The weather variations around the world are already having a profound impact on agricultural production. This impacts apple production and the quality of the product. Through agricultural precision, growers attempt to optimize both yield and fruit size and quality. Two experiments were conducted using field-grown “Gala” apple trees in Geneva, NY, USA, in 2021 and 2022. Mature apple trees (Malus × domestica Borkh. cv. Ultima “Gala”) grafted onto G.11 rootstock planted in 2015 were used for the experiment. Our goal was to establish a relationship between stem water potential (Ψ_trunk), which was continuously measured using microtensiometers, and the growth rate of apple fruits, measured continuously using dendrometers throughout the growing season. The second objective was to develop thresholds for Ψ_trunk to determine when to irrigate apple trees. The economic impacts of different irrigation regimes were evaluated. Three different water regimes were compared (full irrigation, rainfed and rain exclusion to induce water stress). Trees subjected the rain-exclusion treatment were not irrigated during the whole season, except in the spring (April and May; 126 mm in 2021 and 100 mm in 2022); that is, these trees did not receive water during June, July, August and half of September. Trees subjected to the rainfed treatment received only rainwater (515 mm in 2021 and 382 mm in 2022). The fully irrigated trees received rain but were also irrigated by drip irrigation (515 mm in 2021 and 565 mm in 2022). Moreover, all trees received the same amount of water out of season in autumn and winter (245 mm in 2021 and 283 mm in 2022). The microtensiometer sensors detected differences in Ψ_trunk among our treatments over the entire growing season. In both years, experimental trees with the same trunk cross-section area (TCSA) were selected (23–25 cm⁻² TCSA), and crop load was adjusted to 7 fruits·cm⁻² TCSA in 2021 and 8.5 fruits·cm⁻² TCSA in 2022. However, the irrigated trees showed the highest fruit growth rates and final fruit weight (157 g and 70 mm), followed by the rainfed only treatment (132 g and 66 mm), while the rain-exclusion treatment had the lowest fruit growth rate and final fruit size (107 g and 61 mm). The hourly fruit shrinking and swelling rate (mm·h⁻¹) measured with dendrometers and the hourly Ψ_trunk (bar) measured with microtensiometers were correlated. We developed a logistic model to correlate Ψ_trunk and fruit growth rate (g·h⁻¹), which suggested a critical value of −9.7 bars for Ψ_trunk, above which there were no negative effects on fruit growth rate due to water stress in the relatively humid conditions of New York State. A support vector machine model and a multiple regression model were developed to predict daytime hourly Ψ_trunk with radiation and VPD as input variables. Yield and fruit size were converted to crop value, which showed that managing water stress with irrigation during dry periods improved crop value in the humid climate of New York State.

Precision crop load management of apple requires counting fruiting structures at various times during the year to guide management decisions. The objective of the current study was to evaluate the accuracy of and compare different commercial computer vision systems and computer applications to estimate trunk cross-sectional area (TCSA), flower cluster number, thinning efficacy, and yield estimation. These studies evaluated two companies that offer different vision systems in a series of trials across 23 orchards in four states. Orchard Robotics uses a proprietary camera system, and Pometa (previously Farm Vision) uses a cell phone camera system. The cultivars used in the trials were ‘NY1’, ‘NY2’, ‘Empire’, ‘Granny Smith’, ‘Gala’, ‘Fuji’, and ‘Honeycrisp’. TCSA and flowering were evaluated with the Orchard Robotics camera in full rows. Flowering, fruit set, and yield estimation were evaluated with Pometa. Both systems were compared with manual measurements. Our results showed a positive linear correlation between the TCSA with the Orchard Robotics vision system and manual measurements, but the vision system underestimated the TCSA in comparison with the manual measurements (R²s between 0.5 and 0.79). Both vision systems showed a positive linear correlation between nubers of flowers and manual counts (R²s between 0.5 and 0.95). Thinning efficacy predictions (in June) were evaluated using the fruit growth rate model, by comparing manual measurements and the MaluSim computer app with the computer vision system of Pometa. Both systems showed accurate predictions when the numbers of fruits at harvest were lower than 200 fruit/tree, but our results suggest that, when the numbers of fruits at harvest were higher than 200 fruit/tree, both methods overestimated final fruit numbers per tree when compared with final fruit numbers at harvest (R²s 0.67 with both systems). Yield estimation was evaluated just before harvest (August) with the Pometa system. Yield estimation was accurate when fruit numbers were fewer than 75 fruit per tree, but, when the numbers of fruit at harvest were higher than 75 fruit per tree, the Pometa vision system underestimated the final yield (R² = 0.67). Our results concluded that the Pometa system using a smartphone offered advantages such as low cost, quick access, simple operation, and accurate precision. The Orchard Robotics vision system with an advanced camera system provided more detailed and accurate information in terms of geo-referenced information for individual trees. Both vision systems evaluated are still in early development and have the potential to provide important information for orchard managers to improve crop load management decisions.

Hail nets reduce photosynthetically active radiation (PAR) and alter the environment under the netting in apple orchards. Thus, we investigated the effect of nets on the efficacy of metamitron, a short-term photosynthesis inhibitor used for fruit thinning. The objective of this study was to evaluate the effect of the netting and metamitron on thinning efficacy, yield, fruit quality and chlorophyll fluorescence in three apple (Malus domestica Borkh.) cultivars. One or two metamitron applications at different doses or rates were applied the tree under different coloured nets. The reduction of PAR was highest with black nets (19%-22%), followed by green (13%-15%) and white nets (6%-11%). There were no significant differences (P> 0.05) in fruit weight or size with or without nets. Double applications of metamitron increased average fruit fresh weight and reduced the fruit set over four experiments. In contrast, single applications were less effective. In two experiments, thinning was associated with lower yields. However, there was no effect in the other two experiments. The double treatments tended to increase the percentage of the crop with fruit larger than 70 mm in diameter. All thinning strategies showed similar inhibition in fluorescence, with the only observed significant differences between treatments occurring when using a single or double application. The results show that netting does not affect the response to thinning with metamitron.