Search Results (68)

Based on a sample of 412 apple farmer households across Gansu, Shaanxi, Shanxi, and Shandong provinces in China, this study estimates production efficiency and its determinants for apple growers. The stochastic frontier analysis model estimates technical efficiency while the Tobit model identifies influencing factors. Results show that the average production efficiency of smallholder apple farmers is relatively low at 0.45, indicating significant room for improvement. Production efficiency exhibits an inverted “U” relationship with farm scale, and excessive pesticide inputs have a significant negative impact on efficiency. Computer use to search for information among farmers was found to significantly improve apple production efficiency, indicating the potential benefits of ICT adoption. However, membership in cooperatives had no significant effect on efficiency. Overall, these findings suggest approaches to enhance the productivity of China’s apple growers through improved resource allocation, optimized farm scale, and the promotion of information technology. Full article

This study employed the HYDRUS-2D model to simulate soil water movement and water productivity (WP) in an apple–soybean alley cropping system in the Loess Plateau region, Shanxi Province, China, under four irrigation methods: mulched drip irrigation, subsurface drip irrigation, bubbler irrigation, and rainwater-harvesting ditch irrigation, with varying water management treatments. Field experiments provided 2022 data for model calibration and 2023 data for validation using soil water content (SWC) measurements, achieving R² = 0.80–0.87 and RMSE = 0.011–0.017 cm³·cm⁻³, confirming robust simulation accuracy. The simulation results indicated that different irrigation methods had a significant impact on the soil water distribution. Mulched drip irrigation enhanced the water content in the surface layer (0–20 cm), while subsurface drip irrigation increased the moisture in the middle soil layer (20–40 cm). Bubbler irrigation was most effective in replenishing both the surface (0–20 cm) and middle (20–40 cm) layers. Rainwater-harvesting ditch irrigation significantly improved the soil water content in both the surface (0–20 cm) and middle (20–40 cm) layers, with minimal changes observed in the deep layer (40–120 cm). Furthermore, soil water variations were significantly influenced by the water uptake of tree roots. In 2022, soil moisture initially increased with distance, then decreased, and subsequently increased again, while in 2023, it increased initially and then stabilized. When the irrigation amount was limited to 75% of the field capacity in the 0–60 cm soil layer, water productivity (WP) reached its optimum, with values of 4.79 kg/m³ (2022) and 5.56 kg/m³ (2023). Based on the simulation results, it is recommended that young apple trees be irrigated using subsurface drip irrigation with a soil layer depth of 30 cm, while soybeans should be irrigated with mulched drip irrigation. Both crops should be irrigated at the podding and filling stages of soybeans, and the irrigation amount should be limited to 75% of the field water capacity in the 0–60 cm soil layer. This study was designed to aid orchard growers in precision irrigation and water optimization. Full article

Accurate apple yield estimation is essential for effective orchard management, market planning, and ensuring growers’ income. However, complex orchard conditions, such as dense foliage occlusion and overlapping fruits, present challenges to large-scale yield estimation. This study introduces APYOLO, an enhanced apple detection algorithm based on an improved YOLOv11, integrated with the DeepSORT tracking algorithm to improve both detection accuracy and operational speed. APYOLO incorporates a multi-scale channel attention (MSCA) mechanism and an enhanced multi-scale prior distribution intersection over union (EnMPDIoU) loss function to enhance target localization and recognition under complex environments. Experimental results demonstrate that APYOLO outperforms the original YOLOv11 by improving mAP@0.5, mAP@0.5–0.95, accuracy, and recall by 2.2%, 2.1%, 0.8%, and 2.3%, respectively. Additionally, the combination of a unique ID with the region of line (ROL) strategy in DeepSORT further boosts yield estimation accuracy to 84.45%, surpassing the performance of the unique ID method alone. This study provides a more precise and efficient system for apple yield estimation, offering strong technical support for intelligent and refined orchard management. Full article

Agriculture’s sustainable growth necessitates the application of advanced science and technology to ensure the sensible use of resources and improve the agricultural economy’s long-term stability. In this study, apple trees were employed as research objects throughout the spring (NSS) and autumn shoot stop-growing stage (ASS), and the data source was canopy hyperspectral data of fruit trees collected using ASD near-earth sensors, which was then combined with multiple sensitive wavelength screening algorithms and machine learning models to create an efficient and accurate apple yield estimation system. This is critical for guiding fruit farmers’ production, maintaining market supply and demand balances, fostering stable agricultural economy development, and providing a scientific basis and technical support for agricultural sustainability. Firstly, the fruit tree canopy hyperspectral data and apple tree yield data were collected, and the Savitsky–Golay convolution smoothing method (SG) was used to preprocess the canopy hyperspectral data. Secondly, six algorithms—Competitive Adaptive Re-weighting Sampling (CARS), Genetic Algorithm (GA), Successive Projections Algorithm (SPA), Uninformative Variable Elimination Algorithm (UVE), Variable Iteration Spatial Shrinking Algorithm (VISSA), and Variable Combination Population Algorithm (VCPA)—were employed to screen for the sensitive wavelengths related to apple tree yield, then preferring three methods for two-by-two combinations to determine the optimal algorithm combinations. Finally, using the best algorithm combinations, we built the apple yield linear model partial least squares regression (PLSR) and three machine learning models, Random Forest (RF), Cubist, and XGBoost, to screen for the best estimation model. The results demonstrated that ASS was the best fertility period for estimating yield; the validation set of the model constructed using each algorithm in ASS had a higher R² of 0.05–0.51 and a lower RMSE of 0.21–5.33 than those in NSS. The three algorithms preferred were CARS, GA, and VISSA. After combining the three algorithms in two combinations, the best combination of VISSA-CARS was found. The RF model established based on the best VISSA-CARS combination algorithm is the best model for apple yield estimation, with a validation set R² = 0.78 and RMSE = 6.03. The findings of this study may provide a new concept for accurately and quickly estimating apple yield, allowing fruit growers to improve production efficiency and promote agricultural sustainability. Full article

Freeze-drying fresh vegetables and fruits may not only prevent post-harvest losses but also provide a concentrated source of nutrients and phytochemicals. This study focused on the phenolic composition of different freeze-dried products derived from horticultural crop remains (HCRs) in the vegetable and fruit production chain. These products may be considered as a potential health-promoting solution for preventing post-harvest fruit spoiling and losses. The total polyphenolic content (TPC) and the main phenolics were studied using high-performance liquid chromatography (HPLC) with a diode array detector (DAD). Additionally, an in vitro chemical screening of the antioxidant capacity was carried out using the Ferric Reducing Antioxidant Power (FRAP) assay. These analyses were performed together with an investigation of the correlations among phenolics and their antioxidant properties, and a bioinformatic approach was used to estimate the main potential bio-targets in human beings. Furthermore, a statistical approach using Principal Component Analysis (PCA) was carried out for a multivariate characterization of these products. Catechins, flavonols, and phenolic acids were the predominant and most discriminating classes in different products. The TPC values obtained in this study ranged from 366.86 ± 71.30 mg GAE/100 g DW (apple, MD) to 1077.13 ± 35.47 mg GAE/100 g DW (blueberry, MID) and 1102.25 ± 219.71 mg GAE/100 g DW (kaki, KD). The FRAP values ranged from 49.28 ± 2.88 mmol Fe²⁺/kg DW (apple, MD) to 80.43 ± 0.02 mmol Fe²⁺/kg DW (blueberry, MID) and 79.05 ± 0.21 mmol Fe²⁺/kg DW (kaki, KD). The proposed approach may be an effective tool for quality control and valorization of these products. This study showed that the utilization of crop remains can potentially lead to the development of new functional foods, providing additional economic benefits for farmers. Finally, the use of freeze-drying may potentially be a sustainable and beneficial solution for growers who may directly utilize this technology to produce dried products from the crop remains of their fruit productions. Full article

In the context of precision horticulture, decision support tools play a significant role in providing fruit growers with insights into orchard conditions, facilitating informed decisions regarding orchard management practices. This study presents the development of an autonomous yield estimation system designed to provide decision support to small commercial orchards. Autonomous yield estimation is based on the application of UAVs and AI. AI is used to identify and quantify fruitlets and fruits in photographs collected by UAV. In this article, we present our prototype of an autonomous yield estimation system. The adapted “4+1” architecture was applied to design a system with a holistic approach analyzing software, hardware, and ecosystem requirements. Six datasets are presented, which contain the images of fruitlets and fruits of apples, pears, and cherries. Three CNN models were trained: YOLOv8m, YOLOv9m, and YOLOv10m. The experiment showed that the most accurate was YOLOv9m, which achieved mean accuracies of 0.896 mAP@50 and 0.510 mAP@50:95 for all datasets. Full article

Apple scab, caused by Venturia inaequalis, is one of the most important diseases in apples in all production regions and its sustainable control is still a challenge. The aim of this work was to optimize the control of apple scab through different environmentally friendly inoculum management strategies, specifically the removal of fallen leaves in winter and the treatment of ground leaves with the biological agent Trichoderma asperellum (T34 BIOCONTROL^®) to inhibit or prevent inoculum development in commercial orchards. The results obtained from 4 years of trials in commercial orchards demonstrated that the combination of fungicide treatments and leaf litter management, particularly through aspiration, significantly reduced the development of apple scab in comparison with strategies commonly used by growers that are based solely on fungicide application. Both the incidence and severity of the disease in leaves and fruit decreased by over 90% when inoculum management and fungicide treatments were combined. These results highlight that reducing the source of inoculum by removing fallen leaves is an effective strategy that complements fungicide or biological control agent applications. In conclusion, combining eco-friendly strategies with standard fungicides and monitoring environmental conditions can help to reduce the frequency of phytosanitary applications, ultimately contributing to the goal of minimizing their use in the control of apple scab. Full article

This study investigates the economic and ecological impacts of straw returning technology among apple growers in Shaanxi and Gansu provinces, China. Using Propensity Score Matching (PSM) and survey data, the findings reveal that straw returning significantly increases farmers’ incomes by 20.33% compared to those who do not adopt the technology. Additionally, the technology mitigates soil fertility decline by 11.07%, offering substantial ecological benefits. The heterogeneity analysis highlights that older farmers benefit more from the technology in terms of both income and soil fertility improvement, likely due to their experience and reliance on farming. Smaller-scale farmers also show greater gains in income and soil health, while larger-scale farms face complexities that may delay visible benefits. However, land fragmentation did not significantly influence the outcomes. The study recommends promoting straw returning through enhanced farmer training, financial incentives, and improved access to credit. Policymakers should consider tailoring support to different farmer demographics and orchard sizes. Future research should focus on long-term evaluations of straw returning’s sustainability in terms of soil fertility and crop yields. Overall, straw returning technology offers a promising solution for enhancing both economic returns and environmental sustainability in apple production. Full article

The apple tree (Malus × domestica Borkh.) belongs to the Rosaceae. Due to its adaptability and tolerance to different soil and climatic conditions, it is cultivated worldwide for fresh consumption. The priorities of apple growers are high-quality fruits and stable yield for high production. About 90 to 95 percent of fruits should fall or be eliminated from apple trees to avoid overcropping and poor-quality fruits. Apple trees engage in a complex biological process known as yield self-regulation, which is influenced by several internal and external factors. Apple buds develop in different stages along the branches, and they can potentially give rise to new shoots, leaves, flowers, or fruit clusters. The apple genotype determines how many buds will develop into fruit-bearing structures and the capacity for yield self-regulation. Plant hormones such as ethylene, cytokinins, auxins, and gibberellins play a crucial role in regulating the fruit set, growth, and development, and the balance of these hormones influences the flowering intensity, fruit size, and fruit number on the apple tree. Apple growers often interfere in the self-regulation process by manually thinning fruit clusters. Different thinning methods, such as by hand, mechanical thinning, or applying chemical substances, are used for flower and fruit thinning. The most profitable in commercial orchards is the use of chemicals for elimination, but more environmentally sustainable solutions are required due to the European Green Deal. This review focuses on the biological factors and genetic mechanisms in apple yield self-regulation for a better understanding of the regulatory mechanism of fruitlet abscission for future breeding programs targeted at self-regulating yield apple varieties. Full article

Loquat is an evergreen fruit crop which blooms from autumn–winter, and supports human beings with juicy fruit from late spring to early summer. However, the most traditional cultivars of this crop produce small fruit and bear a much lower yield than its relatives like apple, pear and peach. Large-size cultivars have long been a cherished aim of breeders for improving the production yield of loquat. Agronomic practices like panicle thinning, fruit thinning, growth regulator application, fertilization and so on are easier and more accessible ways for growers to produce large-size loquat fruit on existing production trees. Here, we develop a novel pruning method with an annual double back-cut, which provides vigorous shoot with more leaves and thicker branches for bearing much larger loquat fruit. Cellular observation determined that the vigorous shoot training method motivated cell division to produce larger loquat fruit, and that most of these cell layers were proliferated before the appearance of flower blossoms. Gene expression data of four development stages showed that EjFWL1 and EjFWL2 were notably downregulated in flower buds of the vigorously pruned tree. The data here further confirmed that the cell division capacity during flower development greatly influenced both the flower and fruit size of loquat. More importantly, we developed a novel pruning method to inhibit cell division repressors, promote cell proliferation and enlarge fruit size in loquat. Full article

Based on the field survey data for 1216 apple growers in three provinces from China’s Loess Plateau Region, this paper adopted Multivariate Probit (MVP) model and intermediary effect model to analyze the influence mechanisms of digital technology adoption (DTA) on farmers’ choices of Fertilizer-reduction and Efficiency-improving Technologies (FETs) from the perspective of farmers’ cognition (FC). The correlation effects of three typical FETs of soil testing and formula fertilization, integrated water-fertilizer fertilization and slow/controlled release fertilizer, were tested empirically. The results showed that DTA could significantly affect the adoption of FETs by apple growers, and FC played a partial mediating role, and there were complementary effects among the three typical FETs. The results were further confirmed by the propensity score matching (PSM) robustness test and the instrumental variable (IV) endogeneity test conducted in the conditional mixed-process (CMP). The results of our heterogeneity analysis showed that the promotion effect of DTA on FETs in the group with junior high school education or below was more significant than that in the group with higher education, and the promotion effect was more significant in the group with large operation scale. Therefore, the improvement in Internet penetration should not be taken as the ultimate goal, but more attention should be paid to farmers’ mastery and effective use of DTA, promote the improvement in farmers’ cognitive level, and implement the “bundled” publicity and guidance strategy of FETs adoption, so as to help in the green transformation of agriculture. Full article

Green production is crucial in promoting sustainable agricultural practices, ensuring food safety, and protecting the rural ecological environment. Farmers, as the main decision makers of agricultural production, and their green production behaviors (GPBs), directly determine the process of agricultural green development. Based on the survey data of 656 apple growers in Shaanxi and Gansu provinces in 2022, this paper uses a graded response model to measure the information acquisition ability (IAA) of farmers and constructs an ordered Logit model to empirically explore the influence mechanisms of IAA, green benefit cognition (GBC), and new technology learning attitude (NTLA) on farmers’ GPBs. The results show the following: (1) IAA has a significantly positive impact on the adoption of GPBs by farmers, and farmers with a high IAA are more conscious to adopt green production technologies; (2) in the process of IAA affecting farmers’ adoption of GPBs, GBC plays a positive mediating role; (3) NTLAs have a positive moderating effect on the process of GBC affecting farmers’ GPB adoption; (4) there are generational, educational and regional differences in the impact of IAA on farmers’ GPBs. Policy makers should improve rural information facilities, strengthen agricultural technology promotion and training, improve farmers’ IAA and benefit awareness level, and formulate relevant policies to mobilize farmers’ enthusiasm for learning new technologies. Full article

For the CO-FRESH (CO-creating sustainable and competitive FRuits and vEgetableS’ value cHains in Europe) project, implemented under Horizon 2020, the main objective is to design and pilot innovative system approaches to agri-food value chains in order to scale up this innovation at the European level. The Association of Polish Organic Fruit Producers POLSKI EKOOWOC has been selected as a pilot unit of the CO-FRESH project. The association includes 20 certified organic fruit growers from central Poland. Their acreage comprises more than 600 ha of organic orchards and plantations, producing 30,000 tonnes of organic fruit annually. During the course of the CO-FRESH project, a uniform methodology was developed to analyse and redesign the selected pilot units. A definition and description of the EKOOWOC association as a value chain in fruit production was first made. Then, after appropriate project training, a SWOT analysis was carried out for EKOOWOC in a meeting of a Polish working group of 10 people representing the downstream links in the production chain of this pilot unit. At the same meeting, a selection of proposed innovations for EKOOWOC was carried out. Several innovations important for the development of the pilot unit were pre-selected. After a few days, through a DELPHI survey, the working group selected the most important innovations for the EKOOWOC pilot unit. The creation of an online shop for the sale of organic fruit was chosen; the commercial activity here is combined with an educational activity, as customers ordering fruit learn about the qualities of organic apples of different varieties. Another innovation is the composting of organic residues from the orchard, with the aim of minimising organic waste. Two experimental compost heaps were set up, made up of several layers of waste—straw, waste apples, soil from organic mushrooms, leaves from the orchard and cut branches. The compost used a preparation of microoganisms, fermented organic matter and a natural mineral containing 64 elements. The final innovation was the production of vinegar from organic apples that do not meet commercial requirements. These are healthy fruits with too-small a diameter or an unusual shape. This action also minimises producer losses and allows for the use of waste materials. Organic vinegar has great health-promoting qualities and can be used for both culinary and cosmetic–medicinal purposes. The innovations are currently in the implementation phase and will be implemented from October 2023. Full article

Households are among the greatest contributors to food waste generation, particularly in fresh fruit and vegetables. From a policy perspective, reductions in household food waste are generally perceived to generate positive outcomes; however, the economic impacts are transmitted throughout the food value chain. In this paper, an Equilibrium Displacement Model (EDM) of the Australian apple industry is used to demonstrate the potential changes in economic welfare among apple industry participants from a reduction in household demand for food waste. Overall, there is an industry loss of economic surplus with apple growers, wholesalers, processors, and retailers who are adversely impacted. Domestic consumers potentially gain from increased food security at lower prices; however, the direction and magnitude of the change in consumer welfare are ambiguous and dependent on the treatment of consumer surplus on food waste in economic surplus calculations. This ambiguity likely has implications for current policies to combat food waste. The distributional impacts of changes in economic welfare among industry stakeholders emphasise the need for a collaborative approach to the food waste problem. Full article

For some apple cultivars, inadequate red fruit color development can reduce crop value. The use of reflective groundcovers has been demonstrated to improve red coloration in apples in other regions, but evaluation in the southeastern USA has been limited. To address this, we compared the performance of multiple reflective groundcovers in 2018 and 2020 on mature ‘Fuji’ trees in Edneyville, NC, USA. Woven reflective (Extenday^® DayBright, Lumilys^® WH100, Beltech PD2911, and Belton experimental), mylar, and sod groundcovers were deployed ~5 weeks before anticipated harvest. The effects of the treatment on light reflectance (photosynthetically active and UV radiation), fruit color, fruit quality, and crop value were determined. Across both years of evaluation, reflective groundcovers were consistent in increasing the reflectance of photosynthetically active radiation. However, only Extenday^® DayBright consistently increased reflected UV radiation (250–400 nm), red fruit coloration at commercial harvest, and crop value. Fruit maturity and sunburn incidence were not influenced by any treatment in both years. Reflected UV light quality was not characterized, but it is clear that UV_250–400nm reflectance intensity is critical to enhance ‘Fuji’ fruit color development. Growers in the southeastern US can use reflective groundcovers to enhance red fruit coloration to meet market demands. Full article