Farm Profitability Research Articles

Survey and molecular characterization of begomovirus, and assessment of yield losses caused by leaf curl disease of sunflower (Helianthus annuus)

A comprehensive survey was conducted during winter (rabi) and rainy (kharif) seasons of 2019–20 to 2021–22 in the Kurnool, Nandyal, and Prakasam districts of Andhra Pradesh, focusing on the incidence of leaf curl disease in hybrid sunflower (Helianthus annuus L.) crop. The results revealed a high incidence of the disease, ranging from 40–94.5% across most of the surveyed hybrid varieties. Leaf curl-infected samples collected from the surveyed fields were analyzed by PCR using specific primers for the DNA-A component of the virus to confirm the presence of the pathogen. The PCR-amplified fragments were cloned and sequenced. Sequence analysis revealed that the sunflower isolate (Snf-AP) shared 99.2% nucleotide identity with the tomato leaf curl Karnataka virus (ToLCKV), which infects sunflower crops in Karnataka. This indicates a strong geographical and genetic connection between the viral strains affecting sunflowers in Andhra Pradesh and Karnataka. This genetic similarity is significant, as it suggests that the same or closely related viral strains are responsible for sunflower leaf curl disease across broader regions. The disease was found to affect sunflowers at all growth stages, with the highest incidence (42.3%) observed at the star bud stage. Infection at the star bud stage leads to substantial seed yield losses, with reductions of up to 82.8%. This level of damage underscores the economic impact of early infections, as yield losses of this magnitude can severely affect the profitability of sunflower farming. Additionally, a positive correlation was found between the whitefly population, weather parameters, and disease development.

Comparative transcriptomic and proteomic analyses of two salt-tolerant alfalfa (Medicago sativa L.) genotypes: investigation of the mechanisms underlying tolerance to salt

Abiotic stressors such as salt stress restrict plant development and output, which lowers agricultural profitability. In this study, alfalfa (Medicago sativa L.) varieties with different levels of salt tolerance were examined using high-throughput RNA sequencing (RNA-Seq) and Tandem Mass Tags (TMT) technologies to study the reactions of the root systems to salt stress, from transcriptomics and proteomics perspectives. The varieties Atlantic (AT) and Zhongmu-1 (ZM-1) were selected and evaluated after 2 h and 6 h of treatment with 150 mM NaCl. The results showed that under salt stress for 2 h, 1810 differentially expressed genes (DEGs) and 160 differentially expressed proteins (DEPs) in AT were screened, while 9341 DEGs and 193 DEPs were screened in ZM-1. Under salt stress for 6 h, 7536 DEGs and 118 DEPs were screened in AT, while 11,754 DEGs and 190 DEPs were screened in ZM-1. Functional annotation and pathway enrichment analyses indicated that the DEGS and DEPs were mainly involved in the glutathione metabolism, biosynthesis of secondary metabolites, glycolysis/gluconeogenesis, carbon fixation in photosynthetic organisms, and photosynthesis pathways. A series of genes related to salt tolerance were also identified, including GSTL3 and GSTU3 of the GST gene family, PER5 and PER10, of the PER gene family, and proteins such as APR and COMT, which are involved in biosynthesis of secondary metabolites. This study provides insights into salt resistance mechanisms in plants, and the related genes and metabolic pathways identified may be helpful for alfalfa breeding in the future.

Design and Fabrication of the Automatic Multipurpose Agriculture Robot (AMAR)

The rapid development of robotics and automation has significantly benefited various industries, including agriculture. This project proposes the creation of an Automatic Multipurpose Agriculture Robot (AMAR) to revolutionize farming practices. AMAR will automate diverse agricultural tasks, minimize physical labour, and optimize resource use. The automatic multipurpose agricultural seed sowing robot, a state-of-the-art autonomous machine, is designed to revolutionize seed planting. It combines technologies like computer vision and precision mechanics to ensure efficient and precise seed sowing across various crops and terrains. The robot analyses optimal seed placement, ensuring even distribution. Energy-efficient and eco-friendly, it reduces labour costs, increases productivity, and enhances crop yields, fostering sustainable agricultural practices and improving profitability for farmers.The rapid development of robotics and automation has significantly benefited various industries, including agriculture. This project proposes the creation of an Automatic Multipurpose Agriculture Robot (AMAR) to revolutionize farming practices. AMAR will automate diverse agricultural tasks, minimize physical labour, and optimize resource use. The automatic multipurpose agricultural seed sowing robot, a state-of-the-art autonomous machine, is designed to revolutionize seed planting. It combines technologies like computer vision and precision mechanics to ensure efficient and precise seed sowing across various crops and terrains. The robot analyses optimal seed placement, ensuring even distribution. Energy-efficient and eco-friendly, it reduces labour costs, increases productivity, and enhances crop yields, fostering sustainable agricultural practices and improving profitability for farmers.

Analisis Pemasaran Kelapa Sawit Rakyat Desa Perdomuan Nauli Kecamatan Kandis Kabupaten Siak Provinsi Riau

Indonesia, as an agricultural country, has an agricultural sector that contributes significantly to the national economy. Palm oil is the main commodity that plays an important role in increasing state income, especially in Perdomuan Nauli Village, Kandis District, Riau. This research aims to analyze palm oil marketing in the village using descriptive methods. Primary data was obtained through interviews and questionnaires, while secondary data came from literature and related institutions. The research location was selected through purposive sampling involving 35 respondents who used three main marketing channels: Farmers–Collectors–RAM–PKS, Farmers–Collectors–PKS, and Farmers–RAM–PKS. The research results show that the Farmer–RAM–PKS channel provides the highest profits for farmers with a margin of IDR 434.3/kg, followed by the Farmer–Collector–PKS channel with a profit of IDR 234.3/kg. The Farmer–Collector–RAM–PKS channel, even though it is the longest, still provides profits for farmers of IDR 139.3/kg. Each channel has its own advantages and disadvantages, depending on the facilities provided and marketing costs incurred. This research emphasizes the importance of evaluating and improving marketing channels to increase the efficiency and welfare of oil palm farmers in Perdomuan Nauli Village

The Analysis of Geospatial Factors Necessary for the Planning, Design, and Construction of Agricultural Biogas Plants in the Context of Sustainable Development

This spatial analysis focuses on the relevant elements regarding the use of renewable energy sources, in particular, biogas, taking into account sustainability. The characteristics of the processes of biogas formation are presented, including the technological and biological aspects of its production. The issues of agricultural biogas plant profitability are discussed using examples from Poland, analyzing the economic and financial aspects of investing in this type of plant. Geospatial analysis supported by geographic information systems (GISs) looked at factors affecting the relief of the land and also the analysis of local plans or zoning decisions for the selected site. In addition, distance relationships and geological aspects taking into account terrain, landslides, and forestation, as well as hydrological aspects relating to flood and flooding hazards, were examined. It analyzed the availability of utility networks and proximity to road infrastructure. It was also examined that the proposed project will not have a negative impact on environmental protection. The analyzed site meets favorable conditions for the construction of the proposed project, and the conclusion drawn from this study is to emphasize the importance of integrating renewable energy sources with information systems to achieve sustainable development.

Circular agro-economies (CAE): reducing waste and increasing profitability in agriculture

This paper explores the concept of Circular Agro-Economies (CAE), a sustainable agricultural model focused on recycling agricultural by-products to minimize waste and maximize profitability for farmers. In contrast to traditional linear agricultural systems, CAE promotes resource efficiency and the development of new value chains through the reuse of organic materials. The paper examines the environmental, economic, and social benefits of adopting CAE, including waste reduction, cost savings, rural development, and job creation. It also discusses the significant barriers to adoption, such as technological limitations, financial constraints, and policy-related challenges. Finally, practical recommendations for farmers, policymakers, and businesses are provided to support the successful implementation of CAE, highlighting the collaborative efforts needed to overcome existing challenges and realize the full potential of this model. Keywords: Circular Agro-Economies, Agricultural Waste Recycling, Sustainable Agriculture, Resource Efficiency, Rural Development, Profitability in Farming.

ASSESSMENT OF POULTRY FARMERS AWARENESS ON RECORD KEEPING IN JERE LOCAL GOVERNMENT AREA, BORNO STATE, NIGERIA

The study assessed poultry farmers’ awareness on keeping farm record in Jere Local Government Area, Borno State, Nigeria. The research identified the socio-economic characteristics of the poultry farmers, assessed their level of awareness on record-keeping, and determined factors influencing record-keeping among the respondents. The study employed a two-stage sampling technique to select 150 respondents, and data were collected using structured questionnaires. Descriptive statistics such as frequency, percentage, mean, Likert scale, and logistic regression models were employed to analyze the data. The findings revealed that most (46%) of the respondents were aged between 36-51 years with majority (70%) predominantly female, 68% had a mean of 7 persons per household with an average of 7 years of poultry farming experience Majority (85%) of the respondents had attained one form of education or the other. Additionally, more than 80% earned less than ₦30,000 to ₦90,000 per production cycle. Majority (86.7%) had a flock size of less than 90 birds. Additionally, while 70% of the respondents recognized the importance of record-keeping in ensuring farm profitability. Logistic regression analysis showed that education level, flock size, knowledge of record-keeping, and access to extension services were significant at 1% level each. The recommend that, Extension services should prioritize training programs, particularly for women, who form the majority of the farming population. Training programs should focused on the importance of record keeping and practical methods for maintaining records.

Impact of agricultural extension services on rice productivity and profitability in Bangladesh

Agricultural extension services play a pivotal role in promoting sustainable agriculture, particularly in developing countries where many farmers are resource-poor. Enhancing farmers’ profitability and productivity is essential to meet the increasing demand of a growing population. This study aims to examine the impact of agricultural extension services on the profitability and productivity of rice farmers in Bangladesh. The analysis uses unbalanced panel data from the International Food Policy Research Institute’s Bangladesh Integrated Household Survey for 2015 and 2018. The Mann–Whitney U test was used to assess whether the differences between the participant and non-participant groups were statistically significant. Additionally, a probit regression model is used to identify the determinants of participation in agricultural extension services. The findings reveal that participation is positively influenced by access to subsidies, distance to market, occupation and livelihood vulnerability. The impact of agricultural extension services on farm productivity and profitability is assessed using difference-in-difference and random effect generalized least squares models. The results show that agricultural extension services significantly contribute to both farm profitability and productivity. This suggests that governments should intensify and monitor the delivery of agricultural extension services, particularly focusing on the timely provision of support resource-poor farmers.

The LTAR Cropland Common Experiment at Lower Chesapeake Bay.

The Lower Chesapeake Bay (LCB) Long-Term Agroecosystem Research (LTAR) Common Experiment (CE) located in Beltsville, MD, focuses on research of concern to producers of the major regional crops, which are corn (Zea mays L.), soybean [Glycine max (L.) Merr.], wheat (Triticum aestivum L.), and various forage species. Livestock production in the region includes broiler and laying chickens (Gallus gallus domesticus L.) and dairy and beef cattle (Bos taurus L.). The LCB region is among the most heavily populated in the United States. Urban development pressure is high for both farms and natural areas. The need to restore Chesapeake Bay water quality is a major influence on regional agricultural practices. Conservation practices such as cover cropping, no-till agriculture, and nutrient management planning are more common in the region compared to nationally. However, farmers still face management challenges implementing practices that address water quality and the rise of herbicide-resistant weeds. Researchers at the LCB site recognize the need to protect the Chesapeake and Delaware Bays and maintain farmer profitability. The LCB CE compares a 3-year crop rotation system featuring alternative crop management (cover crop intensification, crop rotation diversification, and integrated weed management [IWM]) with a prevailing 2-year system (no cover crops and no IWM), both under continuous no-tillage, to identify the optimal balance to promote the sustainability of regional cropping systems. The LTAR LCB site provides data-driven tools and solutions to support farmers in the mid-Atlantic region.

Livelihood diversification and household welfare among farm households in the Philippines

AbstractDiversification of income sources is one of the most common strategies households employ to minimize household income variability and to ensure a minimum level of income that guarantee their food security. This study examines the impact of livelihood diversification on farm profits among smallholder rice farmers in the Central Luzon Region (CLR) of the Philippines using long‐term farm‐level panel data spanning from 1966 to 2016. We employed a random‐effects ordered probit model to investigate the drivers of livelihood diversification and then used the mixed Markov chain model to analyze the transition of households from less to more diversified livelihoods and its impact on farm profits over time. Our findings reveal substantial diversification among households over time. In particular, the elevation of the farm location is a key driver of rice farm households’ probability to diversify. The estimates show that an increase in the latitude of the farm location increases the probability of rice farmers in the CLR to diversify. We find that 64% of the rice farm households constitute farmers for whom diversification can be a strategy for survival. For medium‐ to high‐profit farm categories, diversification tends to protect farmers against farm profit losses arising from adverse climatic and weather variability.

Transforming agri-food value chains in Bangladesh: A practical application of blockchain for traceability and fair pricing

The agricultural sector is a vital component of Bangladesh's economy, but its agri-food supply chain faces signifi-cant inefficiencies primarily due to the involvement of numerous intermediaries. This complexity not only reduces the profits for farmers but also affects the overall transparency and efficiency of the supply chain. This study aims to em-ploy blockchain technology to transform the traditional agri-food supply chain in Bangladesh, focusing on increasing transparency, enhancing efficiency, and improving profitability for farmers, thus potentially bolstering the entire agri-food ecosystem in the country. The research involves setting up a blockchain-based smart contract on the Ethereum Blockchain network. This approach guarantees that all transactions within the agri-food supply chain are transparent, traceable, and accountable. Additionally, the study develops a web application to facilitate user interaction with the smart contract, enhancing accessibility and usability. Performance analysis and testing of the implemented smart con-tract demonstrate its capability to handle a significant volume of transactions without compromising on performance. The solution effectively reduces the dependency on intermediaries, thereby increasing the profit margins for the farm-ers involved. The integration of blockchain technology in the agri-food supply chain has shown promising results in enhancing transparency and efficiency. It lays a solid foundation for future improvements and suggests a scalable model that could be applied to other sectors within the country to further enhance agricultural practices and economic growth.

Assessment of Reproductive Performance and Husbandry Practices of Horro and Crossbred Cattle Under Smallholder in Sibu Sire District of East Wollega Zone, Oromia, Ethiopia.

The reproductive and production performance of dairy cows determines the profitability of a dairy farm. A questionnaire survey was used to assess reproductive performance and husbandry practices by using 100 randomly selected animal owners. Seventy-nine percent of animal owners involved were men, ages between 30 and 60. Their education was as follows: 26% were illiterate, 67% in primary school and 7% in secondary school. Ninety-five percent of them managed their animals extensively and used natural mating and breeding practices (75%). AFS in months were 46.83±0.65 in Ada-Buke Warego, 46.00±1.36 in Hagalo-Tulam, 47.08±0.99 in Dicho Aba-Garmama and 47.29±0.51 in Waligalte. AFC in months were 56.68±0.97 in Ada-Buke Warego, 58.00±1.36 in Hagalo-Tulam, 57.23±1.41 in Dicho Aba-Garmama and 56.24±1.13 in Waligalte. ANSPCs were 1.85±0.08 in Ada-Buke Warego, 1.67±0.14 in Hagalo-Tulam, 1.54±0.14 in Dicho Aba-Garmama and 2.00±0.10 in Waligalte. The mean length of CI in months was 30.88±0.90 in Ada Buke Warego, 29.00±1.68 in Hagalo-Tulam, 28.62±1.62 in Dicho Aba-Garmama and 31.06±1.04 in Waligalte. The average year of longevity was 9.22±0.7 in Ada-Buke Warego, 9.08±0.8 in Hagalo-Tulam, 9.31±0.13 in Dicho Aba-Garmama and 9.21±0.8 in Waligalte, but there is no significant association (p≥0.05). AFC in months was 48.00±0.00 in local and 37.20±1.30 in crossbreeds. ANSPC was 1.92±0.06 in locals and 1.10±0.10 in hybrids. AFC for Horro and crossbred dairy cattle were 57.73±0.59 and 48.00±0.00months, respectively. The mean length of CI was 30.53±0.67 and 29.40±1.99months in natives and crossbreeds, respectively. The average year of longevity was 9.22±0.05 and 9.10±0.10years for local and hybrids, respectively. ANSPC for natural mating and AI were 1.92±0.05 and 1.10±0.10, respectively, with significant association (p<0.05). The reproductive performance of dairy cows in the study area was low, which required the improvement of husbandry practices.

Automatic cleaning suggestion adapting to real-time soiling status of solar farms

Solar farms are subject to various environmental factors that can affect their performance and output. One of the major factors is soiling. Consequently, it is essential to monitor and mitigate the effects of soiling on solar panels to ensure optimal performance and maximum profitability of a solar farm. In this paper, we present a novel cleaning intervention strategy that adapts to the present solar panel performance status to detect cleaning requirements for maximizing profit. This algorithm works with onsite insolation and panel data to give live feedback on cleaning requirements. Moreover, unlike other models in the literature, this method does not require historical or a priori insolation, weather, or soiling data. We have comprehensively tested the algorithm through experiment and simulation under various conditions (i.e., seasonal rain, few annual rainfall or sandstorms, unpredictable dust accumulation). The results show that the adaptive cleaning algorithm, even with no historical insolation or soiling information, outperforms optimal periodic cleaning strategies in terms of net revenue. The adaptive cleaning suggestion system shows significant advantages especially in locations with high variability in weather and soiling conditions. The algorithm is also suitable for practical deployment in solar farms near industrial or construction zones where sudden dust accumulation can occur. Our adaptive model will maximize profit in such unpredictable soiling scenarios, while in comparison, it is not even possible to utilize historical information-based cleaning cycle model in such cases.

Unintended environmental consequences of anti-corruption strategies

High agricultural profits motivate politicians to collude with local elites and ignore illegal conversion of natural forests. Fighting corruption through fiscal audits can improve local governance in general but may also unintentionally intensify such collusion and rent extraction activities within the less scrutinized forestry sector. This paper highlights such unintended consequences of a federal anti-corruption strategy in Brazil by documenting the causal effects of randomized fiscal audits on deforestation dynamics, a non-targeted outcome. Between 2003 and 2011, public audits of federal funds increased deforestation by about 10% in municipalities of the Brazilian Amazon within the first three years after the audit. The audits triggered forest loss, especially during election years, in municipalities governed by first-term mayors who managed to win re-elections afterward, and in places with a high share of cattle ranching, indicating potential collusion between local politicians and the agricultural sector.

Impacts of winter crop choice and ewe body condition score change on whole farm profitability and production

Variations in body condition score (BCS) in ewes influences lamb survival, ewe survival and ewe lactation performance. Feeding a low protein diet such as fodder beet to ewes in mid-to-late pregnancy increases lamb losses and reduces lamb weaning weight even further. However, using high yielding forages such as fodder beet can reduce the area of winter crop required, introducing potential whole-farm benefits which may alter profitability. We analysed the effects of winter crop choice (brassica or fodder beet) and BCS (maintaining or reducing) on whole-farm production and profitability, using a targeted supplement to offset the impacts of fodder beet feeding. Eight farms were selected to represent low or high rainfall (590 and 1090 mm/annum respectively) regions of the South Island. Impacts of changing BCS on ewe and lamb survival at lambing, and lamb liveweight gain to weaning were calculated when fed either adequate (brassica) or low protein (fodder beet) diets in mid-to-late pregnancy. Production statistics and profitability were calculated using Farmax. Whole farm profitability was analysed using BCS change and winter forage crop as main treatments, blocked by low or high rainfall. Applying the effects of BCS and low protein diets on reproductive performance from prior published studies resulted in variation of 102 to 141 lambs weaned per 100 ewes mated, with the lowest value when the low protein, fodder beet only diet was used. Greatest number of lambs weaned was achieved when BCS was maintained through winter through provision of a balanced supplement, regardless of winter forage diet (P&lt;0.05). Lamb sale dates were later when fodder beet was used, due to lower lamb weaning weights, resulting in marginally higher prices due to changes in pricing schedule. Farm profitability was increased by 25% when BCS was maintained though winter (P&lt;0.05) irrespective of the diet used. Use of fodder beet must be accompanied by targeted supplementation to avoid ewe BCS loss increased lamb losses and the negative effects on wastage and animal welfare. Extra profitability could only be generated by opportunities to sell surplus feed during the summer. These responses were similar in both high and low rainfall environments. This study is unique in testing measured responses of BCS and targeted nutritional supplementation under specific physiological conditions on whole-farm profitability. Farmer decisions on feed utilisation and sale also have a significant influence on the potential to mitigate the effects of variations in winter forage choice.

Risk Management of Green Bean Farming Production in Gluranploso Village, Gresik District

Green beans are the most important food crop in Indonesia and production continues to increase to meet domestic demand. However, production is still insufficient due to several risks faced by farmers. This research analyzes the risk management of green bean production in Gluranploso Village using the Coefficient of Variation (KV) and Failure Mode and Effect Analysis (FMEA) methods. The results showed that yield variation was relatively low with a KV value of 17%, indicating good yield stability. The FMEA analysis identified four main sources of risk affecting production: seed aspect with an RPN value of 5.808, weather with an RPN value of 7.04, pests and diseases with an RPN value of 12.936, and technical aspects with an RPN value of 47.88, particularly delays in pest and disease control spraying. In addition, the market aspect is also a source of risk with the largest value in the increase in production input prices at 12.288. These sources require special attention in risk management. The study concludes that the implementation of appropriate risk management strategies, focusing on the identified key risk sources, can help farmers improve yield stability and farm profitability. These strategies include improving seed quality, mitigating weather risks, controlling pests and diseases, and improving technical procedures in cultivation and market risks. Thus, effective risk management can be key in increasing the productivity and sustainability of green bean farming in Gluranploso village.

Socio-Demographic Characteristics and Adoption of Mobile Phone Applications for Improved Small-scale Commercial Agriculture in Makonde District, Zimbabwe

Mobile applications have provided a new way for agricultural transformation. This is set to revolutionise the agriculture sector with easy access to vital agricultural information on weather, market trends, pest, and disease management, and best agriculture practices to enhance agricultural productivity and profitability. However, there is a dearth of studies on the adoption of mobile applications in agriculture. It was important for this study to understand the impact of farmers’ demographic characteristics on the adoption of mobile applications in small-scale commercial agriculture. The study applied the quantitative research approach, a sample size of 213 small-scale commercial farmers, a descriptive cross-sectional research design, and the structured household questionnaire survey instrument, purposive random and stratified sampling techniques to collect primary data. Data was analyzed using descriptive statistics. The findings of the study revealed a higher adoption rate of mobile applications among young farmers than old farmers. The study indicated that female small-scale commercial farmers adopted mobile applications than male farmers. The study revealed that the majority of small-scale commercial farmers were literate. Further, the study highlighted that married farmers exhibited a greater tendency to adopt mobile applications than single, divorced, separated, and widowed. Furthermore, the study revealed that the majority of small-scale commercial farmers were engaged in agriculture as their primary occupation. The study argued that young farmers, female farmers, educated farmers, married farmers, and farming as a primary occupation positively influenced the adoption of mobile phone applications for improved small-scale commercial agriculture. The study recommends that policymakers and implementers should consider socio-demographic characteristics as critical determinants of the adoption of mobile phone applications for improved small-scale commercial agriculture to tailor strategies that promote the adoption of mobile applications based on different farmer age groups

Mendekatkan Rumput Laut ke Masyarakat: Program Sosialisasi dan Pendidikan untuk Peningkatan Ekonomi Desa Ulidang, Majene

Ulidang Village, part of the Tameroddo Sub-district, has excellent potential in the fisheries and marine sector, although it still faces significant economic challenges. The potential of seaweed as a marine resource that has yet to be fully utilized is the focus of this activity. The main objective is to provide comprehensive counseling on the potential of seaweed, including cultivation methods, nutritional content, and business management aspects. This activity's implementation stage starts with planning, program implementation, and evaluation. The research results showed that socialization efforts, including explanations of seaweed potential, business management, and farming profit simulations, have provided the community with a deep understanding. The pretest and post-test evaluations illustrated the improvement in participants' understanding after the socialization activities. Thus, the development of seaweed farming in Ulidang Village can be a solution to improve community welfare, create jobs, and care for the marine environment. Strategic steps include strong partnerships, community empowerment, and adoption of innovations to ensure the sustainability of seaweed farming at the local and national levels.

Farmer Assessment of the Effectiveness of Empowerment Strategies to Increase Farming Profits

Farmer empowerment is crucial for agricultural development, yet its effectiveness often depends on how well strategies align with farmers' needs. This research aims to determine the effectiveness of the farmer empowerment strategies according to the farmer assessment. The research employs a qualitative multi-case study approach, utilizing in-depth interviews and focus group discussions with farmer group chairmen and members. The study reveals varying levels of effectiveness across seven government-implemented empowerment strategies. These three strategies comprised developing agricultural product marketing systems, consolidating agricultural land, and providing access to science and technology were unfamiliar to participants. The organic fertilizer training strategy was deemed effective in improving competence and profits. Extension services were considered effective in enhancing competence, profits, and productivity. However, institutional strengthening strategies were seen as ineffective in developing farmer groups into cooperatives. Financing facilities through People's Business Credit (PBC).

Maintaining Agricultural Production Profitability—A Simulation Approach to Wheat Market Dynamics

Profitability is a complex notion, intertwined with theoretical, socio-economic, and modern economic considerations. While traditionally linked to monopoly advantages, contemporary views broaden this to include shareholder value creation. In agriculture, profitability faces impediments such as rising input costs, market volatility, and economic disparities, emphasizing technological innovation, market conditions, and policy as crucial determinants. This study presents an econometric simulation model to analyze and forecast wheat production profitability in Poland from 2023 to 2027, providing insights into production efficiencies, market dynamics, and policy impacts. Using a system of recursive equations, the model forecasts profitability, integrating econometric techniques with expert insights. It examines variables like resource use, production levels, and price changes, validated through FADN data. The findings reveal that price relations and production efficiencies are the key to profitability. The model highlights market volatility, particularly through “price scissors”, as the main factor influencing profitability. Favorable price conditions significantly boost profitability and incentivize production. The model is a critical tool for analyzing wheat profitability, highlighting the influence of market and policy changes. Future work could extend the model’s use to other regions or crops, incorporating advanced technologies to improve accuracy. This study offers valuable insights for agricultural economics, aiding stakeholders in strategic decision-making.