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Search Results (160)

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Keywords = agri-environmental modelling

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21 pages, 4147 KiB  
Article
AgriFusionNet: A Lightweight Deep Learning Model for Multisource Plant Disease Diagnosis
by Saleh Albahli
Agriculture 2025, 15(14), 1523; https://doi.org/10.3390/agriculture15141523 - 15 Jul 2025
Viewed by 472
Abstract
Timely and accurate identification of plant diseases is critical to mitigating crop losses and enhancing yield in precision agriculture. This paper proposes AgriFusionNet, a lightweight and efficient deep learning model designed to diagnose plant diseases using multimodal data sources. The framework integrates RGB [...] Read more.
Timely and accurate identification of plant diseases is critical to mitigating crop losses and enhancing yield in precision agriculture. This paper proposes AgriFusionNet, a lightweight and efficient deep learning model designed to diagnose plant diseases using multimodal data sources. The framework integrates RGB and multispectral drone imagery with IoT-based environmental sensor data (e.g., temperature, humidity, soil moisture), recorded over six months across multiple agricultural zones. Built on the EfficientNetV2-B4 backbone, AgriFusionNet incorporates Fused-MBConv blocks and Swish activation to improve gradient flow, capture fine-grained disease patterns, and reduce inference latency. The model was evaluated using a comprehensive dataset composed of real-world and benchmarked samples, showing superior performance with 94.3% classification accuracy, 28.5 ms inference time, and a 30% reduction in model parameters compared to state-of-the-art models such as Vision Transformers and InceptionV4. Extensive comparisons with both traditional machine learning and advanced deep learning methods underscore its robustness, generalization, and suitability for deployment on edge devices. Ablation studies and confusion matrix analyses further confirm its diagnostic precision, even in visually ambiguous cases. The proposed framework offers a scalable, practical solution for real-time crop health monitoring, contributing toward smart and sustainable agricultural ecosystems. Full article
(This article belongs to the Special Issue Computational, AI and IT Solutions Helping Agriculture)
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36 pages, 74051 KiB  
Review
ObjectDetection in Agriculture: A Comprehensive Review of Methods, Applications, Challenges, and Future Directions
by Zohaib Khan, Yue Shen and Hui Liu
Agriculture 2025, 15(13), 1351; https://doi.org/10.3390/agriculture15131351 - 24 Jun 2025
Viewed by 951
Abstract
Object detection is revolutionizing precision agriculture by enabling advanced crop monitoring, weed management, pest detection, and autonomous field operations. This comprehensive review synthesizes object detection methodologies, tracing their evolution from traditional feature-based approaches to cutting-edge deep learning architectures. We analyze key agricultural applications, [...] Read more.
Object detection is revolutionizing precision agriculture by enabling advanced crop monitoring, weed management, pest detection, and autonomous field operations. This comprehensive review synthesizes object detection methodologies, tracing their evolution from traditional feature-based approaches to cutting-edge deep learning architectures. We analyze key agricultural applications, leveraging datasets like PlantVillage, DeepWeeds, and AgriNet, and introduce a novel framework for evaluating algorithm performance based on mean Average Precision (mAP), inference speed, and computational efficiency. Through a comparative analysis of leading algorithms, including Faster R-CNN, YOLO, and SSD, we identify critical trade-offs and highlight advancements in real-time detection for resource-constrained environments. Persistent challenges, such as environmental variability, limited labeled data, and model generalization, are critically examined, with proposed solutions including multi-modal data fusion and lightweight models for edge deployment. By integrating technical evaluations, meaningful insights, and actionable recommendations, this work bridges technical innovation with practical deployment, paving the way for sustainable, resilient, and productive agricultural systems. Full article
(This article belongs to the Section Artificial Intelligence and Digital Agriculture)
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28 pages, 1393 KiB  
Article
Integrated Economic and Environmental Dimensions in the Strategic and Tactical Optimization of Perishable Food Supply Chain: Application to an Ethiopian Real Case
by Asnakech Biza, Ludovic Montastruc, Stéphane Negny and Shimelis Admassu Emire
Logistics 2025, 9(3), 80; https://doi.org/10.3390/logistics9030080 - 23 Jun 2025
Viewed by 560
Abstract
Background: The agri-food sector is a major contributor to environmental degradation and emissions, highlighting the need for sustainable practices to mitigate its impact. Within this sector, perishable food crops require targeted efforts to reduce their environmental footprint. Vertical integration is crucial for ensuring [...] Read more.
Background: The agri-food sector is a major contributor to environmental degradation and emissions, highlighting the need for sustainable practices to mitigate its impact. Within this sector, perishable food crops require targeted efforts to reduce their environmental footprint. Vertical integration is crucial for ensuring alignment between strategic and tactical decision making in supply chain management. This article presents a multi-objective mathematical model that integrates both economic and environmental considerations within the perishable food supply chain, aiming to determine optimal solutions for conflicting objectives. Methods: In this research, we employed combining goal programming with the epsilon constraint approach; this comprehensive methodology reveals optimal solutions by discretizing the values derived from the payoff table. Results: The model is applied to a real case study of the tomato paste supply chain in Ethiopia. To identify Pareto-efficient points, the results are presented in two scenarios: Case I and Case II. Conclusions: The findings emphasize the significant influence of the geographical location of manufacturing centers in supplier selection, which helps optimize the trade-off between environmental impact and total cost. The proposed solution provides decision makers with an effective strategy to optimize both total cost and eco-costs in the design of perishable food supply chain networks. Full article
(This article belongs to the Section Sustainable Supply Chains and Logistics)
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19 pages, 3327 KiB  
Article
YOLOv8m for Automated Pepper Variety Identification: Improving Accuracy with Data Augmentation
by Madalena de Oliveira Barbosa, Fernanda Pereira Leite Aguiar, Suely dos Santos Sousa, Luana dos Santos Cordeiro, Irenilza de Alencar Nääs and Marcelo Tsuguio Okano
Appl. Sci. 2025, 15(13), 7024; https://doi.org/10.3390/app15137024 - 22 Jun 2025
Viewed by 727
Abstract
This research addresses the critical need for an efficient and precise identification of Capsicum spp. fruit varieties within the post-harvest contexts to enhance quality control and ensure consumer satisfaction. Employing the YOLOv8m convolutional neural network, the study identified eight distinct pepper varieties: Pimento, [...] Read more.
This research addresses the critical need for an efficient and precise identification of Capsicum spp. fruit varieties within the post-harvest contexts to enhance quality control and ensure consumer satisfaction. Employing the YOLOv8m convolutional neural network, the study identified eight distinct pepper varieties: Pimento, Bode, Cambuci, Chilli, Fidalga, Habanero, Jalapeno, and Scotch Bonnet. A dataset comprising 1476 annotated images was utilized and significantly expanded through data augmentation techniques, including rotation, flipping, and contrast adjustments. Comparative analysis reveals that training with the augmented dataset yielded significant improvements across key performance indicators, particularly in box precision, recall, and mean average precision (mAP50 and mAP95), underscoring the effectiveness of data augmentation. These findings underscore the considerable potential of CNNs to advance the AgriFood sector through increased automation and efficiency. While acknowledging the constraints of a controlled image dataset, subsequent research should prioritize expanding the dataset and conducting real-world testing to confirm the model’s robustness across various environmental factors. This study contributes to the field by illustrating the application of deep learning methodologies to enhance agricultural productivity and inform decision-making. Full article
(This article belongs to the Special Issue Advances in Automation and Controls of Agri-Food Systems)
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24 pages, 8251 KiB  
Article
Strengthening of the Rural Community and Corn Food Chain Through the Application of the WWP Model and the Integration of CFS-RAI Principles in Puebla, México
by José Regalado-López, José Antonio Maimone-Celorio and Nicolás Pérez-Ramírez
Sustainability 2025, 17(12), 5442; https://doi.org/10.3390/su17125442 - 13 Jun 2025
Viewed by 1140
Abstract
Strengthening producer groups, the rural community, and agri-food chains are important actions to help solve the problem of food poverty, improve the living conditions of producers and promote sustainable development in rural México. It is necessary to seek new ways to improve decision-making [...] Read more.
Strengthening producer groups, the rural community, and agri-food chains are important actions to help solve the problem of food poverty, improve the living conditions of producers and promote sustainable development in rural México. It is necessary to seek new ways to improve decision-making by producer groups and establish some principles to strengthen the different links in agri-food chains. The objective of this study was to analyze the integration of the Principles for Responsible Investment in Agriculture (PRIA) in the corn agri-food chain in order to assess its strengthening. A study was carried out in three cases based on the application of the “Working With People” (WWP) model as well as interviews with key actors. It was found that cooperating groups with a higher degree of application of the WWP model and PRIAs have a higher degree of stability and sustainable development and strengthen the integration and cooperation of local action groups. These groups have the technical component better organize the agri-food processes and better incorporate the PRIAs and improve their economic, social, and environmental development compared to other groups that do it in a traditional way. Full article
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31 pages, 7861 KiB  
Article
Improving Sustainable Viticulture in Developing Countries: A Case Study
by Zandra Betzabe Rivera Chavez, Alessia Porcaro, Marco Claudio De Simone and Domenico Guida
Sustainability 2025, 17(12), 5338; https://doi.org/10.3390/su17125338 - 9 Jun 2025
Viewed by 776
Abstract
This paper presents the identification of the functional requirements and development of a preliminary concept of the AgriRover, a low-cost, modular autonomous vehicle intended to support sustainable practices in traditional vineyards in developing countries, focusing on the Ica region of Peru. Viticulture in [...] Read more.
This paper presents the identification of the functional requirements and development of a preliminary concept of the AgriRover, a low-cost, modular autonomous vehicle intended to support sustainable practices in traditional vineyards in developing countries, focusing on the Ica region of Peru. Viticulture in this region faces acute challenges such as soil salinity, climate variability, labour shortages, and low technological readiness. Rather than offering a ready-made technological integration, this study adopts a step-by-step design approach grounded in the realities of smallholder farmers. The authors mapped the phenological stages of grapevines using the BBCH scale and systematically reviewed available sensing and monitoring technologies to determine the most context-appropriate solutions. Virtual modelling and preliminary analysis validate AgriRover’s geometric configuration and path-following capabilities within narrow vineyard rows. The proposed platform is meant to be adaptable, scalable, and maintainable using locally available material and human resources. AgriRover offers a practical and affordable foundation for precision agriculture in resource-constrained settings by aligning viticultural challenges with sensor deployment strategies and sustainability criteria. The sustainability analysis of the initial AgriRover concept was evaluated using the CML methodology, accounting for local waste processing rates and energy mixes to reflect environmental realities in Peru. Full article
(This article belongs to the Section Sustainable Agriculture)
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19 pages, 1842 KiB  
Article
A.A.A. Good Wines WANTED: Blockchain, Non-Destructive Ultrasonic Techniques and Soil Health Assessment for Wine Traceability
by Diego Romano Perinelli, Martina Coletta, Beatrice Sabbatini, Aldo D’Alessandro, Fabio Fabiani, Andrea Passacantando, Giulia Bonacucina and Antonietta La Terza
Sensors 2025, 25(11), 3567; https://doi.org/10.3390/s25113567 - 5 Jun 2025
Viewed by 500
Abstract
The wine industry faces increasing challenges related to authenticity, safety, and sustainability due to recurrent fraud, shifting consumer preferences, and environmental concerns. In this study, as part of the B.I.O.C.E.R.T.O project, we integrated blockchain technology with ultrasonic spectroscopy and soil quality data by [...] Read more.
The wine industry faces increasing challenges related to authenticity, safety, and sustainability due to recurrent fraud, shifting consumer preferences, and environmental concerns. In this study, as part of the B.I.O.C.E.R.T.O project, we integrated blockchain technology with ultrasonic spectroscopy and soil quality data by using the arthropod-based Soil Biological Quality Index (QBS-ar) to enhance traceability, ensure wine quality, and certify sustainable vineyard practices. Four representative wines from the Marche region (Sangiovese, Maceratino, and two Verdicchio PDO varieties) were analyzed across two vintages (2021 and 2022). Ultrasound spectroscopy demonstrated high sensitivity in distinguishing wines based on ethanol and sugar content, comparably to conventional viscosity-based methods. The QBS-ar index was applied to investigate the soil biodiversity status according to the agricultural management practices applied in each vineyard, reinforcing consumer confidence in environmentally responsible viticulture. By recording these data on a public blockchain, we developed a secure, transparent, and immutable certification system to verify the geographical origin of wines along with their unique characteristics. This is the first study to integrate advanced analytical techniques with blockchain technology for wine traceability, simultaneously addressing counterfeiting, consumer demand for transparency, and biodiversity preservation. Our findings support the applicability of this model to other agri-food sectors, with potential for expansion through additional analytical techniques, such as isotopic analysis and further agroecosystem sustainability indicators. Full article
(This article belongs to the Section Chemical Sensors)
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16 pages, 1236 KiB  
Article
Life Cycle Sustainability Assessment of Agriproducts in Latin America: Overview Based on Latent Dirichlet Allocation
by Lenin J. Ramírez-Cando, Yuliana I. Mora-Ochoa, Adriana S. Freire-Sanchez and Bryan X. Medina-Rodriguez
Sustainability 2025, 17(11), 4954; https://doi.org/10.3390/su17114954 - 28 May 2025
Viewed by 476
Abstract
This study explores the use of Life Cycle Assessments (LCAs), Total Sustainability Assessment, and Life Cycle Sustainability Assessment (LCSA) as tools to evaluate the environmental, social, and economic impacts in Agri-industry. It highlights the unique trajectory of LCA and LCSA implementation in Latin [...] Read more.
This study explores the use of Life Cycle Assessments (LCAs), Total Sustainability Assessment, and Life Cycle Sustainability Assessment (LCSA) as tools to evaluate the environmental, social, and economic impacts in Agri-industry. It highlights the unique trajectory of LCA and LCSA implementation in Latin America, shaped by the region’s distinct environmental, social, and economic contexts, contrasted with global research trends. Evidence shows the importance of biodiversity, conservation, and deforestation mitigation in Latin American LCA applications, which differ from the urban-focused impacts seen in regions like Europe or North America. Furthermore, it emphasizes the significant role of LCSA in addressing socio-economic challenges unique to Latin America, such as inequality and labor conditions. The research reveals the benefits of LCA and LCSA methodologies in the agro-industrial sector, particularly in addressing social issues like land use rights and rural community welfare. Despite challenges such as limited access to high-quality data and the need for capacity building, the innovative application of these methodologies in Latin America offers valuable insights for the global community. Our work relies on Latent Dirichlet Allocation (LDA) to analyze the LCSA literature from 1990 to 2024, identifying evolving trends and research focal areas in sustainability. The analysis herein presented highlights the need for a multi-dimensional and holistic approach to sustainability research and practice. Our findings also emphasize the importance of developing comprehensive models and integrated methodologies to effectively address complex sustainability challenges. Environmental information remains crucial for policy processes, acknowledging uncertainties in estimations and the connection between land use change, agriculture, and emissions from the global food economy and bioenergy sectors. The research underscores the dynamic nature of LCSA and the importance of continually reassessing sustainability efforts to address pressing challenges. Full article
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31 pages, 2749 KiB  
Article
Optimizing Resilient Sustainable Citrus Supply Chain Design
by Sherin Bishara, Nermine Harraz, Hamdy Elwany and Hadi Fors
Logistics 2025, 9(2), 66; https://doi.org/10.3390/logistics9020066 - 27 May 2025
Viewed by 798
Abstract
Background: Growing environmental concerns and the vulnerability of global supply chains to disruptions, such as pandemics, natural disasters, and logistical failures, necessitate the design of sustainable and resilient supply chains. Methods: A novel multi-period mixed-integer linear programming model is developed with the objective [...] Read more.
Background: Growing environmental concerns and the vulnerability of global supply chains to disruptions, such as pandemics, natural disasters, and logistical failures, necessitate the design of sustainable and resilient supply chains. Methods: A novel multi-period mixed-integer linear programming model is developed with the objective of maximizing supply chain profit to design a complete citrus supply chain, which incorporates the production of citrus fruit and juice, and accommodates resilience and sustainability perspectives. Results: A comprehensive citrus supply chain scenario is presented to support the applicability of the proposed model, leveraging real data from citrus supply chain stakeholders in Egypt. Moreover, an actual case study involving a citrus processing company in Egypt is demonstrated. Gurobi software is used to solve the developed model. To build a resilient supply chain which can cope with different disruptions, different scenarios are modeled and strategies for having multiple suppliers, backup capacity, and alternative logistics routes are evaluated. Conclusions: The findings underscore the critical role of resilience in supply chain management, particularly in the agri-food sector. Moreover, the proposed model not only maximizes supply chain profitability but also equips stakeholders with the tools necessary to navigate challenges effectively. Full article
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28 pages, 1216 KiB  
Article
Mathematical Model to Improve Energy Efficiency in Hammer Mills and Its Use in the Feed Industry: Analysis and Validation in a Case Study in Cuba
by Yoisdel Castillo Alvarez, Reinier Jiménez Borges, José Pedro Monteagudo Yanes, Berlan Rodríguez Pérez, Carlos Diego Patiño Vidal and Roberto Pfuyo Muñoz
Processes 2025, 13(5), 1523; https://doi.org/10.3390/pr13051523 - 15 May 2025
Viewed by 1066
Abstract
The feed industry is characterized by high energy consumption during the grinding stage, where hammer mills can account for up to 50% of total electricity usage; furthermore, efficiency analyses are based only on the classical equations reported in the literature. In this context, [...] Read more.
The feed industry is characterized by high energy consumption during the grinding stage, where hammer mills can account for up to 50% of total electricity usage; furthermore, efficiency analyses are based only on the classical equations reported in the literature. In this context, the present theoretical-applied research aimed to improve the efficiency of a plant operating below its nominal capacity. To achieve this, a comprehensive mathematical model was developed, integrating power and grain disintegration equations while overcoming the limitations of classical comminution theories. The model incorporates key factors such as feed rate, moisture content, absorbed power and hammer wear. Additionally, specific correction factors for temperature (Kt) and mechanical degradation (Kd) were introduced to accurately represent real operating conditions. The study was based on extensive measurements of electrical current, power factor, energy consumption, particle size distribution and thermal variations under different load conditions. The statistical analysis, which included ANOVA, ANCOVA and multiple regressions, demonstrated a predictive accuracy of 98% (R2) and a pseudo-R2 of 89%. This high correlation allowed for an 18% reduction in energy consumption equivalent to 4 kWh/t and up to a 30% improvement in particle size uniformity, surpassing typical factory performance. The findings highlight that integrating operational, thermodynamic and wear-related factors enhances the robustness of the model, promoting more reliable energy-management practices in hammer mills. Consequently, the results confirm that the developed model serves as a scientifically robust, efficient and applicable tool for improving energy efficiency and reducing environmental impacts in the agri-food industry. Full article
(This article belongs to the Special Issue Research and Optimization of Food Processing Technology)
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28 pages, 1335 KiB  
Article
Exploring Determinants of and Barriers to Climate-Smart Agricultural Technologies Adoption in Chinese Cooperatives: A Hybrid Study
by Xiaoxue Feng, Jun Chen, Zebing Mao, Yanhong Peng and Suhaiza Zailani
Agriculture 2025, 15(9), 1005; https://doi.org/10.3390/agriculture15091005 - 6 May 2025
Viewed by 688
Abstract
The loss of agricultural production due to climate change and natural disasters has attracted widespread attention. Climate-smart agricultural technologies (CSATs) are attracting attention as a solution to address climate change while achieving sustainable agricultural development. However, in the Chinese context, research on cooperatives’ [...] Read more.
The loss of agricultural production due to climate change and natural disasters has attracted widespread attention. Climate-smart agricultural technologies (CSATs) are attracting attention as a solution to address climate change while achieving sustainable agricultural development. However, in the Chinese context, research on cooperatives’ intention to adopt such technologies is relatively limited. This study investigated the factors influencing the behavioral intentions of Chinese farmers’ cooperatives to adopt CSATs using a behavioral reasoning theory (BRT) framework. A structured questionnaire was administered to 308 participants using purposive sampling techniques. For data analysis, an artificial neural network (ANN) and fuzzy set qualitative comparative analysis (fsQCA) complemented the disjointed two-stage partial least squares structural equation modeling (PLS-SEM) approach to ensure the robustness of the results and provide important practical insights. The results suggest that values (perceived value of government environmental concern, value of openness to change) shape the determinants of and barriers to CSAT adoption by cooperatives, but do not have a direct impact on behavioral intentions. The “determinants” all positively influenced adoption behavioral intentions, with “agricultural extension and advisory service” having the greatest impact on behavioral intentions, followed by “opinion leaders’ recommendation” and “policy support”. Among the “barriers”, only “perceived risk” and behavioral intention were negatively correlated. Behavioral intention to adopt CSATs by cooperatives has a positive effect on willingness to pay, which motivated cooperatives to pay more to acquire the technology. Based on the findings, this study provides theoretical insights for researchers and policy implications for governments, agricultural organizations, policymakers, and agri-technology companies. Full article
(This article belongs to the Section Agricultural Economics, Policies and Rural Management)
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19 pages, 696 KiB  
Article
From Attachment to Action: Consumer Identification and the Sustainable Buying of Rural Brand Products Like “Pită de Pecica”
by Anca Mihaela Dicu, Dana Rad, Florentina Barbu, Lavinia Denisia Cuc, Andrea Feher, Daniela Roman, Luminița Mazuru, Grigorie Sanda and Luminița Pîrvulescu
Sustainability 2025, 17(9), 4133; https://doi.org/10.3390/su17094133 - 2 May 2025
Viewed by 1209
Abstract
The current research examines the psychological and perceptual predictors of sustainable consumption behavior in a rural Romanian context, with specific reference to the traditional product Pită de Pecica. A sample of 485 consumers (n = 485) who were familiar with Pită de Pecica [...] Read more.
The current research examines the psychological and perceptual predictors of sustainable consumption behavior in a rural Romanian context, with specific reference to the traditional product Pită de Pecica. A sample of 485 consumers (n = 485) who were familiar with Pită de Pecica completed validated instruments measuring brand identification and brand attributes perceived. An exploratory factor analysis (EFA) was applied to find two dimensions on each scale—brand-based self-definition (α = 0.92) and emotional brand attachment (α = 0.86); and sensory-affective brand association (α = 0.87) and product functional-symbolic value (α = 0.84). Emotional brand attachment (EBA) refers to the emotional bond a consumer forms with a brand; sensory-affective brand association (SABA) captures affective and sensory connections; and decision tree regression is a machine learning technique that identifies non-linear predictors. In this study, sustainability is operationalized across cultural, economic, and environmental dimensions, reflecting both traditional product preservation and support for regional food systems. A decision tree regression model was then applied to predict the frequency of sustainable consumption behavior. Emotional brand attachment was the strongest predictor (relative importance = 26.13%), sensory-affective brand association was second most important (16.91%) and brand-based self-definition was third (13.99%). Demographic variables (e.g., income, age) were weak predictors. The model explained 43% of the behavior variance (R2 = 0.43) despite considerable behavioral unpredictability (MAPE = 236.85%). Findings show that emotional and identity-driven brand connections are central to leveraging sustainable consumption in rural contexts, which has important implications for future branding initiatives, agri-food policies, and local economic revitalization initiatives that promote sustainable development. Findings support adopting cultural, psychological, and economic dimensions of sustainable development across development paradigms. Full article
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21 pages, 4404 KiB  
Article
Potential of Baled Silage to Preserve White Grape Pomace for Ruminant Feeding
by Marina Galvez-Lopez, Alfonso Navarro, Raquel Muelas, Amparo Roca, Cristofol Peris, Gema Romero and José Ramón Díaz
Agriculture 2025, 15(9), 974; https://doi.org/10.3390/agriculture15090974 - 30 Apr 2025
Cited by 1 | Viewed by 711
Abstract
The use of agro-industrial by-products in animal feed represents a useful alternative to enhance the sustainability of the agri-food chain. Grape pomace represents an environmental problem mainly for wine-producing countries. Because of the high water content and the seasonality of this feedstuff, ensiling [...] Read more.
The use of agro-industrial by-products in animal feed represents a useful alternative to enhance the sustainability of the agri-food chain. Grape pomace represents an environmental problem mainly for wine-producing countries. Because of the high water content and the seasonality of this feedstuff, ensiling might be a technology to preserve its nutritional quality for a long time, and this must be considered and studied on a commercial scale. This study aimed to characterise the ensiling process of white grape pomace, evaluate its suitability for inclusion in the ruminant diet and compare its shelf life to untreated storage conditions. White grape pomace silos were made with baled silage (300 kg approx.). Samples were analysed at days 0, 7, 14, 35, 60 and 180 of conservation to determine microbial populations, fermentation metabolites, nutritional components and bioactive properties. The collected data were analysed using a general linear model, considering the effect of the treatment, sampling days and their interaction (Proc. GLM, SAS v9.4). White grape pomace showed good suitability for ensiling, and stabilisation was achieved on day 35. The microbial populations and fermentative components observed in silage treatments adhered to the expected standards for high-quality ensiling processes. There were no significant losses of dry matter, and no significant differences were observed in the nutritional composition for ruminant feeding. A small reduction in antioxidant potential was observed and considered irrelevant in terms of the bioactive properties of the silages. Additionally, the cost analysis demonstrated that white grape pomace silage could serve as a more economical feedstuff compared to conventional forages, considering its nutritional value. So, the ensiling of white grape pomace in baled silage is a suitable and cost-effective technique that allows its preservation over a long period. Full article
(This article belongs to the Section Farm Animal Production)
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17 pages, 1854 KiB  
Article
The Evaluation of Corporate Sustainability Strategies in Italy: Challenges and Opportunity of Recycled Packaging
by Fabrizio D’Ascenzo, Giuliana Vinci, Giulia Cancer, Marco Ruggeri and Marco Savastano
Sustainability 2025, 17(8), 3608; https://doi.org/10.3390/su17083608 - 16 Apr 2025
Viewed by 795
Abstract
The scientific literature and practice have demonstrated that the old linear economic model “extract—produce—use and throw away” is no longer sustainable due to the enormous accumulation of waste and the related production of CO2. Consequently, there is a need to adopt [...] Read more.
The scientific literature and practice have demonstrated that the old linear economic model “extract—produce—use and throw away” is no longer sustainable due to the enormous accumulation of waste and the related production of CO2. Consequently, there is a need to adopt more sustainable development systems that include recycling resources and producing goods derived from recycled material. The examined literature highlights that SMEs are the least likely to make technological or paradigm changes in favor of sustainable choices due to a lack of resources and managerial competencies. This study presents a mixed-method approach based on qualitative and quantitative analyses. The qualitative analysis aims to identify, in the Italian context, measures that encourage companies to reduce the use of plastics in favor of sustainable alternatives. The quantitative analysis, based on secondary data, aims to identify the characteristics of the firms that benefited from the aid identified in the previous analysis. Thus, this study may support corporate environmental sustainability strategies in Italy by identifying specific characteristics and profiles of those companies willing to obtain public incentives for the use of recycled materials in their business and production processes. The results show that small and micro-sized companies obtained most of the analyzed incentives (almost 76% in terms of number of applications), and the most affected areas by these measures are the agriculture and food industries. Therefore, economic incentives can improve sustainable performance for small and micro-sized enterprises in the wide agri-food sector, while the legislator must adopt different tools, such as bans, Extended Producer Responsibility (EPR), and sustainability reports for medium-large sized companies of other crucial industrial sectors such as construction and automotives. Full article
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26 pages, 1491 KiB  
Review
The Economic and Technological Challenges of the Agri-Development Implementation Model in the Case of the Wielkopolska Region in Poland
by Leszek Wanat, Jan Sikora, Leszek Majchrzak, Łukasz Sarniak, Rafał Czarnecki, Karolina Smętkiewicz and Mateusz Ornoch
Agriculture 2025, 15(4), 412; https://doi.org/10.3390/agriculture15040412 - 15 Feb 2025
Cited by 1 | Viewed by 1487
Abstract
This study discusses key issues relating to the agri-development perspective, which is based on the “numbered” agriculture model. Selected economic and technological dilemmas related to agribusiness development in the Wielkopolska region of Poland were reviewed. Based not only on a literature review, but [...] Read more.
This study discusses key issues relating to the agri-development perspective, which is based on the “numbered” agriculture model. Selected economic and technological dilemmas related to agribusiness development in the Wielkopolska region of Poland were reviewed. Based not only on a literature review, but also on our own research, we identified the current challenges for farmers in terms of innovation, green energy, and environmental ideas. Using the diagnostic survey method, with agricultural practitioners as experts, the potential directions of regional agricultural development were assessed from the perspective of programming the next stages of the “agricultural revolution”. Individual in-depth interviews were conducted with purposely invited farmers from Wielkopolska, one of the most agriculturally developed regions of Poland. By verifying the ex post assessment of the key pillars of the Agriculture “3.0” and “4.0” concepts’ adaptation model, as carried out on the respondents’ farms, the optimal model for farm operation was sought. The study assumed the implementation of the next stages of agribusiness development had taken place and that implementation of the “Agriculture 5.0” model, under the conditions evaluated, was possible. The so-defined hypothesis was only partially confirmed (conditionally). The identified potential provides a development path for the optimal idea of “Agriculture N.0”, with the value of “N” not yet known. Finally, key conclusions and recommendations relating to Wielkopolska’s agribusiness were formulated. Full article
(This article belongs to the Section Agricultural Economics, Policies and Rural Management)
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