Search Results (110)

Exposure to per- and polyfluoroalkyl substances (PFASs) can cause detrimental health effects. The consumption of contaminated food is viewed as a major exposure pathway for humans, but the relationship between agriculture and PFASs has not been investigated thoroughly, and it is becoming a pressing issue since health advisories are continuously being reassessed. This semi-systematic literature review connects the release, environmental fate, and agriculture uptake of PFASs to enhance comprehension and identify knowledge gaps which limit accurate risk assessment. It focuses on the heavily agricultural state of Minnesota, USA, which is representative of the large Midwestern US Corn Belt in terms of agricultural activities, because PFASs have been monitored in Minnesota since the beginning of the 21st century. PFAS contamination is a complex issue due to the over 14,000 individual PFAS compounds which have unique chemical properties that interact differently with air, water, soil, and biological systems. Moreover, the lack of field studies and monitoring of agricultural sites makes accurate risk assessments challenging. Researchers, policymakers, and farmers must work closely together to reduce the risk of PFAS exposure as the understanding of their potential health effects increases and legacy PFASs are displaced with shorter fluorinated replacements. Full article

There are a multitude of raspberry and blackberry varieties, and each of them develops differently depending on environmental factors and cultivation technology, so much research is needed to see which variety has the best yield in a desired area. This paper studied the growth under natural soil and specific climate conditions in the Bucharest–Ilfov region of Romania of a raspberry plantation and a blackberry plantation, both in their first year of vegetation. The studied interval, the period of June to October 2024, was established from the beginning of the ripening of the first fruits to the late ripening of the fruits. The study analyzed the correlations between the vegetative and productive parameters of the raspberry variety “Delniwa” and the blackberry variety “Thornfree” on productivity per plant. During the study period, good shoot formation was observed, with an average height of 1400 mm for raspberries and 3474 mm for blackberries (r = 0.99 to raspberries and r = 0.98 to blackberries); a good development of the average stem diameter of 8.54 mm for raspberries and 12.78 mm for blackberries (r = 0.96 la zmeur si r = 0.89 la mur), of the number of ripe fruits harvested (r = 0.68 to raspberries and r = 0.58 to blackberries), all of which are correlated with increased productivity of 820 g/plant for raspberries and 2050 g/plant for blackberries. The experimental data were statistically analyzed using linearized, polynomial and hyperbolic models to identify the relationships between the studied variables and to highlight growth variations and fruit production in raspberries and blackberries throughout the season. In the first year of vegetation, both crops recorded constant growth but with different rhythms: raspberries showed constant fruit production, with a peak in June–July and a slight resumption in September, while blackberries had high production at the beginning of summer, followed by a significant decrease in August. The results obtained support farmers who grow raspberries and blackberries under similar natural pedo-climatic conditions, contributing to crop planning and production optimization. Full article

Fusarium head blight (FHB) is a serious fungal disease of wheat and other small cereal grains, significantly reducing grain yield and producing mycotoxins that affect food safety. There is a need for disease detection technologies to determine the right time to apply fungicides, as FHB infection begins before visible symptoms appear. Using multispectral remote sensing by an unmanned aircraft system (UAS), wheat plants were observed under field conditions infested with FHB and simultaneously protected with fungicides sprayed with four different types of nozzles, as well as corresponding control plots infested with FHB only. The results showed that the levels of deoxynivalenol (DON) differed significantly between the five treatments, indicating that the control had the highest DON concentration as no fungicide treatment was applied. This study revealed that the assessment of the normalized difference vegetation index (NDVI) after FHB infection could be useful for predicting DON accumulation in wheat, as a significant negative correlation between DON and NDVI values was measured 24 days after anthesis. The decreasing NDVI values at the end of the growth cycle were expected due to senescence and yellowing of the wheat spikes and leaves. Therefore, significant differences in the NDVI were observed between three measurement points on the 13th, 24th, and 45th day after anthesis. Additionally, the green normalized difference vegetation index (GNDVI) and normalized difference red-edge index (NDRE) were in significant positive correlation with the NDVI at 24th day after anthesis. The use of appropriate measurement points for the vegetation indices can offer the decisive advantage of enabling the evaluation of very large breeding trials or farmers’ fields where the timing of fungicide application is particularly important. Full article

In the United States, small and beginning (SB) farmers depend on institutional and elite customers to increase their farm income, whereas food-insecure communities lack alternatives for accessing and utilizing healthy local foods. This study examined two middle-of-the-chain organizations attempting to break the demand- and supply-related barriers faced by food-insecure consumers and SB farmers, respectively. The study suggests that deep engagement on both sides can facilitate the creation of a viable local food pathway. One organization serves as an aggregator for SB farmers while preventing the unrealistic expectations of institutional customers. A second organization activates food-insecure consumers’ agencies to conceptualize and transform locally sourced food into acceptable forms. It provides the necessary support to ensure the utilization of healthy, nutritious foods. When the two organizations’ missions are aligned, they can use an emergent, flexible, and adaptable approach with a continuous improvement mindset to increase SB farmer livelihoods and reduce food insecurity. Middle-of-the-chain organizations collectively should have more than one way to make local foods available, accessible, and utilizable by food-insecure consumers. A nonprofit social enterprise model of organizations in the middle seems central to the viability of the community-based food system. The system is still in its early stages. Further research is needed to examine its sustained viability. Full article

The adoption of agricultural robots is revolutionizing the agricultural sector, offering innovative solutions to optimize production and reduce environmental impact. This review examines the main functions and applications of agricultural robots, with a focus on the crops handled and the technologies employed. The study analyzes the current state of the art regarding the market trend of agricultural robots used in field and greenhouse operations. Several solutions are emerging, some already implemented and others still in the prototype or project stage. These solutions are beginning to spread, though they may still seem far from widespread field application, particularly given the peculiarities and heterogeneity of the global agricultural landscape. In the face of the many benefits associated with the use of agricultural robots, even today some technical bottlenecks and costs limit their widespread use by farmers. The review provides a fairly comprehensive and up-to-date overview of current trends in agricultural automation, suggesting new areas of research to improve the efficiency and adaptability of robotic systems to different types of crops and environments. Full article

The poor quality of natural pastures in the dry season does not make it possible to meet dairy cows’ requirements for milk production in Burkina Faso and in most West African countries. Therefore, it is urgent to find an alternative by developing a full diet from locally available ingredients. The objective was to determine a diet for dairy cattle based on locally available ingredients in the peri-urban area of Ouagadougou. A progressive methodology was used. Thus, a survey was conducted ontoonton 30 dairy farms. This survey was followed by chemical analysis, for which the most dominant forage and concentrate ingredients were selected. Secondly, the recording of milk and on-farm ingredient use was also carried out using Op-Ration software (Op-Ration version V3.4.5.0) in order to compare and determine the most suitable diets. The data from the survey were subjected to descriptive statistics using SPSS version 20. Those from chemical analysis, milk recording, and ingredient assessment on the farm were subjected to a statistical method using the software Minitab version.18.1.0.0 setup. The results showed two dominant forage species, Sorghum (84.85%) and Pennisetum pedicellatum (90.91%), and two dominant concentrates, corn bran (32%) and cottonseed meal (26%), used by dairy farmers. From these ingredients and simulating the requirements of 400 kgPV^0.75 of lactating cows, a diet assessment was carried out at early, middle, and end lactation. The results showed that at the beginning of lactation, the diet consisted of 6.73 kg of forage and 6.59 kg of concentrate for 13.5 L as the main objective of milk production. The diet for mid-lactation was 8 kg of forage and 6.5 kg of concentrate for 15.5 L per day and 5.7 kg of forage and 3.8 kg of concentrate for the end of lactation. The results of this study show that it is possible to manufacture a complete ration for dairy cows at different stages of lactation from locally available forages and concentrates in the peri-urban area of Ouagadougou. This type of method could be applied to other regions from local forages and concentrates for milk production. Full article

Brazil is one of the main agricultural producers in the world, and its agri-food system has been experiencing concentration and intensification. Since the beginning of the 1990s, the Brazilian government has implemented different interventions to support family agriculture, such as the National Programme for Strengthening Family Farming (PRONAF), the Technical Assistance and Rural Extension Programme (ATER), and different seed distribution programs. Despite the social and economic relevance of these programs, there is a lack of quantitative studies investigating their impact on the resilience of family farms, primarily the promotion of commercialization. We aim to fill this gap by applying propensity score matching techniques to household-level data from the 2014 Brazilian National Household Sample Survey. Only this survey has recorded this type of information to date. We compare the commercialization behavior of policy recipients with that of non-recipients, accounting for interaction effects between different policies. Our results show that PRONAF has had a significant positive impact on family farmers’ propensity to engage in commercialization, and the effect increases if they also have access to technical assistance. Technical assistance alone has a positive effect, while seed distribution appears not to make a significant difference. Our results suggest that an appropriate policy mix can increase the resilience of family farms in emerging countries. Full article

Farmers’ training through experiential learning plays a crucial role in the success of their farming businesses. Aspiring farmers seek crucial skill sets, including financial management, marketing strategies, pricing, budgeting, whole-farm planning, and long-term decision-making. The objective of this study was to assess African American farmers’ attitudes and perceptions towards an urban agriculture certificate program launched to equip them with farming skills to help them become more successful in an urban setting. A mixed-method (qualitative and quantitative) research approach was used to evaluate the impact of this certificate program. Pre- and post-survey questionnaires and interviews were administered to assess farmers’ prior urban farming knowledge and skills and if there were any changes after the certificate program was launched. Eighteen participants (n = 18) who participated and completed the program were surveyed to measure knowledge and skills gained. Results showed that African American farmers participating in the Gary Urban Agriculture Certificate Program significantly (p < 0.03) increased their skill sets and knowledge about farming in comparison to their mean scores from pre- and post-certificate program. When participants were asked to summarize the impact of the course, several mentioned that it helped them develop a comprehensive approach to planning, planting, maintaining, and harvesting the produce of their farms. Narratives from interview discussions also support the survey results in which the majority expressed a positive impact of the certificate in helping them learn about the useful farming resources around them and gain skills in running a farm. Key findings support the concept that the urban agriculture certificate program administered by Purdue University impacted participant knowledge and provided a positive attitude towards farming. This study helped us understand the impact of the certificate program. Results provided greater awareness of creating programs to support the development of Gary urban farmers’ ability to become more knowledgeable and successful in their farming endeavors. Full article

Rice is a water-intensive crop, conventionally grown under submerged conditions, with standing water for about 80% of its growth period. There is an urgent need for water-saving technologies to address challenges associated with conventional irrigation techniques for rice. The alternate wetting and drying (AWD) technique is one of these water-saving techniques; however, it requires continuous monitoring of water levels in the field. The implementation of real-time, electronic sensor-based precision irrigation technology may address the problems associated with conventional irrigation systems and AWD leading to high water use efficiency. Therefore, a study was undertaken to develop a suitable sensor-based automated irrigation system to maintain optimal water levels in rice fields. This study conceptualized an electronic sensor-based automated irrigation system for rice cultivated under the AWD technique. In this method, the rice field is initially flooded to a maximum depth of 5 cm. Irrigation is reapplied once the water level reduces to 10 cm below the soil surface. This developed system helps address water scarcity by regulating water levels, preventing excess ponding. It uses magnetic float-based sensors and electronic circuits to detect water levels, converting them into electronic signals transmitted wirelessly via radio frequency (RF) to a controller. The controller has been programmed for different growth stages that need to be set manually during the cropping period. The system is designed primarily for the AWD method but includes an option for continuous ponding (CP), needed during the flowering stage. The maximum water level at full maturity is set at 5 cm above the soil surface, while irrigation with the AWD method begins when the water level falls 10 cm below the soil surface. The developed system was tested during the Kharif season of 2018–19; the irrigation water productivity was 6.15 kg ha⁻¹mm⁻¹ with the automated system, compared to 3.06 kg ha⁻¹mm⁻¹ in the control (continuous ponding). Total water productivity was 4.80 kg ha⁻¹mm⁻¹ for the automated system and 2.63 kg ha⁻¹mm⁻¹ for the control. The automated system achieved 36% more water savings over the control, which used continuous ponding as farmers practice. The developed system supports AWD, a proven water-saving technique in rice cultivation. Full article

A profound transformation of the entire food system is necessary to achieve sustainable development in the agricultural sector. This pertains to the production, distribution, and consumption of food. In the case of distribution, this transformation involves changes both at the beginning of the chain, namely, in the agricultural structure, and at the final stage, in consumer behaviour. By analysing the existing literature, we identify key areas where the principles of short supply chains can be harmonised with smart village initiatives. The concept of smart villages itself is based on using modern technologies and innovative practices to improve the quality of life in rural areas and support sustainable development. Consequently, as mentioned, one of the critical elements of this concept is the cooperation of farmers for sustainable short supply chain management. This study analysed statistical data from the Central Statistical Office of Poland and unpublished data from the General Veterinary Inspectorate, complemented by desk research on relevant reports, scientific literature, and legal documents concerning local food systems. The study investigates local food systems in the Mazowieckie region, where 9% of Polish entities operating within local food systems are registered. Activity within this framework is characterised by significant spatial diversity across the region. The spatial distribution is mainly related to the location of the raw material base, e.g., the concentration of specialised agricultural production, distance to the sales market (proximity to consumers), and other broadly understood conditions for conducting business activity. The paper highlights the need to transform food systems to support sustainable agricultural development, focusing on short supply chains and smart village initiatives. By examining local food systems in Poland’s Mazowieckie region, it identifies how spatial and resource factors impact local food distribution and rural sustainability. Full article

As part of the European Green Deal, the EU has recognised that there is a need to increase organic farming as well as improve animal welfare standards. The PIGLOW app was developed with these goals in mind and allows free-range and organic pig farmers to perform welfare assessments (WAs) of their pigs. The results of each WA contain automated feedback and benchmarking information. The objective of this two-year longitudinal study was to determine whether regular use of the app helps farmers improve pig welfare. Farmers (n = 12) were asked to perform 6 WAs for finisher pigs with the app. At the beginning and end of the study, a researcher visited each farm and performed a detailed WA to determine the welfare status of the pigs at both moments. Farmers (n = 11) also filled out surveys about their opinions on pig welfare and the PIGLOW app. The welfare results did not support that the use of the PIGLOW app had an overall effect on pig welfare, but suggested a positive effect on some specific welfare aspects. Farmers indicated that they found the app easy to use and found most of its elements very useful. However, when asked about the specific influence of the app on their opinions on pig welfare and the welfare of their pigs, they indicated that the app only had small effects. Responses suggested that the app could likely be more useful to new farmers who still have more to learn about animal welfare. Full article

With the implementation of the rural revitalization strategy, rural e-commerce has become an essential means of promoting rural economic development and increasing farmers’ income. However, the development of rural e-commerce varies significantly among different regions. Based on the perspective of “three rural areas”, this study constructs a rural e-commerce development capability measurement system centered on readiness, utilization, and influence. It adopts a panel vector autoregressive model to identify key influencing factors. Through the exploratory spatiotemporal data analysis (ESTDA) method, the spatiotemporal dynamic characteristics of rural e-commerce development capacity and the interaction relationship between provinces and regions are revealed. The study shows that (1) China’s rural e-commerce development capacity gained significant improvement from 2011 to 2022, but provincial polarization is evident, with eastern and central provinces leading and western and marginal provinces lagging; the rural e-commerce development capacity shows a decreasing dynamic pattern from the east to the central and western to the northeastern regions. (2) The eastern region has active rural e-commerce development, stable spatial structure, and provincial solid correlation, which creates a significant linkage effect. The western region shows strong internal spatial dependence, the district cross-regional interaction and linkage effect are beginning to emerge, and the northeastern low-development provinces are challenging to leap to a higher level in the short term; (3) the spatiotemporal interaction network of rural e-commerce development among several provinces and regions shows a positive synergistic relationship, and it is an essential consideration for the high-quality development of rural e-commerce to strengthen regional cooperation and realize complementary advantages. The study results provide a theoretical basis for formulating differentiated regional e-commerce development policies, which can help enhance regional synergy and narrow the regional development gap. Full article

Tamil Nadu, a state in southern India, is bereft of any native dairy or dual-purpose cattle breeds, and the state depends chiefly on crossbred cattle for milk production. Jersey crossbred cattle account for 90% of the state’s milk production. This genetic evaluation study aimed to assess milk production traits, including test-day milk yields (TDMYs), total lactation milk yield (TMY), and 305-day milk yield (305MY), in these cattle reared under farmers’ conditions. Data on monthly TDMYs (TDMY1 to TDMY10) of Jersey crossbred cows (n = 75,627) reared by the farmers over 11 years (2012–2022) were collected for evaluation. The influence of non-genetic factors viz., location (agroclimatic zones), period and season of calving, and parity on TDMYs, TMY and 305MY were assessed, and the variance and covariance components for genetic parameters (heritability and genetic correlation) of the traits were estimated by the method of restricted maximum likelihood (REML) under a multivariate animal model and by a random regression model (RRM). The overall means of various TDMYs ranged from 4.98 (TDMY10) to 9.95 kg (TDMY2), and for TMY and 305MY, the means were 2480.33 and 2393.71 kg, respectively. The heritabilities estimated by the multivariate animal model for TDMYs were moderate and ranged from 0.26 ± 0.02 to 0.37 ± 0.02 and the estimates were less variable throughout lactation, while the estimates obtained by RRM were medium to high and ranged between 0.29 ± 0.01 and 0.67 ± 0.02 for milk yield on day 5 to 305 (DIM 5–DIM 305). The heritabilities estimated for TMY and 305MY were 0.43 ± 0.02 and 0.43 ± 0.02, respectively. The estimates of heritability for mid-lactation yields were comparatively less than those at the beginning and the end of lactation. The moderate to high estimates of heritabilities for TDMYs, TMY, and 305MY obtained in the present study offer ample scope for improving milk production through selective breeding. Genetic correlations between TDMYs estimated by the multivariate animal model were positive and high, with a range between 0.75 ± 0.03 and 0.99 ± 0.00. Considerably higher estimates (0.98–0.99) were observed between adjacent TDMYs showing strong genetic associations. By RRM, genetic correlations estimated between DIMs were positive (except for DIM 5 with DIM 125 to DIM 185 and DIM 125 with DIM 305), and the magnitude of genetic correlation decreased with an increase in the interval between the DIMs. The high genetic correlation observed between the TDMYs (in the early stage of lactation) and total lactation milk yield suggested that these test-day yields could be used favorably for the early selection of cows for milk production, which facilitates reduction in the generation interval and consequently increases the annual genetic gain for the milk production traits. Full article

Onion (Allium cepa) is a major field vegetable in South Korea and has been produced for a long time along with cabbage, radish, garlic, and dried peppers. However, as field vegetables, including onions, have recently been imported at low prices, the profitability of onion production in South Korea is beginning to be at risk. In order to maximize farmers’ profits through onion production, this study develops onion yield prediction models via an ensemble learning-based framework involving linear regression, polynomial regression, support vector regression, decision tree, ridge regression, and lasso regression. The use of nitrogen fertilizers is considered an independent variable in the development of the yield prediction model. This is because the use of nitrogen fertilizers accounts for the highest production cost (13.47%) after labor cost (41.21%) and seed cost (17.42%), and it also directly affects onions yields. For the model development, five research datasets on changes in onion yield according to changes in the use of existing nitrogen fertilizers were used. In addition, a non-linear optimization model was devised using onion yield prediction models for the profit maximization of onion production. As a result, the developed non-linear optimization model using polynomial regression enables an increase in profits from onion production by 67.28%. Full article

The rise of rural e-commerce, accelerated by the COVID-19 pandemic, has driven agricultural development, resulting in a dual-channel model that combines offline supermarket docking with online e-commerce direct sales. Furthermore, given the perishable nature of most agricultural products, consumers exhibit a preference for high-quality logistics services. This paper analyses the dynamics of the agricultural supply chain, beginning with the “leading enterprises + farmers” production mode, and establishes two optimal decision-making models for online and offline dual-channel agricultural supply chains, incorporating logistics service levels. The first model considers centralised decision-making, where leading agricultural producers and community superstores make decisions simultaneously, aiming to maximise the overall profit of the supply chain. The second model addresses decentralised decision-making in which the producer, as the dominant player in a Stackelberg game, anticipates the reactions of retailers and sets the wholesale price, online sales price, and online logistics service level accordingly. Retailers, as followers, then determine the offline sales price and offline logistics service level based on the producer’s decisions. Finally, we conduct a sensitivity analysis of the proposed models. Our findings reveal that as consumer focus on logistics service levels increases, the overall profit of the supply chain improves, and as the unit logistics cost corresponding to the level of logistics service increases, the marginal benefits of decreasing profit brought about by the increase in unit logistics cost also decrease. Full article