Sustainable Agricultural Growth Research Articles

Residue and Irrigation Management for Optimizing Productivity and Profitability of Wheat in Ambala (Haryana)

Background: The rice-wheat cropping system in Haryana, Western Uttar Pradesh and Punjab faces sustainability risks due to soil fertility depletion, rising cultivation costs and environmental pollution hazards because of the large-scale burning of rice crop residues. Two-year field experiments investigated wheat sowing techniques by keeping rice crop residues under various irrigation schedules to optimize production and economic outcomes in Ambala, Haryana. Three sowing methods, i.e., conventional sowing (CS), Happy Seeder (HS) and Super Seeder (SS) and four irrigations scheduling, i.e., scheduling at critical growth stages (IS1), IW/CPE ratio 0.9 with first irrigation at CRI (IS2), IW/CPE ratio for whole crop season (IS3) and depletion of 50% available soil moisture (IS4). Methods: Happy Seeder sown wheat exhibited a significantly higher average yield of 58.38 q ha-1 than conventional (57.69 q ha-1) and Super seeder (56.85 q ha-1) sown wheat. Overall, Happy Seeder and irrigation schedule (IS3) produces the highest grain yield of 65.23, 63.56 and 64.40 q ha-1 in the first, second year and pooled year results. In conventional sowing of wheat, the average total cultivation cost was 107134.02 and 110907.71 Rs ha-1, which was less in Happy Seeder sown wheat, i.e., 99077.07 and 102932.27 Rs. ha-1 respectively, in the year 2021-22 and 2022-23. Result: The average benefit-cost ratio (BCR) for the happy seeder technique, 1.42 and 1.44, outperforms the conventional sowing wheat approach during both years of experiments. The recent wheat sowing using happy seeder under residue mulching conditions, must adopt modified irrigation scheduling practices to enhance yield and profitability, contributing to sustainable agricultural practices. The study highlights the potential of recent agricultural practices to boost farmer income, promote sustainable agricultural growth and environment conservation.

An Exploration of the Relationship Between Digital Village Construction and Agroecological Efficiency in China

Whether digital village construction can effectively promote agriculture’s green development is essential for modernizing agriculture and rural areas. Using panel data from 30 provinces in China between 2011 and 2022, this study empirically examines the relationship between digital village construction and agroecological efficiency and explores its mechanism of action and threshold effect, contributing to the exploration of agricultural digitization and sustainable development. This study shows that (1) AEE is positively associated with digital village construction; (2) the positive association size varies in regions and construction levels; (3) agricultural land transfer and technological innovation play a mediating role in the positive effect; and (4) there is a single threshold value for the positive effect of digital village construction, and after crossing the threshold value, its marginal effect shows a positive and increasing nonlinear characteristic. This study enhances our comprehension of digital village development to advance agroecological efficiency and offers theoretical insights and policy recommendations for optimizing the rural digital infrastructure and fostering sustainable agricultural growth.

Factors Influence the Adoption of Improved Agricultural Practices among Smallholder Farmers in the Ripat Program: A Case of Morogoro Municipality, Tanzania

Maize plays a significant role in securing food insecurity mostly in developing countries such as Africa, especially in Tanzania where it is a main dietary staple for most people. This research assesses the factors influencing corn production levels among small-scale farmers who benefit from the RIPAT SUA Project in Morogoro, Tanzania. The project aims to improve maize production and food security through improved agriculture practices such as fertilizer use and intercropping methods. This study employed a cross-sectional design with 110 smallholder farmers. Information was collected through semi-structured questionnaires and analyzed using descriptive and bivariate probit regression models. Findings reveal that household income, farm size, farmer experience, and training play a crucial role in adopting improved agriculture practices. Notably a significant finding is that a higher income household income increases the chances of using fertilizer by 16.9% (p= 0.015) and receiving training improves the likelihood of adopting intercropping by 8.47% (p = 0.007). However, education alone does not have a noticeable impact signifying that specialized training could be more effective in improving adoption rates among small farmers with limited formal education. The research findings conclude that increased training opportunities, specifically for farmers with minimal education, and matching access to credit availability with agricultural investment. This measure will assist small-scale in boosting productivity, eventually supporting the sustainable growth of agriculture in Tanzania.

Can nanotechnology and genomics innovations trigger agricultural revolution and sustainable development?

At the dawn of new millennium, policy makers and researchers focused on sustainable agricultural growth, aiming for food security and enhanced food quality. Several emerging scientific innovations hold the promise to meet the future challenges. Nanotechnology presents a promising avenue to tackle the diverse challenges in agriculture. By leveraging nanomaterials, including nano fertilizers, pesticides, and sensors, it provides targeted delivery methods, enhancing efficacy in both crop production and protection. This integration of nanotechnology with agriculture introduces innovations like disease diagnostics, improved nutrient uptake in plants, and advanced delivery systems for agrochemicals. These precision-based approaches not only optimize resource utilization but also reduce environmental impact, aligning well with sustainability objectives. Concurrently, genetic innovations, including genome editing and advanced breeding techniques, enable the development of crops with improved yield, resilience, and nutritional content. The emergence of precision gene-editing technologies, exemplified by CRISPR/Cas9, can transform the realm of genetic modification and enabled precise manipulation of plant genomes while avoiding the incorporation of external DNAs. Integration of nanotechnology and genetic innovations in agriculture presents a transformative approach. Leveraging nanoparticles for targeted genetic modifications, nanosensors for early plant health monitoring, and precision nanomaterials for controlled delivery of inputs offers a sustainable pathway towards enhanced crop productivity, resource efficiency, and food safety throughout the agricultural lifecycle. This comprehensive review outlines the pivotal role of nanotechnology in precision agriculture, emphasizing soil health improvement, stress resilience against biotic and abiotic factors, environmental sustainability, and genetic engineering.

Sustainable Development Strategies and Good Agricultural Practices for Enhancing Agricultural Productivity: Insights and Applicability in Developing Contexts—The Case of Angola

In general, agricultural productivity in Angola is low due to the limited awareness among stakeholders regarding sustainable development strategies (DSs) and good agricultural practices (GAPs) that could be adjusted to local crops, soil types, and climatic conditions. A structured approach was followed to develop a systematic literature review (SLR) that can address this gap by examining how DSs and GAPs may be adapted for Angola’s context to encourage sustainable agricultural development. Key steps included the selection and exclusion of literature from primary scientific databases based on specific screening indicators such as the publication date, language, relevance to DSs and GAPs, and geographic focus on developing or developed nations with comparable agricultural challenges. The initial search resulted in 11,392 articles, of which 4257 met the primary selection criteria. After further screening for relevance and availability, 98 articles were shortlisted, and 15 studies were ultimately included for in-depth analysis. This strict screening process ensured the inclusion of studies most applicable to Angola’s agricultural context. The key research findings indicate that certain DSs and GAPs have high adaptability potential for Angola. The findings emphasise practices such as drip irrigation and inorganic fertilisation, which are widely implemented in both developed and developing countries due to their efficiency in resource-limited environments. Additional strategies, such as water management systems, organic composting, and agroforestry practices, demonstrate significant potential to enhance soil fertility, water efficiency, and crop resilience against climate variability. By identifying these practices and strategies, this study provides a basic framework for policymakers in Angola to develop targeted implementation guidelines, fostering sustainable agricultural growth and resilience in the face of climatic challenges. Thus, this review contributes to the scientific and practical understanding of sustainable agriculture in developing countries, offering critical insights that support Angola’s efforts to achieve greater self-sufficiency and economic stability through sustainable agricultural practices.

Performance of cash transfer program on farmers’ livelihood: evidence from PM-KISAN scheme of India

IntroductionResearch into various aspects of vulnerability and poverty has played a key role in shaping cash transfer systems. Cash-based direct benefit transfers (DBT) are frequently discussed, as they help reduce corruption and limit intermediary involvement, which often impedes policy implementation in countries like India. Small and marginal farmers (SMFs), constituting 86% of India’s farming population, are essential for sustainable agricultural growth and ensuring food and nutrition security. The Pradhan Mantri Kisan Samman Nidhi (PM-KISAN) scheme provides Rs.6000 annually to the farmer families via DBT mechanism. Despite reports and information from various government sources, significant concerns remain regarding the performance of PM-KISAN scheme in improving living conditions of SMFs.MethodsFor having the highest number of SMFs, a research study was conducted in Bihar and Uttar Pradesh. Two cluster of villages from each of these two states were chosen by simple random sampling (SRS) method. An ex post facto research design was used; data was gathered from 240 SMFs, with 120 beneficiaries and 120 non-beneficiaries, using a stratified disproportionate simple random sampling technique. The study used 18 indicators related to livelihood assets—human capital, social capital, natural capital, physical capital, and financial capital—to generate a Livelihood Index (LI) through Principal Component Analysis (PCA).ResultsThe beneficiaries of the scheme had an average LI score of 0.396, while non-beneficiaries had a score of 0.366. Propensity Score Matching (PSM) was employed to compare the beneficiaries and non-beneficiaries in order to determine the impact of the scheme. In the Livelihood Index of beneficiaries, in comparison to non-beneficiaries, there was a significant improvement of 3.34 to 4.13 percentage points, according to the analysis, which utilized a variety of matching algorithms.DiscussionImplications from the study suggests that PM-KISAN should be integrated into a broader rural development strategy to maximize multiplier effects. By combining cash transfers with complementary initiatives like modern technology adoption and high-yield seeds, farmers can make productive investments that could enhance their livelihood status.

Advancing Vegetable Grafting: A Comprehensive Review of Techniques, Challenges, and the Future of Automated Solutions

Vegetable grafting, a practice that combines two plant parts rootstock and scion into a single, superior plant, is an increasingly important technique in modern agriculture. By enhancing yields, stress resistance, and disease tolerance, grafting plays a crucial role in addressing challenges such as soil borne pathogens, extreme environmental conditions, and crop vulnerability to nematodes. Despite its benefits, vegetable grafting faces several challenges, including the need for compatible plant material, labour-intensive nursery production, high seed costs, and the potential for pathogen spread. Effective grafting requires meticulous selection of rootstock and scion, precise grafting techniques, and optimal post-grafting care to ensure survival and success. Looking toward the future, significant advancements in grafting technologies and nursery practices are required to overcome these challenges and improve efficiency. The development of grafting robots, capable of mechanizing the grafting process, holds promise for increasing productivity while reducing labor costs. Additionally, the establishment of specialized plug plantlet nurseries, equipped with advanced seeders, growth chambers, and acclimatization facilities, offers a pathway to enhance seedling vigour and uniformity in developing countries. Future research should also focus on refining seed-priming methods, improving seedling storage technologies, and exploring digital tools such as databases, crop models, and mobile applications to optimize grafting practices. These innovations could provide valuable insights for growers, helping them select the best rootstock-scion combinations and manage crops more efficiently. With continued research and technological advancements, vegetable grafting is poised to become a global solution, offering sustainable growth and productivity improvements in agriculture.

The Role and Future Potential of Bio-Fertilizers in Indian Agriculture

Only imports and subsidies have been able to guarantee the availability and affordability of chemical fertilisers made from fossil fuels at the farm level in India. Because of their non-toxicity, affordability, ease of use, and environmental friendliness, biofertilizers are currently a very effective substitute for chemical fertilisers. By making naturally available nutrients in the soil or environment advantageous to plants, they also serve as an adjunct to agrochemicals. If farmers and producers have the proper kind of access to information gleaned through experience and communication, this commodity could eventually show promise economically. The Indian government has been attempting to blend more advanced agrochemicals with biofertilizers. This study focuses on the success and failure issues in the Indian context to increase the potential for sustainable agriculture growth. Additionally, it emphasises the necessity of high levels of innovation, active involvement in scientific research and development, public awareness campaigns, and enticing business organisations and policy leaders to show interest in this area.

Impact of Agricultural Credit by Commercial Banks on Agricultural GDP

The farming sector in India has always been an essential and significant part of the country’s economy. Agriculture has long been a significant employer of over 43% of the workforce and a large contributor to the nation’s Gross Domestic Product (GDP), (14.39%) but it has also experienced difficulties including exploitation and uneven regulations. Despite these challenges, agriculture remains essential for the country’s development, especially as it shifts towards a more business-oriented approach that requires access to capital. When looking at what factors influence agricultural productivity growth in India, attention to credit, inputs and policies can be signalled. Credit has been a crucial component in supporting agriculture for centuries and its importance has only increased as financial institutions have taken over from traditional non-institutional players such as moneylenders, friends and relatives. A significant factor in agriculture’s expansion, especially in spurring the Green Revolution, has been institutional financing. Institutional lending to the agricultural industry and allied fields has grown significantly over time. Based on regression analysis, this study examines the relationship between direct institutional credit and agriculture and allied services GDP by analysing data covering 19 years (1992-2011) using a Multi Linear Regression model to find determinants of agricultural development. The research has found that a strong correlation exists between credit and agricultural output along with other inputs like seeds, fertilisers, pesticides, tractors, power tillers and electricity. This has been reinforced by government interventions such as offering subsidies, providing extension services and developing infrastructure. Nonetheless, a nagging problem of climate change markets is out of control and gaps in the execution of policies continue to cross the horizons. For India to manage these changes, it will be necessary for the country to shift and take positive measures that will ensure sustainable agricultural growth in rural communities.

An analysis of the rebound impact of energy consumption and the factors that influence it in China's agricultural productivity

With China's agricultural sector being a major contributor to both the national economy and energy consumption, the rebound effect—the phenomenon where energy efficiency improvements lead to increased energy use—poses significant challenges to sustainable energy use. The motivation for this study stems from the need to understand the extent of this rebound impact and its underlying drivers, particularly in the context of China's agricultural modernization efforts. This study examines the rebound effect of energy consumption in China's agricultural productivity and the factors influencing it over the period from 1990 to 2023. Using a Generalized Method of Moments (GMM) model, this research analyzes the relationship between energy consumption, agricultural productivity, and several influencing factors, including technological innovation, rural-urban migration, and financial development. The results reveal that (1) energy efficiency improvements have led to a significant rebound effect in China's agricultural sector, limiting potential energy savings, (2) technological advancements have mitigated the rebound effect to some extent, but the effect remains substantial, (3) rural-urban migration has contributed to labor shortages, increasing mechanization and energy demand, and (4) financial development has positively influenced both agricultural productivity and energy use, exacerbating the rebound effect. The study suggests that policymakers should focus on developing stricter energy efficiency standards and promoting technological innovations that reduce energy intensity in agriculture, while also addressing labor migration challenges to curb the rebound impact and achieve more sustainable agricultural growth.

A review on hydroponics, a recent technological advancement for sustainable agriculture growth in India

A review on hydroponics, a recent technological advancement for sustainable agriculture growth in India

Integrating Machine Learning for Enhanced Agricultural Productivity: A Focus on Bananas and Arecanut in the Context of India’s Economic Growth

AbstractAgriculture is one of the sectors that has an important impact, taking into account the problem of sufficient food supply on a global level. The process of predicting the yield of crops is among the most challenging undertakings in the agricultural industry. Agriculture is the main source of income for most developing nations. The purpose of the study is to investigate the significant role that agriculture plays in boosting India's economic growth. Additionally, the research considers the challenges posed by a growing population and a changing environment in terms of agricultural production and food security. The research focuses on analysing the complex characteristics of the agricultural industry, with a particular emphasis on the nutritional importance of tropical fruits, notably bananas and arecanut. These fruits are well-known for their vital nutrients and their role in ensuring world food security. This study acknowledges the importance of sustainable agriculture practices and incorporates sophisticated machine learning algorithms as dynamic tools to forecast crop yields and enhance decision-making processes throughout the crop development cycle. The main aim of this study is to create strong machine learning models and statistical techniques that can accurately predict crop yield by combining a variety of environmental parameters, then assess which models outperform each other. Assist yield projections may provide governments and policymakers with valuable information to make well-informed choices about food security, import–export policies, and resource allocation. It facilitates national- and regional-level food supply planning. The validation method utilises important metrics like R square (R2), Mean Absolute Error (MAE), and Root Mean Squared Error (RMSE). This present research adds to the continuing discussion on using creative methods to promote sustainable agricultural growth and ensure food security.

The intermediate role of farmland transfer in the impact of digital financial inclusion on agricultural total factor productivity in China

IntroductionEnhancing agricultural productivity and promoting sustainable development in China are critical priorities, given their significant contribution to food security and rural development. However, achieving consistent agricultural productivity growth across regions and sectors has been challenging, leading to inefficiencies and environmental pressures. To address this, the potential of digital inclusive finance (DIF) as a catalyst for progress has been explored.MethodsThis study investigates the impact of DIF on agricultural total factor productivity (ATFP) through farmland transfer, with implications for rural revitalization and high-quality agricultural development. Using the HMB index method, we calculate and decompose China’s inter-provincial ATFP from 2011 to 2020. Employing the dynamic panel fixed effect model and SYS-GMM method, we empirically test the influence of DIF on agricultural productivity in relation to farmland transfer.Results and discussionOur findings reveal a slow upward trend in China’s ATFP, driven primarily by scale efficiency. Notably, a 1% increase in the general index of DIF correlates with a 0.136% increase in ATFP. We analyze the sub-classification indexes of digital inclusive finance, namely coverage breadth, depth of use, and digitalization degree. Their contributions to agricultural productivity growth are significant, with coverage breadth having the greatest impact, followed by depth of use and digitalization degree. Farmland transfer acts as a crucial intermediary, enhancing agricultural allocation efficiency and driving the relationship between digital finance and total factor productivity growth. Interestingly, the western region exhibits the highest growth rates, followed by the eastern region, while the central region shows no significant effects.ConclusionTo comprehensively enhance ATFP, aligning supply and demand for digital financial services, leveraging service depth, and guiding farmland transfer according to local conditions are essential. These findings offer valuable insights into effective strategies for maximizing the potential of DIF, promoting rural development, and achieving sustainable agricultural growth.

Agricultural Financing and Agricultural Output in Nigeria: An ARDL Approach

This study analyzes the impact of agricultural financing on agricultural output in Nigeria from 1991 to 2022. Employing an Autoregressive Distributed Lag (ARDL) model, the research examines the effects of government capital expenditure, commercial bank credit schemes, and the agricultural credit guarantee scheme (ACGS) on agricultural output. The findings indicate that both government capital expenditure and ACGS positively and significantly influence agricultural output in both the short and long run. Commercial bank credit schemes also have a positive and significant impact, although some studies report this effect as positive but not statistically significant. The study highlights the crucial role of financial support in boosting agricultural productivity and offers policy recommendations to improve agricultural financing mechanisms. These include increasing government investment, enhancing credit schemes, and strengthening the ACGS to ensure sustainable agricultural growth and economic development in Nigeria.

AGRICULTURE CREDIT AND THE ROLE OF KISAN CREDIT CARD (KCC) IN INDIA

This research paper presents a comprehensive analysis of agricultural credit in India, focusing on the transformative role of the Kisan Credit Card (KCC) scheme in empowering farmers. Through a review of literature and an examination of pertinent data from various government reports and international organizations, this study evaluates the evolution of agricultural credit, assesses the trends in credit disbursement, and explores the significant impact of the KCC on agricultural productivity, rural development, and financial inclusion. The analysis showcases the KCC's contribution in facilitating timely credit access, reducing dependency on informal credit sources, and enhancing financial accessibility for farmers across different banking institutions. Furthermore, this paper discusses policy implications and recommendations to augment the effectiveness of KCC and agricultural credit schemes in meeting the evolving needs of farmers and fostering sustainable agricultural growth. The insights drawn from this research aim to provide a nuanced understanding of agricultural credit dynamics and underscore the pivotal role of KCC in enhancing the livelihoods of Indian farmers. KEYWORDS: Agricultural credit, Kisan Credit Card (KCC), financial inclusion, rural development, farmers' empowerment, policy recommendations, sustainable agriculture

Exploring the "Double-Edged Sword" effect of the digital economy on sustainable agricultural development: Evidence from China

The prolonged reliance on excessive resource utilization and unsustainable production methods has resulted in significant environmental issues in China, posing serious challenges to the sustainable development of agriculture. While the digital economy offers new opportunities for enhancing agricultural sustainability, its rapid and unregulated growth could also lead to negative effects. Therefore, exploring the relationship between the digital economy and sustainable agriculture development (SAD), along with clarifying the mechanisms involved, is of paramount importance. This study uses the EBM-GML index to calculate AGTFP as a representation of SAD and empirically tests the impact and mechanism of the digital economy on SAD. Additionally, it explores the moderating role of government behavior, specifically Agricultural fiscal support and digital policies. The main findings are as follows: (1) During the observation period, SAD showed a steady upward trend, but regional disparities widened, forming a contiguous agglomeration pattern. The decentralization of the digital economy weakened, trending towards unipolarization and homogenization, with a north-to-south diffusion. (2) The impact of the digital economy on SAD presents an inverted "U" shape, indicating a "double-edged sword" effect. This relationship remains significant after robustness and endogeneity tests. Additionally, the digital economy exhibits significant spatial effects, maintaining an inverted U-shaped relationship with SAD in neighboring areas. (3) Regional heterogeneity shows that coastal provinces are in digital economy suppression or alert areas, while inland regions are in enhancement areas. During the study period, the number of suppression and alert areas did not significantly increase, but there was a trend of shifting from coastal to inland regions. (4) When below the threshold, the digital economy promotes agricultural green technology innovation, optimizes resource allocation, and fosters synergetic agglomeration of agriculture with the secondary and tertiary industries, enhancing SAD. However, surpassing the threshold negatively impacts these mechanisms. (5) Fiscal support for agriculture smooths the inverted "U" curve, mitigating the negative impact of excessive digital economy growth on SAD. Conversely, digital policies steepen the inverted "U" curve, exacerbating these negative effects. The findings highlight the need for balanced digital economic development to support sustainable agricultural growth.

An Improved Spatiotemporal Time Series Modelling Procedure with Application to Forecasting of Solar Radiation

The demand for energy and associated services to meet sustainable agricultural and economic growth and improve human health and lifestyle is increasing day by day. Hence, there is a need for systematic and scientific prediction of solar and other renewable sources of energy to meet these requirements. The main purpose of this study is to propose a hybrid Space-Time Autoregressive Moving Average Artificial Neural Network (STARMA-ANN) model for the precise and accurate forecasting of solar radiation for better planning and policy making. This approach has been implemented at seven geographical locations of Bihar in India. Spatial weight matrices have been used to describe all seven geographical locations and incorporated into the STARMA model to reflect the spatial and temporal correlation. To deal with nonlinear dynamics in the spatiotemporal data, ANN technique has been applied on residuals of the fitted STARMA model. The results have demonstrated that the proposed hybrid model performs better prediction accuracy than using conventional STARMA model, especially for spatiotemporal data with nonlinear characteristics of solar radiation.

Are farmers willing to pay for low-carbon agriculture? Evidence from China

PurposeReducing carbon emissions in agriculture is vital for fostering sustainable agricultural growth and promoting ecological well-being in rural areas. The adoption of Low-Carbon Agriculture (LCA) by farmers holds great potential to accomplish substantial reductions in carbon emissions. The purpose of this study is to explore the farmers' preference and willingness to engage in LCA.Design/methodology/approachThis study employs the Choice Experiment (CE) method to examine farmers' preferences and willingness to adopt LCA, using field survey data of 544 rural farmers in the Weihe River Basin between June and July 2023. We further investigate differences in willingness to pay (WTP) and personal characteristics among different farmer categories.FindingsThe empirical results reveal that farmers prioritize government-led initiatives providing pertinent technical training as a key aspect of the LCA program. Farmers' decisions to participate in LCA are influenced by factors including age, gender, education and the proportion of farm income in household income, with their evaluations further shaped by subjective attitudes and habits. Notably, we discovered that nearly half of the farmers exhibit indifference towards LCA attributes.Originality/valueTo the best of the authors' knowledge, this study is the first to investigate farmers' attitudes toward LCA from their own perspectives and to analyze the factors influencing them from both subjective and objective standpoints. This study presents a fresh perspective for advocating LCA, bolstering rural ecology and nurturing sustainable development in developing nations.

Public-Private Partnerships in driving Sustainable Agricultural Growth for Addressing Poverty and Food Insecurity in Nigeria

Poverty and food insecurity have become a concern in various parts of the world including Nigeria which are regarded as impediments for achieving sustainable development goals (SDGs). Overwhelming studies have explored the roles and contributions of public-private partnerships (PPP) in driving various aspects of the economy in general and gross domestic product (GDP) in particular. However, less focus of attention is given to public-private partnerships (PPP) in fostering the sustainable agricultural growth in Nigeria in order to addressing poverty and food insecurity in Nigeria. Content and critical analysis is used in this study as a methodological approach. Secondary data were used which were sourced through academic databases such as journals from google scholar. The result demonstrated that the current hike in the price of commodities in the country contribute to the proliferation of poverty among the households and the challenges of kidnapping and banditry immensely contribute to the challenge of food security in the country. The challenge of funds identified among the farmers contribute immensely to high level of poverty and prevalence of food insecurity in the country. It is therefore suggested that the government should encourage provision of funds through an effective collaboration of public-private partnerships (PPP) in driving sustainable agriculture growth in the country. In so doing, it would strengthen the income of households through farming and sustainable agricultural productivity for poverty alleviation and food security will be achieved.

Data-Driven decision making in agriculture and business: The role of advanced analytics

Advanced analytics has revolutionized decision-making processes in agriculture and business by harnessing data-driven insights to optimize operations, manage risks, and drive innovation. This paper explores the transformative role of advanced analytics in these sectors, highlighting key benefits, challenges, and future directions. In agriculture, advanced analytics enables precision farming by integrating AI, IoT sensors, and satellite imagery. Predictive models forecast crop yields, optimize irrigation, and enhance soil management practices, improving productivity and sustainability. Similarly, advanced analytics supports strategic decision-making in business by analyzing consumer behavior, predicting market trends, and optimizing supply chain operations. However, adopting advanced analytics faces challenges such as data quality, technical expertise, cost constraints, and ethical considerations. Addressing these challenges requires investments in data infrastructure, talent development, and regulatory compliance to ensure secure and ethical data usage. Emerging trends include AI-driven automation, blockchain for supply chain transparency, and augmented analytics for democratizing data access. Recommendations for stakeholders include investing in data capabilities, fostering collaborative partnerships, and promoting a culture of data-driven decision making. In conclusion, advanced analytics offers profound opportunities to enhance efficiency, inform decision making, and drive sustainable growth in agriculture and business. Embracing these technologies is essential for organizations seeking to thrive in a data-driven economy. Keywords: Advanced Analytics, Precision Farming, Predictive Analytics, Data-driven Decision Making, Business Intelligence.