservation, as well as discussing the impact of these laws on farmers, landowners, and the broader economic landscape.Key findings reveal that many existing laws are outdated and do not adequately accommodate modern agricultural practices or the challenges posed by climate change. The study also identifies a lack of consistency in the application of these laws, leading to disparities in land assessment and management across regions.Recommendations include integrating advanced geographic information systems (GIS) for more precise land valuation, adopting environmentally sustainable practices in legal criteria, and enhancing legal clarity to reduce administrative burdens on landowners.This research is intended for policymakers, legal experts, and stakeholders in the agricultural sector. It provides a comprehensive overview of the legal issues surrounding agricultural land assessment and proposes actionable solutions to enhance the effectiveness of these legal frameworks. By reforming agricultural land assessment laws, countries can better support their agricultural sectors, promoting economic stability and sustainable development.

Aerosol-PM2.5 Dynamics: in-situ and satellite observations under the influence of regional crop residue burning in post-monsoon over Delhi-NCR, India

The increasing air pollution in the urban atmosphere is adversely impacts the environment, climate and human health. The alarming degradation of air quality, atmospheric conditions, economy and human life due to air pollution needs significant in-depth studies to ascertain causes, contributions and impacts for developing and implementing an effective policy to combat these issues. This work lies in its multifaceted approach towards comprehensive understanding and mitigating severe pollution episodes in Delhi and its surrounding areas. We investigated the aerosol dynamics in the post-monsoon season (PMS) from 2019-2022 under the influence of both crop residue burning and meteorological conditions. The study involves a broad spectrum of factors, including PM2.5 concentrations, active fire events, and meteorological parameters, shedding light on previously unexplored studies. The average AOD550 (0.799) and PM2.5 concentration (140.12 μg/m³) were the highest in 2019. PM2.5 was higher from mid-October to mid-November each year, exceeding the WHO guideline of 15 μg/m³ (24 hours) by 27 to 34 times, signifying a public health emergency. A moderate to strong correlation between PM2.5 and AOD was found (r = 0.650) in 2021. The hotspot region accounts for almost 50% (2019), 47.51% (2020), 57.91% (2021) and 36.61% (2022) of the total fire events. A statistically significant negative non-linear correlation (r) was observed between wind speed (WS) and both AOD and PM2.5 concentration, influencing air quality over the region. HYSPLIT model and Windrose result show the movement of air masses predominated from the North and North-West direction during PMS. This study suggest to promotes strategies such as alternative waste management, encouraging modern agricultural practices in hot-spot regions, and enforcing strict emission norms for industries and vehicles to reducing air pollution and its detrimental effects on public health in the region and also highlights the need for future possibilities of research to attract the global attention.

Numerical Prediction Uncertainty and Data Worth Analysis of Solute Transport in an Agricultural Clay Till Setting With Preferential Flow

AbstractWith modern agricultural practices, it is essential to quantify flow and solute transport fluxes by numerical models and associated predictions. A major challenge in modeling preferential flow settings is the ability to constrain the often numerous parameters needed to physically represent these systems. Following this, there is a lack of understanding of what parameters and observations carry the most worth for a model to reduce its prediction uncertainty. Here, first‐order second moment (FOSM) analyses were used for a heavily monitored clay till field with preferential flow to investigate which parameters and observation types contribute the most to reducing the uncertainty of bromide predictions at various depths. Using a multi‐objective regularized optimization approach, a 1‐D preferential flow model was calibrated and subjected to FOSM analyses. Key parameters contributing to the prediction uncertainty of bromide concentrations in 0.25–3 m were limited to the lower boundary condition, the mass transfer coefficient, the hydraulic conductivity of the micro‐ and macropore, the macropore porosity, and the water content at wilting point. The data with the largest worth and ability to reduce the pre‐calibration prediction uncertainty were concentration observations closest to the sought prediction depth, drain concentrations, and averaged water table measurements from the entire field. The post‐calibration prediction uncertainty was increased primarily by removing concentration observations closest to the prediction depths. While this study provided new insights into parameter importance and data worth further research is required to understand if these findings apply broadly to clay till settings (or any soil setting) with preferential flow.

An Empirical Analysis of the Adoption of Hi-Tech Farming Techniques Among the Farmers of the Eastern Uttar Pradesh Belt

Like in every sector, the agriculture sector also shows numerous technological advancements every now and then and it is expected from farmers to incorporate the same and increase the crop yields and keep themselves up-to-date for meeting up any type of competitions & contingencies as well. A lot has been done in the agricultural sector to improve cultivation but Indian farmers still rely on the traditional practices. Farming is still not regarded as a secure source of income in India. For Indian agriculture to become more profitable and sustainable, smart farming is essential. The farmer breed will soon go extinct without getting into smart and high-tech farming. Though Agropreneurs have started taking baby steps in India with respect to smart farming, it is still a silent revolution in India as compared to other countries because of lack of awareness and confidence. In this paper a study has been conducted in order to identify the inclination of farmers towards new technologies when it comes to agriculture from the Eastern Uttar Pradesh belt. At the same time farmers have also been inquired about the limitations and the challenges faced by them in the traditional farming system. During the survey of this study farmers have also been made aware how innovative modern agricultural practices doubles the crop yield which is not only beneficial to meet the domestic needs but can also be exported worldwide adding to the GDP of the country which could be of economic importance to the nation.

From growth inhibition to ultrastructural changes: Toxicological assessment of lambda cyhalothrin and fosetyl aluminium against Bacillus subtilis and Pseudomonas aeruginosa

In modern agricultural practices, agrochemicals and pesticides play an important role in protecting the crops from pests and elevating agricultural productivity. This strategic utilization is essential to meet global food demand due to the relentless growth of the world's population. However, the indiscriminate application of these substances may result in environmental hazards and directly affect the soil microorganisms and crop production. Considering this, an in vitro study was carried out to evaluate the pesticides' effects i.e. lambda cyhalothrin (insecticide) and fosetyl aluminum (fungicide) at lower, recommended, and higher doses on growth behavior, enzymatic profile, total soluble protein production, and lipid peroxidation of bacterial specimens (Pseudomonas aeruginosa and Bacillus subtilis). The experimental findings demonstrated a concentration-dependent decrease in growth of both tested bacteria, when exposed to fosetyl aluminium concentrations exceeding the recommended dose. This decline was statistically significant (p < 0.000). However, lambda cyhalothrin at three times of recommended dose induces 10% increase in growth of Pseudomonas aeruginosa (P. aeruginosa) and 76.8% decrease in growth of Bacillus subtilis (B. subtilis) respectively as compared to control. These results showed the stimulatory effect of lambda cyhalothrin on P. aeruginosa and inhibitory effect on B. subtilis. Pesticides induced notable alterations in biomarker enzymatic assays and other parameters related to oxidative stress among bacterial strains, resulting in increased oxidative stress and membrane permeability. Generally, the maximum toxicity of both (P. aeruginosa and B. subtilis) was shown by fosetyl aluminium, at three times of recommended dose. Fosetyl aluminium induced morphological changes like cellular cracking, reduced viability, aberrant margins and more damage in both bacterial strains as compared to lambda cyhalothrin when observed under scanning electron microscope (SEM). Conclusively the, present study provide an insights into a mechanistic approach of pyrethroid insecticide and phosphonite fungicide induced cellular toxicity towards bacteria.

Deep Learning Algorithms for IoT Based Crop Yield Optimization

Precision agriculture, with its objectives of optimizing crop yields, decreasing resource waste, and enhancing overall farm management, has emerged as a revolutionary technology in modern agricultural practices. The advent of deep learning techniques and the Internet of Things (IoT) has brought about a paradigm shift in monitoring, decision-making, and predictive analysis within the agriculture industry. This review paper investigates the relationship between deep learning, the (IoT), and agriculture, with an emphasis on how these three domains might work together to optimize crop yields through intelligent decision-making. The integration of deep learning techniques with  (IoT) technology for precision agriculture is thoroughly analyzed in this study, covering recent developments, obstacles, and possible solutions. The paper investigates the role of deep learning algorithms in analyzing the vast amounts of data generated by IoT devices in agriculture. It scrutinizes various deep learning models such as convolutional neural networks (CNNs), recurrent neural networks (RNNs), and their variants applied for crop disease detection, yield prediction, weed identification, and other crucial tasks. Furthermore, this review critically examines the integration of IoT-generated data with deep learning models, highlighting the synergistic benefits in enhancing agricultural decision-making, resource allocation, and predictive analytics. This review underscores the pivotal role of IoT and deep learning techniques in revolutionizing precision agriculture. It emphasizes the need for interdisciplinary collaboration among agronomists, data scientists, and engineers to harness the full potential of these technologies for sustainable and efficient farming practices.

A Study on Agricultural Loans offered by NABARD to Farmers

This study delves into the comprehensive landscape of agricultural loans disbursed by the National Bank for Agriculture and Rural Development (NABARD) to farmers in India. The research scrutinizes the varied purposes for which these loans are extended, encompassing crop cultivation, animal husbandry, dairy farming, poultry, fisheries, and agro-processing. Emphasizing the different loan types – short-term, medium-term, and long-term – the investigation explores the interest rates associated with each category and evaluates the role of government subsidies in enhancing affordability. Additionally, the study investigates the credit delivery mechanism facilitated by NABARD through cooperative banks, regional rural banks, and commercial banks, ensuring an inclusive approach to reach farmers across diverse strata. The research underscores the technological impetus provided by NABARD, encouraging farmers to adopt modern agricultural practices and technologies. Special attention is given to risk mitigation measures, including crop insurance, designed to shield farmers from losses arising due to unforeseen circumstances. Keywords: NABARD, Agricultural Loans, Farmer Financing, Credit Delivery, Government Subsidies, Rural Development, Risk Mitigation, Financial Inclusion, Technological Adoption, Indian Agriculture.

MiRNA Dynamics for Pest Management: Implications in Insecticide Resistance.

Utilizing chemical agents in pest management in modern agricultural practices has been the predominant approach since the advent of synthetic insecticides. However, insecticide resistance is an emerging issue, as pest populations evolve to survive exposure to chemicals that were once effective in controlling them, underlining the need for advanced and innovative approaches to managing pests. In insects, microRNAs (miRNAs) serve as key regulators of a wide range of biological functions, characterized by their dynamic expression patterns and the ability to target genes. Recent studies are increasingly attributed to the significance of miRNAs in contributing to the evolution of insecticide resistance in numerous insect species. Abundant miRNAs have been discovered in insects using RNA sequencing and transcriptome analysis and are known to play vital roles in regulation at both the transcriptional and post-transcriptional levels. Globally, there is growing research interest in the characterization and application of miRNAs, especially for their potential role in managing insecticide resistance. This review focuses on how miRNAs contribute to regulating insecticide resistance across various insect species. Furthermore, we discuss the gain and loss of functions of miRNAs and the techniques for delivering miRNAs into the insect system. The review emphasizes the application of miRNA-based strategies to studying their role in diminishing insecticide resistance, offering a more efficient and lasting approach to insect management.

Indigenous agriculture in Brazil: review (2011-2021)

Modern agricultural practices have caused severe impacts on nature, especially in traditional communities such as indigenous peoples, leading to the loss of knowledge about traditional agriculture. The objective of this study was to carry out a bibliographical survey of works on indigenous agriculture in Brazil in the period between 2011 and 2021. Papers in the form of thesis, dissertations and abstracts were excluded, as well as articles that, despite including the term indigenous agriculture in the text, did not address the subject as the main theme. The selected articles were analyzed in order to determine the main agricultural practices used by indigenous people in Brazil. Data analysis took place in a qualitative manner. The analyzed studies covered 69 ethnic groups and 87 ethnospecies were used in in their agriculture. Cassava (Manihot esculenta Crantz) stood out as the most important species. The plantations are established in backyards, on the outskirts of the village or in coivara (slash-and-burn) fields. The choice of location for the fields and the planting of species are based on the traditional knowledge of each ethnic group. Cutting, burning, planting, cleaning, and harvesting actions are generally governed by the seasons. Religious influences are also cited in some ethnicities. The analysis of the word cloud presents the main themes addressed in the publications and demonstrates the undeniable link between issues involving the environment and the traditional knowledge when the central theme is indigenous peoples. The works suggest that many ethnic groups preserve their traditional agricultural practices, however the influence and changes caused by the arrival of modern agriculture are also perceived and caused an impact on the eating habits of several ethnic groups.

Vermicompost Leachate-Based Biostimulant and its Effects on Physiological Variables and Yield of Different Crops in Manabí, Ecuador

Using large volumes of synthetic chemical fertilizers is a general practice in modern agriculture at a high economic and environmental cost. Biostimulants have become an alternative to this routine due to their ability to stimulate plant physiological processes without polluting soil and water. In Ecuador, however, little research has been carried out on the effect of biostimulants on the yield of crops of agricultural interest. The objective of this research was to determine the effect of foliar application of a biostimulant based on bovine manure vermicompost (VCLB) leachates on physiological variables and the yield of corn, cotton, and peanuts under field conditions and chard and five pepper hybrids in semi-protected cultivation under the agro-climatic conditions of the province of Manabí, Ecuador. The nine experiments carried out with the species and hybrids included various dilutions of VCLB and controls consisting of fertilization with nitrogen, phosphorus, and potassium, depending on the species, and soil without fertilizer. In all species, VCLB-induced plant length, chlorophyll content, and crop yield exhibit equal or higher statistical differences than those achieved under chemical fertilization (NPK). These results demonstrate the potential of this biostimulant as a sustainable alternative to produce these crops, reducing potentially the adverse effects of production on the environment under the tropical conditions of Manabí, Ecuador. We recommend corroborating these results with production-scale research.

Population declines of a widespread amphibian in agricultural landscapes.

Modern agricultural practices are suspected to play a major role in the ongoing erosion of biodiversity. In order to assess whether this biodiversity loss is linked to past habitat modifications (e.g. land consolidation) or to current consequences of modern agriculture (e.g. use of agrochemicals), it remains essential to monitor species that have persisted in agricultural landscapes to date. In this study, we assessed the presence, abundance and recent population trends of one such species, the spined toad (Bufo spinosus) along a gradient of habitats from preserved (forests) to highly agricultural sites in rural Western France. Our results showed that both presence and abundance of spined toads were markedly lower in reproductive ponds surrounded by intensive agriculture. The most salient result of our study is the ongoing decline of this species in farmland habitats. Indeed, this result suggests that unknown factors are currently affecting a widespread terrestrial amphibian previously thought to persist in agricultural landscapes. These factors have recently induced strong population declines over the course of a few years. Future investigations are required to identify these factors at a time when anthropogenic activities are currently leading to unprecedented rates of biodiversity loss.

Fallen apple detection as an auxiliary task: Boosting robotic apple detection performance through multi-task learning

In modern agricultural practices, advanced machine learning techniques play a pivotal role in optimizing yields and management. A significant challenge in orchard management is detecting apples on trees, which is essential for effective harvest planning and yield estimation. The YOLO series, especially the YOLOv8 model, stands out as a state-of-the-art solution for object detection, but its potential in orchards remains untapped. Addressing this, our study evaluates YOLOv8’s capability in orchard apple detection, aiming to set a benchmark. By employing image augmentation techniques like exposure, rotation, mosaic, and cutout, we lifted the model's performance to a state-of-the-art level. We further integrated multi-task learning, enhancing tree apple detection by also identifying apples on the ground. This approach resulted in a model with robust accuracy across evaluation metrics. Our results underscore that the YOLOv8 model achieves a leading standard in orchard apple detection. When trained for both tree and fallen apple detection, it outperformed the one when trained exclusively for the former. Recognizing fallen apples not only reduces waste but could also indicate pest activity, influencing strategic orchard decisions and potentially boosting economic returns. Merging cutting-edge tech with agricultural needs, our research showcases the promise of multi-task learning in fruit detection with deep learning.

Assessment of soil microbial diversity and soil enzyme activities under inorganic input sources on maize and rice ecosystems

BackgroundTo increase crop productivity, modern agricultural practices comprises fertilizers, algaecides, herbicides and fungicides. ObjectiveThe purpose of this study was to evaluate the effects of soil microbial population and soil enzyme activity by the use of fertilizer in maize and inorganic input in the rice ecosystem. MethodsA field experiment (2021 to 2023) was carried out using synthetic fertilizer doses with maize crops followed by rice crops using inorganic inputs. Soil microbial population and enzyme activities were examined. ResultsMaize field experiment revealed that the plots treated with 75 % Standardized Dose of Fertilizer (SDF) of NPK had the highest populations of diazotrophs (124 × 105cfu / g), Phosphobacteria (66.33 × 105cfu / g), and Azospirillum (0.409 × 105 MPN / g) than 100 % and 150 % SDF of NPK. The soil enzyme activity was higher in the unfertilized control plot than fertilized plot. These experimental results revealed that a low amount of fertilizer and no fertilizers favour the growth of soil microorganisms and soil enzyme activities, respectively. Followed by the rice field experiment, revealed that the soil microbial population was decreased by the application of inorganic inputs viz., fertilizer, algaecide, herbicide and fungicide. However, the maximum soil microbial population was found in algaecide application followed by herbicide and fungicide. ConclusionThe field experiment concluded that soil microbial population and enzyme activity were affected by inorganic amendments. Less inorganic fertilizers and no fertilizers improve soil microbial activities and soil enzyme activities.

The role of technology in the water–energy–food nexus. A case study: Kerinthos, North Euboea, Greece

The role of technology in the water–energy–food nexus. A case study: Kerinthos, North Euboea, Greece

Biostimulants and Microbial Bioformulations

Agricultural biostimulants enhance crop performance through improved nutrient uptake and increased resilience. These substances positively influence plant metabolism, promoting superior photosynthesis and nutrient absorption. They also contribute to soil health. Parameters such as dry matter yield were closely examined to evaluate the performance of kale crops under the influence of the biostimulant, providing insights into its potential benefits within both conventional and regenerative farming contexts. These glasshouse trials were carried out in the Department of Botany at the University of Otago, along with field trials on Lake Hawea and Glen Dene Stations. Bacteria samples were prepared in the Centre for Innovation before being planted out onto the trials. Information for the report was gathered from several sources including journals, literature reviews, on field trials, and laboratory visits at the University of Otago. Embracing biostimulants aligns with sustainable agriculture, offering an eco-friendly approach. They complement traditional fertilizers, optimizing effectiveness, and fostering early plant development. Rye seeds coated with beneficial microbes represent an innovative application, promoting nutrient absorption, root development, and crop resilience. This technology aligns with eco-friendly farming. Field trials of kale cultivation, to evaluate a biostimulant impact on growth, yield, and stress resilience, guiding farmers in seamless integration for enhanced productivity sustainably. This report provides an insight into the uses of kelp biostimulants and microbial coatings for future farmers to integrate into sustainable farming practices.&#x0D; Biostimulants for Rye and Kale&#x0D; The research project involved planting rye and kale seeds in the glasshouse and introducing selected biostimulants to assess their impact. The study focused on evaluating the yield, specifically the dry matter, of both grass and kale. The goal was to understand how the application of specific biostimulants influenced the growth and productivity of rye and kale, with a particular emphasis on quantifying dry matter yield as a key outcome measure.&#x0D; Rye Seeds Coated with a Beneficial Bacteria&#x0D; This study explored the glasshouse cultivation of rye seeds coated with a beneficial microbe. This involved applying a microbial coating. The research aimed to investigate the impact of this coating on the growth and productivity of rye. The goal was to determine the efficacy of rye seeds coated with beneficial microbes (including their stability during storage) in enhancing the yield, offering a promising avenue for advancing modern agricultural practices.&#x0D; Kelp Biostimulant on Kale - Field Trial&#x0D; The field trial focused on the cultivation of kale on two distinct farms – one employing conventional practices and the other following regenerative farming methods. In this study, a biostimulant derived from kelp was introduced to assess its impact on kale growth and yield in both farming systems. The research aimed to compare and contrast the effects of the kelp-based biostimulant on two different agricultural approaches.&#x0D; Supervised by: Craig Bunt&#x0D; Scholarship Projects Funded by: Riddet Otago Scholarship, Kelp Blue, RAGT

Crop mapping in smallholder farms using unmanned aerial vehicle imagery and geospatial cloud computing infrastructure

Smallholder farms are major contributors to agricultural production, food security, and socio-economic growth in many developing countries. However, they generally lack the resources to fully maximize their potential. Subsequently they require innovative, evidence-based and lower-cost solutions to optimize their productivity. Recently, precision agricultural practices facilitated by unmanned aerial vehicles (UAVs) have gained traction in the agricultural sector and have great potential for smallholder farm applications. Furthermore, advances in geospatial cloud computing have opened new and exciting possibilities in the remote sensing arena. In light of these recent developments, the focus of this study was to explore and demonstrate the utility of using the advanced image processing capabilities of the Google Earth Engine (GEE) geospatial cloud computing platform to process and analyse a very high spatial resolution multispectral UAV image for mapping land use land cover (LULC) within smallholder farms. The results showed that LULC could be mapped at a 0.50 m spatial resolution with an overall accuracy of 91%. Overall, we found GEE to be an extremely useful platform for conducting advanced image analysis on UAV imagery and rapid communication of results. Notwithstanding the limitations of the study, the findings presented herein are quite promising and clearly demonstrate how modern agricultural practices can be implemented to facilitate improved agricultural management in smallholder farmers.

The Effect of Climate Change on Food Security in Gedo, Jubaland, Somalia

Climate change is a global phenomenon that has far-reaching consequences for various sectors, including agriculture and food security. It is widely acknowledged that the impacts of climate change pose a significant threat to food production systems and the livelihoods of millions of people, particularly in vulnerable regions such as Somalia. The study was set to examine the effect of climate change on food security in Gedo, Jubaland, Somalia. This study adopted a mixed-methods research approach to investigate the effect of climate change on food security in Gedo, Jubaland, Somalia. From the study discussions the demographic profile of our respondents, highlighting its implications on our data. The agricultural practices prevalent in the region, the economic indicators that define the community’s prosperity, and the crucial indicators of food security were deliberated upon in depth. Drawing the study results, the study concluded that the tapestry of Gedo, Jubaland, Somalia, is a complex interplay of tradition, resilience, challenges, and aspirations. At the heart of this narrative is a community deeply rooted in its agricultural practices, where livestock rearing emerges not just as an occupation, but as a way of life. The reliance on traditional farming, while indicative of a rich cultural heritage, also points to opportunities for growth and modernization. Lastly from the study conclusion and findings the study recommended that embrace Modern Agricultural Practices: While traditional farming has sustained Gedo for generations, there are benefits to integrating modern techniques. Workshops and training sessions focused on sustainable farming, crop rotation, and soil conservation can lead to improved yields and better food security. Keywords: Climate change, Food security, Modern agricultural practices, Traditional farming

Agricultural Implement Industry Using WPM Method

Agricultural implements are agricultural Human labor in activities that Reduce field crop yield Tools that can be used to improve is reapers, Traction, disc harrows, Cultivators, seed drills, Harrows, Spades, Baggage, Plows, and other agricultural Tools are very common. In Modern Agricultural Practices Agricultural implements play an important role play These are commercial and Widespread in organic farming are used. This Tools are for sowing, field preparation, Planting, threshing, and irrigation and are used for harvesting. Agricultural machinery industry or Agricultural engineering is a profession as part of the industry, it is in agriculture or other agriculture used tractors, Agricultural machinery and Manufacturing agricultural implements maintain. This branch is mechanically Considered part of the profession.Agricultural implements are agricultural to carry out procedures The necessary tools are: In today's farming operations Many agricultural implements are used. Agriculture means crops and livestock Production, Aquaculture, Aquaculture and food and food Forests for non-food products Includes. Seated man Agriculture at the Rise of Civilization A major development was Raised by this Cultivation of species is food Generated surpluses, which helped people live in cities. Humans are at least 105,000 grains years ago Although started to collect, New farmers are about 11,500 years ago They started planting. Sheep Goats, pigs, and cattle About 10,000 years ago were raised. World's lowest Plants are native to 11 regions and Cultivated as fodder. twentieth in century, large-scale Based on monocultures Industrial agriculture with dominated agricultural production.The weighted product method is a multi-criteria decision-making process is there are many alternatives, and based on several criteria we must determine the best alternative.DuPont India, Rallis India Limited, Nuziveedu Seeds Limited, Lemken India Agro Equipments Private Limited, Advanta Limited.Technical capability, Product quality capability, Delivery capability, Financial/cost capability from the result, it is seen that Lemken India Agro Equipments Private Limited is got the first rank where as Nuziveedu Seeds Limited is having the lowest rank