Accurate predictions of crop production are critical to developing effective strategies at the farm level. Knowing banana production is due to the need to maximize the investment–profit ratio, and the availability of this information in advance allows decisions to be made about the management of important diseases. The objective of this study was to predict the number of banana bunches from epidemiological parameters of Black Sigatoka (BS), using random forests (RF) for its ability to predict crop production responses to epidemiological variables. Weekly production data (number of banana bunches) and epidemiological parameters of BS from three adjacent banana sites in Panama during 2015–2018 were used. RF was found to be very capable of predicting the number of banana bunches, with variance explained as 70.0% and root mean square error (RMSE) of 1107.93 ± 22 of the mean banana bunches observed in the test case. The site, week, youngest leaf spotted and youngest leaf with symptoms in plants with 10 weeks of physiological age were found to be the best predictor group. Our results show that RF is an efficient and versatile machine learning method for banana production predictions based on epidemiological parameters of BS due to its high accuracy and precision, ease of use, and usefulness in data analysis.

(1) Background: Precision agriculture has been used mostly to study spatial variability in vineyards for winemaking. Nevertheless, there is little available information on the impacts of its use on table grape vineyards under different slope conditions. (2) Methods: The aim was to study the spatial variability of production and berry quality in ‘Flame Seedless’ vines established on a flat (3% slope) and sloping (23% slope) terrain in the Chilean hyper-arid northern region. (3) Results: The results showed that in both vineyards, the measured variables presented a high spatial variability according to their coefficient of variation, being higher in slope than in the flat vineyard. The geostatistical analysis showed that 82% of the measured variables presented a strong spatial dependence in the slope vineyard, whereas 45% and 55% of the variables measured in the flat vineyard presented strong and moderate spatial dependence, respectively. Elevation was related to berry quality parameters in both vineyards, while trunk vine circumference was related to berry quality for the slope vineyard and to yield for the flat vineyard. (4) Conclusions: There is an important spatial variability in table grape vineyards mostly those cultivated on slope sites. Therefore, precision agriculture tools can be useful for zoning table grape vineyards, and thus improving both economic returns of viticulturists and sustainability.

Viticulture is facing important challenges in cultivation and management since grapevines are particularly vulnerable to changes in environmental conditions. Heat waves, extreme temperatures, and unpredictable weather patterns have become more frequent in wine‐growing regions, creating an uncertain future for growers. In response, shading nets have emerged as a promising and adaptable technology to mitigate the adverse effects of climate change on grape production and wine quality. By moderating the vine microclimate, shading nets reduce solar radiation, decrease the extreme heat and wind speed, and improve water‐use efficiency, enhancing ripening dynamics and preserving berry quality. However, the effectiveness of shading nets varies depending on the shade provided and the specific characteristics of the nets, highlighting the importance of adjusting the strategies to the specific needs of each environment, productive system, and grape variety. This review explores the influence of shading nets on grapevine physiological responses, including their ability to enhance resilience to stress. It examines their impact on grape and wine quality, providing insights into this vital adaptive tool for the future of viticulture.

(1) Background: Currently, some ampelographic methods are developing in order to identify grapevine varieties. For this purpose, morpho-colorimetric parameters in leaves have been analyzed by digital imagen analysis, but some environmental conditions may affect their determinations. (2) Methods: A research study was conducted to characterize leaf morpho-colorimetric parameters in five grapevine varieties growing under different plant water status and to discriminate them under these conditions. Leaves were collected in vines, and twelve leaf morpho-colorimetric and fractal dimension variables were assessed. (3) Results: Merlot presented the highest values of perimeter and area to perimeter ratio in leaves and higher leaf area than Chardonnay in both plant water conditions. Most of the leaf morpho-colorimetric variables allowed discriminating the grapevine varieties under the contrasted hydric conditions. Under non-water stress, Carmenère was not related to any measured parameters. Merlot was positively related to most of the leaf morphometric parameters, whereas Chardonnay presented the opposite behavior. RGB color system variables allowed discriminating the grapevine varieties under water stress conditions, and Sauvignon Blanc was not related to any measured parameter. Chardonnay and Pinot Noir were positively related to green color and negatively related to most of the leaf morphometric parameters, whereas Merlot showed the opposite behavior. (4) Conclusions: Leaf morpho-colorimetric and fractal dimension parameters were affected by plant water stress and more variables should be incorporated into the new ampelographic methods in order to characterize leaf morpho-colorimetric parameters of the different grapevine varieties more clearly.

Background: Recently, antitranspirant or radiation-reflective products have been studied in several crops to mitigate the negative effects of global warming in Mediterranean climates. Nevertheless, to our knowledge, there is a scarce availability of information studying their effects on blueberries and much less from applications of sunscreens elaborated based on a mixture of dicarboxylic acids. Methods: Controls and three treatments were performed in ‘Duke’ and ‘Star’ blueberries as follows: (i) control without water stress (T1 = 100% ETc); (ii) foliar application of sunscreen in plants without water stress (T2 = 100% ETc + sunscreen); (iii) water stress in plants without foliar application of sunscreen (T3 = 50% ETc); (iv) foliar application of the sunscreen in plants with water stress (T4 = 50% ETc + sunscreen). Stem water potential (Ψs), stomatal conductance (g_s), yield, berry weight and berry total soluble solids were determined. (3) Results: As expected, the decrease in irrigation frequency in water stress treatments (T3 and T4) allowed for a decrease in the water applied at 25% compared to non-stressed plants (T1 and T2). This resulted in an increase in the Ψs on the days closest to harvest in both varieties, decreasing g_s in blueberries plants subjected to water stress conditions. Sunscreen applications to Duke plants subjected to water stress (T4) induced higher total berry soluble solids than the treatments performed in non-stressed plants (T1 and T2). Sunscreen applications to Star plants subjected to water stress (T4) promoted similar g_s levels and did not affect total soluble solids concerning irrigated plants (T1 and T2). (4) Conclusions: The results suggest that the response to water stress to sunscreen application based on dicarboxylic acid salts depended on the cultivar. Therefore, despite the novelty of this research, it is necessary to perform long-term studies to establish accurate conclusions.

Chile has become a significant producer of hazelnuts (Corylus avellana L.) due to its favorable conditions for off-season production to meet global market demand. Efficient light interception is crucial for optimizing the hazelnut yield and quality, as it directly influences the plant’s photosynthetic capacity. The goal was to assess the impact of intercepted photosynthetically active radiation (PAR) at upper, middle, and lower canopy levels in hazelnut trees grown at different planting densities and the canopy management of yield and quality parameters. The percentage of vain, sucker, double, bug, and healthy hazelnuts, including the number of fruits, total fruit weight, and grams per fruit was evaluated. The upper canopy levels intercepted the highest PAR, significantly enhancing the number and weight of fruits. The lower canopy levels received considerably less PAR, reducing the productivity. Production pruning in dense planting systems (5 × 3 m) improved the light penetration compared to a less dense planting density (5 × 6 m). Strong positive correlations were observed among PAR, fruit weight, and fruit number, emphasizing the importance of the light distribution within the canopy in hazelnut production. Production pruning and optimized planting densities are essential for maximizing light interception, improving yield, and ensuring high-quality hazelnut production.