Agricultural Issues Research Articles

Study on optimization of maize irrigation scheduling in Shaanxi Province

With the impact of climate change in recent years, the instability of precipitation and the increase of evaporation have made water resources in Shaanxi Province more and more stressed. How to maintain stable economic development while ensuring the sustainable development of agriculture within the limited water resources has become an important issue facing Shaanxi Province. This paper analyzes the temporal and spatial distribution characteristics of maize irrigation water requirement in Shaanxi Province based on meteorological data and obtains the ideal irrigation water requirement. However, considering the agricultural water scarcity issue in this region, this paper establishes different water scarcity scenarios, adopts the Jensen model to construct an objective function aimed at minimizing crop yield reduction, and solves it using a genetic algorithm to obtain the optimized maize irrigation scheduling under different water scarcity scenarios. The results analysis indicates the following: (1) The effective rainfall in Shaanxi Province from 1960 to 2019 shows a slight upward trend, while the maize water requirement and maize irrigation water requirement shows a downward trend. (2) The spatial distribution of maize irrigation water requirement in Shaanxi Province decreases gradually from north to south. High-value areas are mainly distributed in the northern regions of Yulin City and Yan’an City in Shanbei. Low-value areas are distributed in Ankang City in Shannan. (3) In the face of water scarcity, spring maize should ensure water use during the middle growth period, fast development period, and initial growth periods. Under the same water scarcity conditions, the yield reduction rate is the highest in Guanzhong, followed by the Shannan, and the lowest in Shanbei. This paper aims to provide a scientific and reasonable optimization plan for maize irrigation in Shaanxi Province by calculating and analyzing the maize irrigation water requirement in Shaanxi Province, combined with optimization tools such as genetic algorithms, to address the challenges brought by water resource constraints.

Framing Agricultural Labor Issues: An Analysis of News Coverage of the H-2A Program

Framing Agricultural Labor Issues: An Analysis of News Coverage of the H-2A Program

Optimal strategies for contract farming supply chain with government subsidies under e-commerce assistance to farmers.

The agricultural issue is a focal point of concern for each country, and e-commerce assistance to farmers, as an emerging model, is gaining increasing attention. Considering this trend, this paper bases on e-commerce assistance to farmers and considers four types of government subsidies: no subsidy, price subsidy model with the farmer as the subsidy target, price subsidy model with the e-commerce platform as the subsidy target, and area subsidy model. Based on this, a game model of the contract farming supply chain involving a farmer and an e-commerce platform was established to explore the optimal decision-making in the contract farming supply chain considering various government subsidies under the background of e-commerce assistance to farmers. The results indicate that: (1) Consumer preference for supporting farmers and consumer premiums can stimulate the farmer to expand farm size, increase agricultural production, increase the purchase price of agricultural products and promote the growth of profits for the farmer and the e-commerce platform, contributing to the growth of social welfare. Output volatility can lead to a decrease in farm size and a reduction in the purchase price of agricultural products. (2) Government subsidies can support the farmer in expanding farm size and contribute to increased profits for the farmer and the e-commerce platform. However, government subsidies do not universally have a positive impact on every variable. The influence of government subsidies on the purchase price of agricultural products is contingent upon the method of subsidy distribution. Similarly, the effects of government subsidies on social welfare are influenced by factors such as price elasticity and agricultural productions per unit area. (3) From the perspectives of farm size, the purchase price of agricultural products, and profits of the farmer and the e-commerce platform, the government will have different and more targeted subsidy models, and the corresponding subsidy models are influenced by the agricultural productions per unit area. The research conclusion can provide references for optimal decision-making in contract farming under the model of e-commerce assistance to farmers.

Spatial and Temporal Patterns of Rainfall Erosivity in Southern Africa in Extreme Wet and Dry Years

Soil erosivity is a key indicator of the effectiveness of precipitation acting on the land’s surface and is mainly controlled by event-scale and seasonal weather and climatic factors but is also influenced by the nature of the land’s surface, including relief and vegetation cover. The aim of this study is to examine spatial and temporal variations in soil erosivity across southern Africa using rainfall data for the period 2000–2023 and a gridded raster spatial modelling approach. The two wettest and driest years in the record (±>1.5 standard deviation of rainfall values) were identified, which were 2000 and 2006, and 2003 and 2019, respectively. Monthly rainfall values in these extreme wet/dry years were then analyzed for four rainfall regions (arid, semiarid, subhumid, humid), identified according to their annual rainfall totals. These data were then used to calculate Precipitation Concentration Index (PCI) values as an expression of rainfall seasonality, and the modified Fournier index (MFI) was used to quantify rainfall erosivity. The results show that there are significant differences in erosivity between the different climate regions based on rainfall seasonality and also their distinctive environmental settings. In turn, these reflect the synoptic climatic conditions in these regions, their different precipitation sources, and rainfall totals. The results of this study show that calculated MFI values at the national scale, which is the approach taken in most previous studies, cannot effectively describe or account for erosivity values that characterize different climatic regions at the sub-national scale. Furthermore, the mismatch between PCI and MFI spatial patterns across the region highlights that, under semiarid, and highly seasonal rainfall regimes, episodic rainfall events interspersed with periods of dryness result in significant variability in erosivity values that are unaccounted for by rainfall totals or seasonality alone. In these environments, flash floods and wind erosion result in regional-scale soil erosion and land degradation, but these processes and outcomes are not clear when considering MFI values alone. Fully evaluating spatial and temporal patterns of erosivity in their climatic and environmental contexts, as developed in this study, has implications for sediment and carbon exports, as well as identifying the major regions in which land degradation is an environmental and agricultural issue.

A Methodological Framework to Enhance Potential Spatial Planning to Support Agroecological Transition at the Scale of Local Territories

Agroecological transition requires research and actions at the scale of local territories, in which agricultural activities interact with the environment and natural resources depending on a territory’s spatial configuration. To support the agroecological transition, there is an urgent need to design and implement new spatial configurations. For this, local public authorities in France can be considered as an interesting level of governance, because of their skills in spatial planning and their interest in agriculture, to ensure the ecological transition of their territory. However, new methodological frameworks need to be developed to support the design of new spatial configurations of territories, by constructing representations of the territory that consider both agricultural and socio-environmental issues, and by involving agricultural and non-agricultural stakeholders so that both can project themselves into the new spatial configurations. We developed a new methodological framework at the interface between landscape agronomy and landscape architects’ approaches, and experimented with applying this framework in the Urban Community of Dunkirk (UCD), which was performing a spatial planning approach called a Landscape Plan and proposing to create an Agricultural Park. The results show that the implementation of the methodological framework enabled the construction of a spatially explicit and place-based representation including the spatial issues of farming systems. These representations enable a local authority’s stakeholders to enhance their knowledge of the agricultural issues and consider changes in the spatial configuration of the Agricultural Park. In the discussion, we question the adaptation of the framework in rural territory and highlight the limitations of local authorities as the level of governance at which to address the agroecological transition at the territorial scale.

Salinity challenges and adaptive strategies in salinization-affected coastal Bangladesh: Implications for agricultural sustainability and water resource management

Abstract Salinization has become a rising global concern due to its notable effects on agriculture and freshwater resources. Coastal region of Bangladesh has been struggling with elevated levels of soil and water salinity, exacerbated by storm surges and rising sea levels. We assessed nutrient and salinity contents in agricultural and homestead lands, and the level of salinity in pond and canal water in six sub-districts in coastal Bangladesh. Finally, using household (HH) survey, focus group discussion (FGD) and key informant interview (KII), we explored the adaptive practices and challenges of salinity issues in agriculture and drinking water management. Soil nitrogen, phosphorus, and potassium contents exhibited significant variations across the sub-districts, which reflect the diversity of agricultural practices and soil management strategies. However, there was no notable difference in soil salinity across the sub-districts, which underscores the commonality of soil salinity as a pressing concern. Shyamnagar (13.99 dS m−1) recorded the highest level of pond water salinity, followed by Assasuni (13.96 dS m−1), Dacope (13.91 dS m−1), Koyra (13.58 dS m−1), Morrelganj (13.33 dS m−1), and Mongla (13.19 dS m−1) sub-districts, which highlights that water salinity decreased from exposed coast to the landward areas. Respondents in HH surveys, FGDs and KIIs identified salinity as a major challenge in agriculture and drinking water. Furthermore, climate-related stresses were recognized as significant challenges impacting crop productivity. The research highlights the feasibility of rainwater harvesting, with 89%–100% of HHs harvest rainwater in HH tanks, as an effective adaptive practice for managing drinking water. The study emphasizes the positive impact of vermicompost in reducing soil salinity levels, which is demonstrated by the 43%–88% of HHs using this practice, indicating its potential as a nature-based solution to address soil salinization. The findings underscore the need for resilient agricultural systems and sustainable water management approaches to tackle these challenges.

Gender, Issue Stereotypes, and the Electoral Returns to Distributive Politics in the United States

Elected officials can often successfully increase voter support in their district by “bringing home the bacon,” yet theory suggests that the electoral effects of such efforts may depend on the legislator’s gender and whether the legislator delivered benefits in a stereotypically feminine (e.g., healthcare) or masculine (e.g., agriculture) issue area. Using both observational and experimental data in the United States, we find weak, limited evidence that issue area conditions the electoral impact of credit claiming for legislators of either gender. In addition, we show that men and women are rewarded comparably when they secure benefits for their district, regardless of issue area. Our findings suggest that women legislators — typically more effective than men at securing these benefits — can use distributive politics and credit claiming as an effective electoral strategy without concern that issue-based gender biases in the electorate will get in the way.

Carbon footprint calculating for fruit processing and storage activities

Food production plays a significant role in greenhouse gas emissions. Addressing these issues in agriculture and production requires strategies that consider regional and national contexts while ensuring food security. There is no universal solution for agro-processing sector; thus, research and adaptable tools must be employed based on local conditions. The research were focused on analysis of fruit paste production technology, refrigerated storage and transport. As a result, a calculating carbon footprint method for these processes was developed. Conclusions of this research can be of great value to agri-food industry, enabling producers to make more informed decisions about energy efficiency and reducing greenhouse gas emissions. This makes it possible to move toward more sustainable and environmentally friendly production, while ensuring high quality products throughout their shelf life.

Evaluating machine learning performance in predicting sodium adsorption ratio for sustainable soil-water management in the eastern Mediterranean

Soil salinization is a critical global issue for sustainable agriculture, impacting crop yields and posing a threat to achieving the Sustainable Development Goal (SDG) of ensuring food security. It is necessary to monitor it in detail and uncover its underlying factors at a regional scale. In this context, the present study aimed to evaluate soil health in the eastern Mediterranean region by using the Sodium Adsorption Ratio (SAR) as an indicator of soil salinity in three distinct soil horizons. The main objective of the research was to evaluate the performance of four machine learning (ML) models, including Random Forest (RF), Nu Support Vector Regression (NuSVR), Artificial Neural Network-Multi Layer Perceptron (ANN-MLP), and Gradient Boosting Regression (GBR), for accurate prediction of SAR following the Recursive Feature Elimination (RFE) as a feature selection method. Moreover, SHapely Additive exPlanations (SHAP) was applied as sensitivity analysis to identify the most influential covariates. Main findings of the research revealed that the average clay content in the surface horizon (H10-25cm) was 50.5% ± 10.4, which significantly increased to 57.5% ± 8.7 (p < 0.05). No significant mean differences were detected between the studied horizons for SAR and Na+. ML output revealed that NuSVR outperformed other algorithms in accurately predicting outcomes during both the training and testing stages. Moreover, Scenario 2 (SC2) with seven selected features from the RFE method facilitated highly accurate SAR predictions. Overall, the performance of ML models is ranked as NuSVR > GBR > ANN-MLP > RF. Lastly, SHAP sensitivity analysis identified CEC, Ca+2, Mg+2, and Na+ as the most influential variables for SAR prediction in both the training and testing stages. Hence, the research yielded valuable insights for efficient agricultural soil management at a regional level using state-of-the-art technology.

Who (actually) gets the farm? Intergenerational farm succession in the United States

AbstractFarm succession is a central issue in agricultural policy. Yet although many studies explore succession planning, little is known about how farms are actually transferred. We provide the first population‐level evidence on intergenerational farm succession by linking US census records for millions of farmers' children in 1900 and 1910 to identify which children own and operate the family farm up to 40 years later. We first show that daughters are rarely successors. Using a within‐family identification strategy, we find that first‐born sons are slightly more likely than their younger brothers to be successors while their parents are working aged. However, birth order is not predictive of who receives the farm when parents are older or deceased. For later farm transfers, sons who were previously tenant farmers are much more likely than their brothers to be successors, possibly because they are better prepared. Fewer than one‐fifth of farmers transfer their farm to any son. Our study relies on rich historical data because current policy prevents the necessary data linkages for studying intergenerational farm succession. Providing a secure system for researchers to link modern agricultural data to population microdata, similar to what has been achieved with other data sources, would yield crucial insights into long‐term agricultural policy issues in the US.

Feasibility study of floating solar photovoltaic systems using techno-economic assessment and multi-criteria decision-making method: A case study of Bangladesh

Many developing countries with abundant solar resources and rich history of agriculture, face overpopulation and land shortage issues. Floating solar photovoltaics (FSPVs) do not compete with agriculture for land and offer higher energy potential than land-based photovoltaics (LBPVs). For feasibility and site suitability evaluation of FSPVs, this study proposes an integrated approach of techno-economic assessment (TEA) and multi-criteria decision making (MCDM), based on a case study of Bangladesh. The system advisor model (SAM) was used to conduct TEA, evaluating the potential of nine FSPV sites on a regional scale using ten criteria. Combined compromise solution (CoCoSo) was implemented to determine the optimum site. Bergobindopur lake was ranked top, with the highest energy yield and lowest cost of energy of 1564 kWh/kW and $0.055/kWh respectively. Case study of Bergobindopur revealed buy-all-sell-all electricity tariff was more profitable than net billing and net metering. Energy generation was found to be influenced by tilt angle and soiling. Sensitivity analyses demonstrated the superiority of FSPVs over LBPVs for varying electricity prices, degradation and discount rates, project durations, and investor's equities. Longer project durations and lower equities resulted in higher profits for investors. The proposed approach contributes to the expansion of FSPV in land-constrained areas.

A custom pipeline for building computational models of plant tissue

Stalk lodging in the monocot Zea mays is an important agricultural issue that requires the development of a genome-to-phenome framework, mechanistically linking intermediate and high-level phenotypes. As part of that effort, tools are needed to enable better mechanistic understanding of the microstructure in herbaceous plants. A method was therefore developed to create finite element models using CT scan data for Zea mays. This method represents a pipeline for processing the image stacks and developing the finite element models. 2-dimensional finite element models, 3-dimensional watertight models, and 3-dimensional voxel-based finite element models were developed. The finite element models contain both the cell and cell wall structures that can be tested in silico for phenotypes such as structural stiffness and predicted tissue strength. This approach was shown to be successful, and a number of example analyses were presented to demonstrate its usefulness and versatility. This pipeline is important for two reasons: (1) it helps inform which microstructure phenotypes should be investigated to breed for more lodging-resistant stalks, and (2) represents an essential step in the development of a mechanistic hierarchical framework for the genome-to-phenome modeling of herbaceous plant stalk lodging.

Gleaning Rural Journalism: Rural Journalists' Agricultural and Environmental Reporting Utilizing Community Storytelling Networks☆

AbstractEnvironmental concerns are growing in parts of the rural United States as drinking water wells become contaminated with agrichemicals, and climate change impacts such as drought and extreme rain events disrupt farming practices. Analyzing in‐depth interviews with 29 U.S. rural journalists, we explore the role rural journalists play when reporting on the environment as it relates to agricultural issues. Findings show that reporting about the environment—such as weather, climate change, water shortages, and droughts—appear in rural journalists' stories given those topics' relevance to their rural communities and the social systems forces exerting influence on journalists, yet rural journalists often do not perceive themselves as doing environmental reporting. Rural journalists also report lacking training and resources to do environmental reporting. This study points to the need for more support for rural journalists' environmental reporting as one way to build social change and maintain local community.

The future of agricultural data-sharing policy in Europe: stakeholder insights on the EU Code of Conduct

In 2018, the EU Code of Conduct of Agricultural Data Sharing by Contractual Agreement (EUCC) was published. This voluntary initiative is considered a basis for rights and responsibilities for data sharing in the agri-food sector, with a specific farmer orientation. While the involved industry associations agreed on its content, there are limited insights into how and to what extent the EUCC has been received and implemented within the sector. In 2024, the Data Act was introduced, a horizontal legal framework that aims to enforce specific legal requirements for data sharing across sectors. Yet, it remains to be seen if it will be the ultimate solution for the agricultural sector, as some significant agricultural data access issues remain. It is thus essential to determine if the EUCC may still play a significant role to address sector-specific issues in line with the horizontal rules of the Data Act. During six workshops across Europe with 89 stakeholders, we identified how the EUCC has been (1) received by stakeholders, (2) implemented, and (3) its future use (particularly in response to the Data Act). Based on the workshop results and continued engagements with researchers and stakeholders, we conclude that the EUCC is still an important document for the agricultural sector but should be updated in response to the content of the Data Act. Hence we propose the following improvements to the EUCC: 1. Provide clear, practical examples for applying the EUCC combined with the Data Act; 2. Generate model contractual terms based on the EUCC provisions; 3. Clarify GDPR-centric concepts like anonymisation and pseudonymisation in the agricultural data-sharing setting; 4. Develop a functional enforcement and implementation framework; and 5. Play a role in increasing interoperability and trust among stakeholders.

Novel biopolymeric chitosan-urea-based core-shell hydrogel for use in sustainable agriculture

Agricultural sustainability is a major issue in recent times, deficiency of water as well as insufficient fertilizer to the crop is a main reason for it. This work is focused on core-shell hydrogel aiming to overcome the agricultural issues of water as well as deficiency of fertilizer to the plant. The core-shell hydrogel was prepared by incorporating urea in κ-carrageenan to be part of the controlled release mechanism of the core of the hydrogel. Chitosan was used for the shell structure to prepare over the core and cross-linked by the cations of the salts. The prepared hydrogel was termed as Chitosan-κ-carrageenan-Urea (CK-CU). Four different types of hydrogels were prepared with the different compositions named as CK-CU 2, CK-CU 5, CK-CU 7.5 and CK-CU 10 as varying with the ratio of 2 %, 5 %, 7.5 % and 10 % of urea respectively. The core-shell morphology structure was verified with Scanning electron microscopy (SEM) in which the complete coverage of the κ-carrageenan core by a consistent chitosan shell has been verified. Fourier transform infrared spectroscopy (FTIR) was utilized to confirm the composition of the hydrogel. Thermo-gravimetric analysis (TGA) was also performed for checking the thermal endurance of the hydrogel. The release rate of the urea was determined under Ultraviolet Visible spectroscopy. The swelling index, dewatering, and urea release rate of optimized CK-CU 10 hydrogel were found to 121 %, 21.22 %, and 70.4 % respectively. The developed Core-Shell hydrogel exhibits significant promise as a vehicle for fertilizer and as a soil conditioner in agricultural applications especially in arid and semi-arid areas.

The Environmental Footprint of Available Food Waste in Young Households: A Diary Case Study of Schleswig-Holstein (Germany)

As households contribute significantly to food waste, it can be assumed that they bear considerable responsibility for the environmental footprint of it. In Germany, household food waste comprises over half of all food loss and waste, with a notable share attributable to young people. To explore their environmental footprint, data from fifty young households in Schleswig-Holstein, northern Germany, is analyzed using the Food Loss and Waste Value Calculator with an integrated life cycle assessment. We evaluate the environmental footprint of animal and plant food waste across five categories: climate change, water scarcity footprint, soil quality index, phosphorus and nitrogen eutrophication. Surprisingly, animal food waste, though representing only 18% of the total volume of all available food waste in our study, exhibits a more substantial impact in all categories except water scarcity. Specifically, animal food waste is found to be an important factor in soil degradation. Our results generally indicate an inverse relationship between the volume of animal-based and plant-based food waste in young households and its environmental footprint. However, the case study highlights a troubling connection between plant food waste and significant water scarcity issues in European agriculture.

School Factors Influencing the Choice of Agriculture Subject among Girls in Post-primary Education in Gusii Counties, Kenya

Kenya's economy relies heavily on agriculture, making it essential to integrate agricultural education into secondary school curricula. This study aimed to assess how school-related factors influence female students' decisions to pursue agriculture in post-primary institutions in Gusii counties, Kenya. The study emphasized Gusii counties because of their low girls’ enrolment in agriculture compared to boys. A descriptive survey approach was employed, focusing on 9,000 form three girls from 470 schools with mixed and all-girl student populations. The study concentrated on form three girls enrolled in agriculture, as their longer time in school has exposed them more to agricultural issues. The sample comprised 368 girls studying agriculture, selected through simple random and purposive sampling methods. Data was collected via questionnaires, with pilot testing to ensure validity and reliability. Analysis was conducted using SPSS version 21, employing graphs, means, frequencies, and standard deviations. Pearson’s correlation coefficient was used to determine the impact of various factors at a 0.05 confidence level. Results showed significant correlations: previous agriculture grades (r=.428), availability of land for farming (r=.605), supportive and motivating teachers (r=.257), adequate facilities (r=.196), and sufficient teachers (r=.775). To encourage more girls to choose agriculture, the study recommends that the Teachers Service Commission recruit more trained agriculture teachers in understaffed schools, schools provide adequate teaching materials, and career counsellors offer informed guidance. These findings will help the Ministry of Education develop policies targeted at increasing female participation in agriculture and understanding barriers preventing girls from pursuing this field

Biochar Production from Plant Residues: A Sustainable Approach for Carbon Sequestration and Soil Fertility Improvement

This review article explores the sustainable practice of producing biochar from plant residues, effectively transforming green waste into a valuable resource commonly referred to as “green gold”. It discussed mainly on the pyrolysis process of biochar production, and the impact of different pyrolysis methods on the resulting biochar's properties, including surface area, porosity, and nutrient holding capacity. Further, the review analyzes the multifaceted benefits of biochar for soil health and plant growth. It highlights how biochar can improve soil structure, increase water retention, and enhance nutrient availability, leading to healthier and more productive agricultural lands. Additionally, the review explores biochar's potential in influencing the soil microbial community, potentially promoting beneficial organisms and suppressing harmful pathogens. It also explores biochar's role in mitigating climate change by capturing and storing atmospheric carbon, effectively reducing greenhouse gas emissions. However, a balanced perspective is maintained by acknowledging potential drawbacks associated with biochar use, such as the need for further research to optimize production methods and potential negative impacts on certain soil fauna. This review highlights biochar's promise as a sustainable, cost-effective solution for agriculture and environmental issues. Biochar adoption can lead to a greener future through carbon capture, soil health, and waste management.

Organic Agriculture for Sustainable Food Systems: A Comprehensive Review of Benefits and Constraints

The global population is increasing at a rapid pace, posing significant challenges to sustainable development and food security. This review paper examines the advantages and challenges of organic farming as a potential solution to address the pressing issues in modern agriculture and food production. Organic farming offers a range of benefits, including improved soil fertility, higher profitability, reduced external input usage, land reclamation, improved market access, and enhanced farmer capacity and self-reliance. Organic farming practices prioritize environmental sustainability by reducing chemical usage and reliance on biological methods of pest control, as well as enhancing biodiversity, which strengthens ecological balance and resilience against pests and diseases. However, organic farming also faces challenges that need to be addressed for its widespread adoption. These challenges include uncertainty surrounding legislative environments, psychological and sociological costs of conversion, financial risks during the transition period, securing marketing channels for organic produce, and diminishing profit margins. Efforts should be made to provide farmers with the necessary support, including technical assistance, subsidies, and access to markets, to overcome these challenges. Despite the challenges, the potential of organic farming in promoting sustainable agriculture and ensuring a secure food system cannot be overlooked. It offers a natural and environmentally friendly approach to food production, prioritizing the health of both humans and the ecosystem.

Unveiling innovation imperatives in agriculture: A data-driven framework for identifying latent needs and regional priorities

Innovation within a company, sector, or territorial context can arise from identifying specific problems or needs. Performance analysis provides valuable insights, potentially highlighting areas where innovation may be necessary. This paper outlines a methodology designed to identify latent innovation needs at regional, sectoral, and dimensional levels. This methodology is based on critical issues emerging from comparing economic, environmental, and social sustainability indicators of farms. An iterative approach is used for this purpose. Mixed matching algorithms are employed to form the comparison groups, while G-computation is used to calculate the differences. Logistic regression is adopted to calculate the propensity scores, and several generalized linear models are used to estimate the impact of regional localization. Hypothesis tests are then conducted to confirm the statistical significance of the impacts, from which criticality levels are derived. This methodology is applied to data collected by the Italian Farm Accountancy Data Network, which includes over 64,000 observations from two consecutive three-year periods (2016-2018 and 2019-2021). The results highlight the existence of widespread critical issues in Italian agriculture. These problems primarily concern the efficient use of water, whose costs, relative to revenue, exceed, on average, around 40 %, and greenhouse horticulture, which shows an increased criticality level in terms of sustainability of over 50 %. From a regional perspective, Puglia in Southern Italy exhibits the most evident critical issues, with an average criticality level of 30 % that has increased over time. The emerging criticalities are analyzed in relation to the interventions introduced by the 2023-2027 Common Agricultural Policy to verify their coherence and identify possible innovative actions that can be implemented.