Search Results (234)

Mangoes are an important part of Hainan’s tropical characteristic agriculture. In response to the requirements of building an ecological civilization pilot demonstration zone in Hainan, China, green and sustainable development will be the future development trend of the mango planting system. However, the economic benefits and environmental impact during its planting and management process remain unclear. This paper combines emergy, life cycle assessment (LCA), and economic analysis to compare the system sustainability, environmental impact, and economic benefits of the traditional mango cultivation system (TM) in Dongfang City, Hainan Province, and the early-maturing mango cultivation system (EM) in Sanya City. The emergy evaluation results show that the total emergy input of EM (1.37 × 10¹⁶ sej ha⁻¹) was higher than that of TM (1.32 × 10¹⁶ sej ha⁻¹). From the perspective of the emergy index, compared with TM, EM exerted less pressure on the local environment and has better stability and sustainability. This was due to the higher input of renewable resources in EM. The LCA results showed that based on mass as the functional unit, the potential environmental impact of the EM is relatively high, and its total environmental impact index was 18.67–33.19% higher than that of the TM. Fertilizer input and On-Farm emissions were the main factors causing environmental consequences. Choosing alternative fertilizers that have a smaller impact on the environment may effectively reduce the environmental impact of the system. The economic analysis results showed that due to the higher selling price of early-maturing mango, the total profit and cost–benefit ratio of the EM have increased by 55.84% and 36.87%, respectively, compared with the TM. These results indicated that EM in Sanya City can enhance environmental sustainability and boost producers’ annual income, but attention should be paid to the negative environmental impact of excessive fertilizer input. These findings offer insights into optimizing agricultural inputs for Hainan mango production to mitigate multiple environmental impacts while enhancing economic benefits, aiming to provide theoretical support for promoting the sustainable development of the Hainan mango industry. Full article

Global policy narratives on livestock development increasingly emphasize environmental concerns, often overlooking the social dimensions of the sector. In the case of dairy, the world’s most valuable agricultural commodity, its role in social and economic development remains poorly quantified. Our study contributes to a more balanced vision of the UN SDGs thanks to the inclusion of a socio-economic dimension. Here we present a novel empirical approach to assess the socio-economic impacts of dairy development using a new global dataset and non-parametric modelling techniques (local polynomial regressions), with yield as a proxy for sectoral performance. We find that as dairy systems intensify, the number of farm households engaged in production declines, yet household incomes rise. On-farm labour productivity also increases, accompanied by a reduction in employment but higher wages. In dairy processing, employment initially grows, peaks, and then contracts, again with rising wages. The most substantial impact is observed among consumers: an increased milk supply leads to lower prices and improved affordability, expanding the access to dairy products. Additionally, dairy development is associated with greater agricultural value added, an expanding tax base, and the increased formalization of the economy. These findings suggest that dairy development, beyond its environmental footprint, plays a significant and largely positive role in social transformation, yet is having to adapt sustainably while tackling labour force relocation, and that dairy development’s social impacts mimic the general agricultural sector. These results might be of interest for the assessment of policies regarding dairy development. Full article

Designing sustainable farming systems in mountainous regions is particularly challenging because of complex economic, social, and environmental factors. Production models prioritizing sustainability and environmental protection require integrated assessment methodologies that can address multiple criteria and incorporate diverse stakeholders’ perspectives while ensuring accuracy and applicability. Life cycle assessment (LCA) and multi-actor multi-criteria analysis (MAMCA) are two complementary approaches that support “eco-design” strategies aimed at identifying the most sustainable options, including on-farm transformation processes. This study presents an integrated application of LCA and MAMCA to four supply chains: rye bread, barley beer, cow cheese, and goat cheese. The results show that cereal-based systems have lower environmental impacts than livestock systems do, although beer’s required packaging significantly increases its footprint. The rye bread chain emerged as the most sustainable and widely preferred option, except under high-climatic risk scenarios. In contrast, livestock-based systems were generally less favorable because of greater impacts and risks but gained preference when production security became a priority. Both approaches underline the need for a deep understanding of production performance. Future assessments in mountain contexts should integrate logistical aspects and cooperative models to enhance the resilience and sustainability of short food supply chains. Full article

The petiole nitrate–nitrogen concentration (PNNC) has been an industry standard indicator for in-season potato (Solanum tuberosum L.) nitrogen (N) status diagnosis. Leaf sensors can be used to predict the PNNC and other N status indicators non-destructively. The SPAD meter is a common leaf chlorophyll (Chl) meter, while the Dualex is a newer leaf fluorescence sensor. Limited research has been conducted to compare the two leaf sensors for potato N status assessment. Therefore, the objectives of this study were to (1) compare SPAD and Dualex for predicting potato N status indicators, and (2) evaluate the potential prediction improvement using multi-source data fusion. The plot-scale experiments were conducted in Becker, Minnesota, USA, in 2018, 2019, 2021, and 2023, involving different cultivars, N treatments, and irrigation rates. The results indicated that Dualex’s N balance index (NBI; Chl/Flav) always outperformed Dualex Chl but did not consistently perform better than the SPAD meter. All N status indicators were predicted with significantly higher accuracy with multi-source data fusion using machine learning models. A practical strategy was developed using a linear support vector regression model with SPAD, cultivar information, accumulated growing degree days, accumulated total moisture, and an as-applied N rate to predict the vine or whole-plant N nutrition index (NNI), achieving an R² of 0.80–0.82, accuracy of 0.75–0.77, and Kappa statistic of 0.57–0.58 (near-substantial). Further research is needed to develop an easy-to-use application and corresponding in-season N recommendation strategy to facilitate practical on-farm applications. Full article

Foot-and-mouth disease (FMD) significantly impacts global livestock industries, with raw milk transportation posing a recognized pathway for viral dissemination, particularly in endemic regions. This study aimed to evaluate the risk of FMD virus (FMDV) introduction and transmission to dairy farms via raw milk transportation in Ban Thi District, Thailand. A qualitative risk assessment methodology, adhering to WOAH guidelines, was employed. Data were collected through structured farmer surveys (n = 109), expert interviews (n = 12), and reviews of national disease surveillance data and scientific literature. The risk assessment, utilizing a scenario tree approach for domestic dairy cattle, revealed a moderate overall risk of FMDV transmission. This finding is primarily attributed to critical gaps in on-farm biosecurity practices, potential contamination at milk collection centers, and significant challenges in detecting subclinical carrier animals. While the qualitative approach presented inherent limitations and uncertainties, the study successfully highlighted key vulnerabilities. The results underscore the urgent necessity for implementing targeted biosecurity protocols, developing more robust surveillance strategies for FMDV carriers, and establishing standardized risk assessment frameworks to mitigate potential outbreaks and protect the regional dairy industry. Full article

Hoof disorders in small ruminants pose significant challenges to animal welfare and farm productivity. This study presents the first attempt to determine the prevalence of lameness and hoof disorders and their associated risk factors in goat and sheep farms in Selangor, Malaysia. Locomotion scores were collected from 226 animals (126 sheep and 100 goats) across 10 farms. A hoof examination was conducted, and hoof lesions were identified through detailed photographic evaluation. On-farm assessments and interviews were conducted to gather information on management practices from the farms. Data were analysed using descriptive statistics, bivariate analysis, and logistic regression models. The prevalence of lameness was 42.8% (95% CI 34.2 to 51.9) in sheep and 23.0% (95% CI 16.3–38.4) in goats. Significant variation (p > 0.05) in lameness prevalence was observed across farms, ranging from 26.7% to 61.5% in sheep and 7.7% to 30.8% in goat farms. The majority of lameness and hoof lesions were observed in the hindlimbs of both species. The prevalence of hoof disorders was 91.3% (95% CI 84.6–95.4) in sheep and 43.0% in goats (95% CI 21.4–58.0). The predominant hoof disorders were overgrown wall horn, white line disease, sole bruise, and wall fissures. No hoof affections of infectious origin were observed in the sampled animals. Risk factors for lameness and hoof lesions in sheep included pregnancy, semi-intensive management, and breeds other than Damara. Higher odds of lameness were observed in exotic goat breeds and those with overgrown wall horns. In conclusion, this study revealed a high prevalence of lameness and hoof disorders in goat and sheep farms, highlighting the need to address these important welfare and economic issues. While the identified risk factors could be considered for the management of hoof disorders in small ruminant farms, a larger sample size that is representative of the sheep and goat population is recommended for more generalizable results. Full article

This study presents a mobile-based sperm analysis system featuring a user-friendly, droplet-loaded microfluidic chip that enables non-specialist users to perform the rapid and accurate quantitative evaluation of boar semen directly on the farm. The iSperm system integrates a tablet, optical module, heater, and real-time image analysis app to deliver automated measurements of sperm concentration, motility, and progressive motility in under one minute. Precision and user variability tests demonstrated high concordance with CASA and the hemocytometer, with minimal differences between trained and untrained users. A method comparison using 77 farm-collected samples confirmed agreement through Passing–Bablok regression and Bland–Altman analysis. ROC curve analyses further validated diagnostic accuracy for all parameters, with AUC values exceeding 0.95. The iSperm platform offers a reliable, user-friendly, and field-deployable solution for on-site semen quality assessment, improving decision-making in swine artificial insemination. Full article

Despite growing interest in improving soil health on cocoa farms, applied research on the impacts of specific amendments on soil and plant outcomes is lacking. An integrated assessment of the impacts of two different organic amendments (compost and vermicompost) and a microbial biofertilizer on soil physical, chemical, and biological properties, as well as cocoa flowering, fruit set, and yield, was conducted in Guayaquil, Ecuador. Complementary culture-dependent and culture-independent methods were used to assess the impacts of amendments on microbial diversity, community composition, and specific taxa. Compost or vermicompost application affected soil chemical properties, including potassium, phosphorus, and sodium, and had small but significant effects on fungal beta diversity. Biofertilizer application slightly lowered soil pH and altered the total abundance of specific taxonomic groups including Azotobacter sp. and Trichoderma sp., with borderline significant effects on Azospirillum sp., Lactobacillus sp., Pseudomonas sp., calcium-solubilizing bacteria, and phosphorus-solubilizing bacteria. Amplicon sequencing (16S, ITS) identified 15 prokaryotic and 68 fungal taxa whose relative abundance was influenced by organic amendments or biofertilizer. Biofertilizer application increased cherelle formation by 19% and monthly harvestable pod counts by 11% despite no impact on flowering index or annual pod totals. This study highlights the tangible potential of microbiome optimization to simultaneously improve on-farm yield and achieve soil health goals on cocoa farms. Full article

Among physiological parameters, total locomotor activity (TLA) and heart rate (HR) are used as physiological indicators in animal welfare evaluations. The present study aimed to simultaneously record for 24 h the TLA and HR of ten clinically healthy horses housed in conventional individual boxes subjected to a natural photoperiod and temperature. An actigraphy-based data logger was placed on the headstall, and an equine HR monitor was placed around the chest to monitor TLA and HR, respectively. Activity was monitored with 5 min sampling intervals and HR with 5 s intervals. To make the data points uniform, the means of 5 min intervals were calculated. Both investigated parameters showed a daily rhythmicity with a diurnal acrophase (locomotor activity 17:05 ± 1:15 arbitrary unit; heart rate 16.40 ± 0.30 beats/min). Robustness of the rhythm was 17.95 ± 10.53% and 37.05 ± 0.63% for the TLA and HR. A positive correlation was observed between the two investigated parameters in each horse, r = 0.48 ± 0.07, p < 0.0001. Change in TLA is a good index for success of management. Its positive correlation with daily HR monitoring confirms the use of these two physiological parameters for an objective on-farm welfare assessment. The application of new technologies for the simultaneous recording of physiological indexes of animals’ welfare can be a useful instrument. Full article

Vegetable production primarily relies on the conventional tillage system (CTS), which leads to soil degradation through erosion and reduced soil health. The use of no-tillage vegetable systems (NTVS) aims to mitigate these issues; however, information about the impact of this management system on soil health and greenhouse gas (GHG) emissions remains limited. Thus, the objective of this study was to conduct an on-farm evaluation of the effects of no-tillage and cover crop use on soil C and N contents and stocks, soil bulk density (SD), mean geometric diameter (MGD) of aggregates, soil temperature, volumetric soil moisture (VM), plant yield, and GHG emissions in cauliflower production under NTVS compared to CTS in a subtropical ecosystem in southeastern Brazil. Chemical and physical properties were assessed at depths of 0–5, 5–10, and 10–30 cm. GHG emissions, particularly nitrous oxide (N₂O), carbon dioxide (CO₂), and methane (CH₄) were measured using closed static chambers and gas chromatography. NTVS with cover crop mixes had higher yield than CTS without cover crops (25.1 and 18.4 Mg ha⁻¹, respectively). NTVS exhibited increased MGD and VM and reduced SD. Soil temperature in the 0–5 cm layer was lower in NTVS than in CTS. Soil C and N stocks were higher in NTVS, but high N₂O emissions offset this advantage compared to CTS. Overall, NTVS emitted more CO₂ and N₂O than CTS, while both systems showed soil CH₄ uptake. NTVS maintained sufficient carbon equivalent reserves (0–30 cm) to offset GHG emissions, making it a viable alternative for plant yield and soil quality; however, its environmental impact on GHG emissions requires further attention. Full article

The accurate prediction of body mass (BM) in cattle is crucial for herd monitoring, assessing biological efficiency, and optimizing nutritional management. This study evaluated BM prediction models using morphological data from 465 lactating Holstein cows, including the dorsal length (DL), thoracic width (TW), abdominal width (AW), rump width (RW), hip height (HH), body depth (BD), thoracic perimeter (TP), and abdominal perimeter (AP). Spearman’s correlation analysis identified TP (r = 0.89), AP (r = 0.88), and RW (r = 0.80) as the strongest predictors. Simple and multiple linear regression models, artificial neural networks (ANNs), and Support Vector Regression (SVR) were tested. The dataset was split into 90% for training (419 samples), 5% for validation (23 samples), and 5% for testing (23 samples). The best simple model, using only TP, achieved an R² of 0.7763 and an RMSE of 43.69 kg. A multiple regression model with TP, AP, and RW improved performance (R² = 0.9067, RMSE = 28.00 kg). The ANN outperformed all of the models (R² = 0.9125, RMSE = 25.86 kg), and was followed by SVR (R² = 0.9046, RMSE = 27.41 kg). As an indication of the evaluation of the results obtained, it is observed that, although regression models are effective, the ANNs and SVR provide greater accuracy, reinforcing their potential for herd management. However, simpler models remain viable alternatives for practical on-farm application. Full article

Within the agricultural sector, dairy cattle farming systems are of the main ammonia emitters contributing to nitrogen (N) pollution. As a main strategy to mitigate N pollution, increased N use efficiency (NUE) of dairy cattle farms has been proposed. Dairy replacement heifers are an important aspect of dairy herds, and improving their NUE is a step toward addressing the issue holistically. The aim of the current review was to describe and assess heifer nutritional practices that affect NUE and examine protein supplementation to minimize N excretion in the environment. Heifer management practices related to growth and nutrition appear to have an important role on improving overall farm NUE. In particular, age at first calving, dietary crude protein level and rumen degradable protein level appear to be among the factors that affect N losses during the growth period. From a management point of view, frequent body weight monitoring at growth benchmarks and the use of mechanistic nutritional models are highly desirable to increase NUE under on-farm conditions. Full article

One of the most successful on-farm diversification activities in Italy is the adoption of organic farming: a bona fide entrepreneurial approach to differentiating products for specific economic targets as opposed to merely a survival strategy to avoid decline and abandonment. The main objective of this paper is to assess the positioning of organic farming in periurban areas as defined in Rural Development Programmes (RDPs). Using Italian FADN data and running a logit regression model, we compare urban and periurban farms to other groups of farms identified in the RDP to assess their propensity to switch to organic farming. The assumption is that periurban farmers are more oriented to supplying organic products than farmers in other locations, given their proximity to urban populations who are keen on consuming organic products and are willing to pay a premium price for them. This, in turn, activates other on-farm functions such as the supply of public goods and services. This synergy is also relevant for the design and targeting of specific policies in line with the type of area considered in RDPs. Full article

The common bean (Phaseolus vulgaris L.) arrived in Europe in the sixteenth century from the American continent and spread across the old continent as a result of adaptation to different climatic and geographical conditions, as well as selection for different cultivation techniques and eating habits. This expansion gave rise to a huge number of landraces, which have now been largely replaced by more productive cultivars. To avoid losing this genetic diversity heritage, it is essential to characterize the genetic resources at risk of extinction for correct in situ/ex situ conservation and as a first step toward promoting and relaunching their exploitation. In this article, we report the study of a group of Borlotti beans, both landraces and modern cultivars, which are typically cultivated in Northern Italy. The aim was to explore the variability within the assembled Borlotti panel to assess whether landraces have maintained their morphological and genetic identity over time during on-farm cultivation. In particular, we investigated whether it is possible to distinguish between landraces and commercial accessions, a topic that has so far been understudied, but in the field of conservation, it is particularly important because it allows for the prioritization of preserving genetic resources. We found distinctive traits among the various accessions, with only a few landraces maintaining their identity, many of which should more properly be defined as obsolete cultivars. Taken together, these data indicate that it is possible to establish a priority scale for in/ex situ conservation by comparing landraces and cultivars using morphological and genetic data. Furthermore, thanks to geographical isolation, on-farm conservation has proven to still be successful in maintaining the identity of landraces. Full article

This study investigates grassland-based farming systems within the framework of agroecology (AE), focusing on the identification of relevant indicators for on-farm assessment. The purpose of this research is to test indicator compliance with AE at the farming system level in grassland farms, particularly in High-Nature-Value (HNV) areas. Seventeen farms in France and Italy were selected for this study, and data were collected through semi-structured interviews. These interviews explored various indicators across environmental, economic, and social dimensions. Principal Component Analysis (PCA) was employed to analyze the quantitative indicators, while qualitative data offered insights into farm management and learning practices. The results highlighted the importance of forage self-sufficiency (livestock production dimension) and revenue (economic dimension) as key indicators of successful agroecological management. The study also found that increasing forage self-sufficiency was linked to higher farmer satisfaction, an indicator related to the social dimension. Additionally, qualitative data underscored the significance of self-sufficiency, workload management, and social interaction and continuous learning as critical elements in grassland-based farming. In conclusion, this research proposes self-sufficiency as an indicator that can facilitate the assessment of grassland-based systems, aiding in the broader adoption of agroecological practices in compliance with European policies. Full article