Agricultural Economics Research Articles (Page 1)

Automated activity-based costing for large tractor fleets: A scalable CANBUS framework for farm economics

Byzantine plants: an archaeobotanical study of the agricultural economy and land use history of Caesarea Maritima

Sustainable Development Goal 2 (SDG-2), “Zero Hunger,” aims to end hunger, ensure food security, improve nutrition, and promote sustainable agriculture by 2030. India, as one of the world’s largest agricultural economies, has made considerable progress in food production, welfare schemes, and nutritional security programmes. Yet persistent hunger, malnutrition, rising food prices, climate uncertainties, and agricultural distress remain critical barriers. This research paper analyses India’s progress, challenges, and gaps in achieving SDG-2 using both primary data collected from 300 households across Maharashtra (Aurangabad, Jalna, Beed) and secondary data from NFHS-5, GHI, NITI Aayog, FAO, and government reports. The primary survey indicates that 62% households face nutritional insecurity, 47% report low dietary diversity, and 55% of children consume inadequate protein-rich foods. Secondary data show India continues to rank poorly on global hunger indicators, with high levels of stunting (35.5%), wasting (19.3%), and anaemia among children (67%). The paper identifies key structural challenges such as poverty, unequal access to food, climate-vulnerable agriculture, high post-harvest losses, gender disparities, and weaknesses in public distribution systems. It concludes that achieving Zero Hunger requires integrated strategies—nutrition-sensitive agriculture, women-led food systems, climate-resilient farming, improved PDS reforms, fortified foods, and community-driven nutrition models. The paper recommends a holistic policy framework to ensure equitable food access, enhance farmer incomes, and build sustainable agricultural ecosystems necessary to achieve SDG-2 by 2030.

This study focused on analyzing the current status of agricultural economic restructuring in Dong Anh District through crop and livestock structure transformation, the development of specialized farming areas, investment in infrastructure, and reforms in production organization. The district has achieved significant progress thanks to synchronized policies and the consensus of local people. However, it also faces challenges from rapid urbanization, shrinking agricultural land, and labor shifts away from the agricultural sector.The study surveyed 145 respondents, including 20 officials from functional units and 125 representatives from economic organizations, comprising 25 farm owners and 100 farming households. The research assesses the current situation of agricultural restructuring based on several aspects: restructuring by ecological zones and localities; restructuring by commodity chains and local products; the application of science and technology; restructuring of agricultural production and trade organizations. It also identifies the factors influencing this process: (1) factors related to infrastructure development; (2) factors related to industrial and commercial development; and (3) other factors such as human resources, supportive policies, climate change, and socio-cultural aspects.These findings serve as a foundation for orienting sustainable development solutions for the agricultural economy in Dong Anh District in the future.

Brucellosis is a neglected zoonotic disease impacting agricultural economies, as well as animal and human health globally. In sub-Saharan Africa, brucellosis is considered endemic in many countries based on serological evidence, although the presence and distribution of specific Brucella species remain unverified due to limited bacteriological confirmation. Due to the economic importance and national/international trade routes, this cross-sectional study investigates Brucella prevalence in 4612 animals (cattle, sheep, goats, and pigs) from slaughterhouses in the Far-North, North, and West regions of Cameroon sampled between February 2021 and May 2023. The analysis includes serology (Rose Bengal Testand indirect Enzyme-Linked Immunosorbent Assay), culture, real-time PCR, and next-generation sequencing (NGS). Results show only Brucella abortus is present, primarily affecting cattle (8.3%) and goats (7.3%). NGS reveals the local B. abortus strain is related to the clade from Uganda and Sudan, indicating it is endemic to Africa, rather than introduced from outside the continent. These results confirm the presence of a genetically distinct African lineage and reinforce brucellosis as a major concern for both animal and public health. The study emphasizes the critical need for coordinated surveillance systems to support evidence-based control strategies, enhance disease monitoring, and reduce the risk of transboundary transmission.

Agriculture remains the backbone of India’s economy, contributing 18.3% to national income and employing nearly 58 per cent of the workforce. Paddy as the staple food for a majority of the population plays a crucial role in ensuring food security and sustaining rural livelihoods. This study analyses long-term trends in area, production, productivity, and the economic importance of paddy farming using secondary data from 2000-01 to 2023-24. The study underscores the socio-economic significance of paddy cultivation as a driver of rural employment, income security and food stability. It also highlights persistent challenges including climate variability, irrigation deficits, and rising input costs. The paper concludes by emphasizing the need for region-specific interventions focused on water-use efficiency, mechanization, hybrid seed adoption, and institutional support to enhance productivity, profitability, and sustainability of paddy farming in Karnataka and across India. Keywords: Paddy Cultivation, Karnataka, Productivity Trends, Agricultural Economics, Food Security, Rural Livelihoods

Abstract: This project suggests that around the world, sugarcane is an essential crop that contributes significantly to the agricultural economy. Unfortunately, illnesses that can significantly impact both output and quality frequently pose a hazard to its cultivation. Conventional disease detection techniques usually include manual inspections, which can be labour-intensive, time-consuming, and prone to human mistake. By employing Convolutional Neural Networks (CNNs) and incorporating environmental data, this project suggests a machine learning-based approach to sugarcane disease prediction that enhances detection efficiency and accuracy. Images of sugarcane leaves and stems are processed by the system to detect disease symptoms visually. The goal of the research is to develop an automated, real-time illness diagnosis tool by fusing predictive modelling and visual processing. Farmers will be able to reduce crop losses and implement sustainable agricultural practices because to this tool’s ability to provide prompt interventions. The suggested paradigm offers the agricultural community a scalable and easily available solution that has the potential to completely transform crop health management.

Abstract The Computer Age has enabled an explosion in Bayesian inference. Historically, agricultural and resource economists have contributed to the development and application of Bayesian econometrics. This article describes Bayesian econometrics in agricultural and resource economics and highlights its use. We detail the basics of Bayesian methodology and computation, and provide an accompanying empirical example. We then examine the strengths and weaknesses of the Bayesian approach, particularly for applications in agricultural and resource economics. Lastly, we consider frontier Bayesian methods and how they might be used to obtain improved inference, make more accurate predictions, or solve computational challenges.

Evolutionarily, the most recent connective system in the human brain is the language circuitry. However, its presence may impose restrictions on higher executive functions apparent as non-verbal talents in art, science, and management– essentially a conflict between talking and doing. Since the associative cortex underlies thinking, the question then is how much of it is assigned to language functions, and how much is left for associative networks that support non-verbal functions such as planning and parallel processing. Arguments: (i) The determinant of neocortical network organization is the motor cortex, which acts as the main attractor for all processes in the hemispheres yet is split in two sub-attractors formed by disproportionally enlarged zones of origins for two bundles, the corticospinal tract co-driving movements of arms and hands, and the corticobulbar tract to the motor nuclei of the cranial nerves innervating the vocal tract, tongue and face. (ii) This arrangement must entail different functional properties of the associated networks. The language network faces executive limits because the linear generation of words becomes dominated by cerebellar feedback from lingual processing (“one word generates the next”), while the non-verbal networks have more freedom in generating mental goals and movements. (iii) Functional imbalance between these neocortical networks results from altered connections caused by neuronal competition during brain development, either by epigenetic events or by selectable genetic factors. (iv) The descent of the larynx in humans during the paleolithic period and the following self-domestication and neoteny during the last 30,000 years have favored the expansion of the cerebral language network. Voices gained prosody and melody, thereby transmitting fine-grained levels of emotions between individuals, facilitating the evolution of collective cooperation in agricultural economies. On the other hand, with the advent of densely populated kingdom states, emotional voicing also enabled mass control of people for warfare and social stratification of societies. This new environment entailed genetic adaptation of a large population segment resulting in moderately lowered cognition, firstly by expansion of the language network permitting emotional association of simple memes and words, possibly supported by additional mechanisms conserving a child-like stage of brain development responsible for word-linked beliefs.

A field study was conducted in Gorai village of Kalyanpur block, Samastipur district, to evaluate the economic and water-use efficiency of electric versus diesel-operated tubewell irrigation systems across major crops. The study encompassed 20 farmers and analysed multiple parameters including water productivity, irrigation costs, crop profitability and water balance. The irrigation water productivity values were highest for kharif maize at 7.77 kg/m³, followed by wheat (1.95 kg/m³), spring maize (1.45 kg/m3), rabi maize (1.01 kg/m³) and paddy (0.79 kg/m³). In terms of gross water productivity, wheat showed the highest efficiency at 1.69 kg/m³, followed by rabi maize (0.95 kg/m³), spring maize (0.89 kg/m³), kharif maize (0.74 kg/m³) and paddy (0.44 kg/m³). Economic analysis revealed that diesel pump irrigation costs were substantially higher than electric pump costs, ranging from 30 to 37 times more expensive across crops. This cost differential significantly impacted profitability, with electric pump users achieving higher profits of 22 % more for paddy, 13 % for rabi maize, 7.8 % for wheat, 4 % for spring maize and 2 % for kharif maize. The study demonstrates that crop selection and irrigation technology choice are critical factors for optimizing both water use efficiency and farm economics. While electric tubewells demonstrate clear economic advantages, the extremely low electricity tariffs (₹ 0.75/unit) raise sustainability concerns regarding potential groundwater overextraction, necessitating integrated groundwater governance frameworks.

The article discusses the goals and types of business plans, the approaches of foreign and domestic scientists to this tool of strategic management and the method of solving internal business problems of the enterprise. The balance of production factors in agriculture sets the task of developing the land and property complex as the basis for the successful functioning of business structures. The key parameters of business planning take into account the need to substantiate existing or proposed directions for the development of a peasant (farming) economy from the standpoint of economic feasibility. Using the example of "IP head of K(F)X Romazanova E.N." of the Sargatsky municipal district of the Omsk region, the distribution of land by land is analyzed, the state of the property complex of K(F)X is assessed, and economic performance indicators are studied. Proposals for the development of the land and property complex "IP chapter K(F)X Romazanova E.N." include the following stages: assessment of development prospects based on SWOT analysis, development of the material and technical base, optimization of the use of land resources taking into account the ecological state of the lands, justification of the size and sources of financing of the proposed measures, assessment of the economic feasibility of the project offers. The financing of the project is proposed using state support funds within the framework of the Omsk Region state program "Development of agriculture and regulation of agricultural products, raw materials and food markets in the Omsk region", designed for the period up to 2030. Calculations of the effectiveness of investments based on the planned period are given, and their payback period is determined. The effectiveness of the proposed solutions is complex, manifested in economic, social and environmental aspects. The proposed business plan for the development of the land and property complex makes it possible to use land resources in a balanced manner, modernize the production base, creating the basis for sustainable development of the economy in the long term.

Background: Wheat quality and safety are crucial for global food security and regional agricultural economies. Conventional analytical methods for assessing grain composition and quality-while accurate-are often time-consuming, destructive and resource-intensive. In contrast, near-infrared spectroscopy (NIR) has emerged as a rapid, non-destructive alternative that provides detailed chemical and physical insights. Recent advancements in machine learning have enhanced NIR’s analytical capabilities by enabling the development of predictive models that accurately categorize, quantify and monitor grain quality parameters. These models-spanning from linear regression methods to intricate neural networks-enable researchers to discern significant patterns from spectral data, even amidst noise or overlapping signals. Methods: This study used NIR spectroscopy and machine learning models to evaluate wheat quality across multiple Albanian regions during the 2023 harvest. NIR spectra were preprocessed using standard normalization and smoothing techniques. Machine learning models-including PLSR, SVM and random forest-were trained to predict key quality traits such as protein content and moisture. Model performance was validated using cross-validation metrics (RMSE, R², accuracy), demonstrating the potential of NIR-ML integration for rapid, non-destructive grain assessment. Result: Protein content ranged from 9.6% to 15.0%, gluten from 19.4% to 37.5% and starch from 66.3% to 71.5%, indicating consistent nutritional profiles across samples. Sedimentation index values (21.1-57.8 cm³) and moisture levels (9.8-12.5%) confirmed compliance with EU food safety standards. The integration of NIR spectroscopy with machine learning enabled rapid, non-destructive prediction of wheat quality traits, supporting scalable decision-making in agri-food systems.

This review critically examines government intervention in agriculture through policies and bilateral agreements, focusing on mechanisms such as the Minimum Support Price (MSP), input subsidies, crop insurance, extension services, and market regulations. A review of existing literature reveals that although these interventions aim to support farmers and stabilize the agricultural economy, their implementation is often flawed. Key findings highlight systemic gaps: MSP programs face delays and insufficient procurement; input subsidies suffer from targeting inefficiencies and elite capture; crop insurance adoption remains limited due to accessibility barriers; and the federalization of extension services has led to institutional fragmentation. The study has deduced that, despite considerable effort by the government, its efficacy and accessibility to common farmers remain far-fetched, and it is confronted with several technical and infrastructure shortcomings.

Cloud farming is an emerging online farming model where owners remotely participate in raising animals or plants without direct contact. The commercialized cloud farming economy represents an innovative development of traditional agriculture leveraging internet technology, characterized by strong online attributes. This paper will conduct an in-depth study on the criminal regulation of online cloud farming economy activities. In recent years, many criminals have exploited the guise of agricultural innovation, breeding numerous crimes within the cloud farming economy sector. These activities exhibit characteristics such as conceptual hype and deviation from the inherent nature of the agricultural industry, involving issues related to illegal fundraising crimes. Challenges include disputes over factual determinations, debates over the legal characterization between the crimes of illegal absorption of public deposits and fundraising fraud, and complexities in identifying participants' legal statuses. To refine the criminal regulatory framework for online cloud farming economy activities, a criminal policy of strict prevention, strict control, and strict suppression. should be advocated. This involves enhancing the criminal classification system at the legislative level, strengthening regulations against behavioral patterns such as promising high returns without genuine business support, and promoting cross-departmental collaborative governance. Moving forward, further refinement of adjudication standards based on judicial practice is needed to enhance the effectiveness of criminal regulation in this domain.

Wheat serves as a cornerstone of India’s agricultural economy and nutritional security, forming a vital component of both rural livelihoods and national food supply. To enhance its nutritional and qualitative attributes, a field study was conducted during the 2022–23 and 2023–24 rabi seasons to assess the influence of individual and combined applications of sulphatic zinc, iron, and copper fertilizers on the grain nutrient composition and quality parameters of two wheat cultivars (DBW-222 and HD-2967). The study revealed significant varietal and treatment differences across all parameters. DBW-222 consistently outperformed HD-2967 in zinc (29.60 mg kg⁻¹), iron (47.35 mg kg⁻¹), copper (2.22 mg kg⁻¹), crude protein (14.58%), wet gluten (29.40%), dry gluten (10.50%), sedimentation value (61.58 mL), and ash content (1.90%) at pooled analysis. Among nutrient management treatments, the combined soil application of Zn + Fe + Cu (T8) and the combined foliar application (T9) produced the highest enrichment in grain micronutrient content and quality traits. Zinc concentration reached 30.26 mg kg⁻¹ in T8, while iron and copper contents were highest under T9 (48.54 mg kg⁻¹ and 2.67 mg kg⁻¹, respectively) at pooled. Enhanced nutrient accumulation under combined applications was attributed to synergistic effects on root uptake, translocation and enzymatic activation. Quality parameters also improved markedly under T8 and T9, with higher crude protein, gluten fractions, sedimentation values, and ash content. Falling number, an indicator of starch integrity, was highest under T9 (445 seconds at pooled), confirming better enzymatic stability. Overall, integrated application of sulphatic Zn, Fe, and Cu fertilizers—particularly through combined soil and foliar routes, significantly enhanced grain micronutrient concentration and processing quality. The results revealed the importance of balanced micronutrient management in achieving nutritionally rich and high-quality wheat production.

Understanding cash crops offers insight into regional concentration, agricultural economics, market demands, and the social impacts of farming practices globally. The authors try to study the spatial patterns and regional concentration of cash crops in the state of Odisha, India. Twelve cash crops that are predominant in the state are considered under study. The study is based on secondary data collected from the Statistical Abstract of Odisha. Twelve major cash crops, primarily grown in Odisha, were taken under study. We are utilizing the crop concentration method proposed by Bhatia and Geospatial technology for this study. The cash crop area in the state of Odisha is miserable, as the major cash crops, which are under study, covered only 3.98 % of the net area shown. The highest concentration of crops above concentration index 10 are jute (20.98), Kendrapara, maize (18.89), Gajapati, til (17.54), Malkangiri, maize (15.48), Nabarangpur, nizer (14.14), Koraput, ragi (12.62), Koraput and mung (10.31), Jagatsinghpur. Agro-climatic zone wise concentration of cash crops are biri in North Western Plateau; biri, groundnut, and kulthi in North Central Plateau; potato, and sugarcane in North Eastern Central Plateau: groundnut; jute, kulthi, mung, and potato in East and South-Eastern Coastal plateau; maize, mustard, nizer, and ragi in North Eastern Ghat; kulthi, maize, potato, and ragi in Eastern Ghat High Land; nizer, til, sugarcane, and groundnut in South Eastern Ghat; mustard, and kulthi in Western Undulating Zone; biri, and maize in Western Central Tableland: and Potato in Mid Central Table Land. The study's findings help policymakers and agricultural planners distinguish between cash crop production and noncash crops, particularly rice cultivation, as well as to create and promote numerous appropriate cash crops in an appropriate agroclimatic and geographic location. This can boost farmer income, guarantee food security, while minimize farmer distress and end suicides.

Sugarcane plays an important role in the agricultural economy of Pedras de Fogo, Paraíba, contributing to the economy in terms of generating jobs and income in the region. However, its production has been affected by challenges such as climate variations and traditional agricultural practices. The objective of this study was to analyze the productive dynamics of sugarcane in the municipality of Pedras de Fogo, PB, between 2004 and 2023, seeking to understand the factors that influence this production chain and offer subsidies for local development actions. The methodology consisted of analysis through a database, evaluating the variables: planted area, harvested area, quantity produced, productivity and production value. The results revealed a significant reduction in the cultivated area, which went from approximately 30.000 hectares (ha), in 2004 to approximately 18.000 ha in 2023, with emphasis on 2019, which presented the lowest production. Despite the reduction in area, a trend towards increased production was observed, reflected in the stability of productivity throughout much of the period. Therefore, to ensure the sustainability of the activity, it is necessary to invest in more efficient agricultural practices, adoption of technologies, adequate irrigation management and strengthening of public policies that support local producers.

Floriculture plays a crucial role in India's agricultural economy, contributing significantly to farmers' income and rural livelihoods. Among various floricultural crops, chrysanthemum (Chrysanthemum indicum) stands out as a commercially important flower due to its high demand in both domestic and export markets. Tamil Nadu, particularly Dharmapuri district, is a key region for chrysanthemum cultivation. However, farmers face multiple constraints that hinder productivity, profitability, and sustainability. This study aims to identify and analyse the major constraints faced by chrysanthemum growers in Tamil Nadu, categorizing them into resource and infrastructure, extension, production, and marketing constraints. A survey was conducted in Nallampalli block of Dharmapuri district, selecting 72 chrysanthemum growers through a proportionate random sampling method. The data were collected using a structured interview schedule and analysed using the Rank-Based Quotient (RBQ) method. The findings indicate that labour scarcity had RBQ of 73.20 and lack of rainfall RBQ of 59.20 are the most pressing resource constraints. Among extension constraints, the lack of training on crop protection practices had RBQ of 93.00 and market information RBQ of 78.14 significantly affect farmers' decision-making. In production, poor harvest during the rainy season RBQ of 86.38 and high costs of plant protection chemicals RBQ of 73.25 emerge as major concerns. The marketing challenges include low flower prices in local markets RBQ of 95.17 and middlemen exploitation RBQ of 80.33, severely impacting farmers' income. Strengthening infrastructure, facilitating direct market access, and promoting sustainable farming practices can help alleviate these constraints and improve the livelihoods of chrysanthemum growers in Tamil Nadu.

Plant-derived bioactive hydrogels have attracted growing attention in regenerative medicine due to their biocompatibility and multifunctional properties. However, limited studies have explored the integration of Ocimum basilicum extract into crosslinked hydrogels and its effects on angiogenesis and embryonic development. This study aimed to fabricate GPTMS-crosslinked chitosan–polyvinyl alcohol (CP) hydrogels incorporated with different concentrations of O. basilicum extract and to evaluate their physicochemical behavior, angiogenic potential, and embryotoxicological impact using the chick CAM model. Hydrogels were prepared with extract concentrations of 0, 300, and 600 µL (CP-0, CP-3, and CP-6). Swelling and biodegradation properties were assessed under in vitro conditions. In vivo evaluation included angiogenesis quantification using the chick CAM assay, morphological and morphometric analysis of embryos, amniotic fluid biochemical profiling, and histological examination of the liver. The CP-6 hydrogel exhibited the highest swelling and faster degradation, whereas CP-3 showed stable physicochemical behavior. CAM analysis revealed that CP-3 significantly enhanced vessel formation, while CP-6 suppressed angiogenesis. Morphometric and morphological evaluations confirmed normal development in control, CP-0, and CP-3 groups, but CP-6 embryos displayed teratogenic defects, including malformed limbs, abnormal curvature, and abdominal wall defects. Amniotic fluid biomarkers indicated reduced AST (31.8 U/L) and ALT (28.5 U/L) levels in the CP-3 group, demonstrating hepatoprotective effects, whereas the CP-6 group exhibited elevated AST (48.6 U/L) and ALT (42.3 U/L) values, confirming dose-dependent hepatic and renal toxicity.. Histological findings further corroborated these outcomes, with CP-3 preserving hepatic structure and CP-6 causing vacuolation and tissue disorganization. O. basilicum–loaded hydrogels demonstrated a biphasic, dose-dependent response, with CP-3 showing pro-angiogenic and biocompatible potential, while CP-6 induced systemic toxicity. These findings underscore the need for dose optimization to harness herbal extract–based hydrogels for wound healing, bone regeneration, and tissue engineering applications.uminants, offering actionable targets for precision breeding in tropical agricultural economics.

Factors impacting beef cattle producers' perceptions on disease prevention and preparedness in Illinois, USA: The role of farm biosecurity evaluations, veterinary visits, and willingness to invest in disease prevention.