ASHS 2024 Conference

Eight rootstock cultivars were planted in 2017 as part of the NC-140 semi-dwarfing peach [Prunus persica (L.) Batsch] rootstock trial. The eight rootstock cultivars were budded to ‘Cresthaven’ and examined for their potential use in Western Colorado high density production systems. Listed in order of declining vigor the rootstocks included ‘Guardian®’, ‘Rootpac® 20’, ‘Lovell’, ‘ControllerTM 8’, ‘ControllerTM 6’, ‘Rootpac® 40’, ‘ControllerTM 7’, and ‘MP-29’. One rootstock, ‘ControllerTM 7’, was unable to perform in alkaline soils, showing extreme iron chlorosis and diminutive fruit size. Deemed unsuitable for use in Colorado, this rootstock was removed from analysis in the 3rd leaf. Six years of data showed that all remaining rootstocks, except ‘MP-29,’ had vigor profiles within 14% of ‘Lovell’, a known standard, making them attractive candidates for use in high density production. The two ‘Rootpac®’ rootstocks performed contrary to previous reports. ‘Rootpac® 20’ was the second most vigorous and ‘Rootpac® 40’ was the third least vigorous, slightly larger than ‘ControllerTM 6’. Additional physiological traits showing distinct differences between the rootstocks were yield, proleptic shoot formation, light interception, fruit size, and internal fruit quality. In the six years since planting there have been three harvests. Cumulative yield showed a strong linear relationship to vigor (TCSA). ‘ControllerTM 6’ had early precocity and high yields given its vigor class. Observance of gummosis was also positively associated with vigor. Both vigor and proleptic shoot formation manipulated the canopy light environment. ‘ControllerTM’ series rootstocks had increased proleptic shoot formation. Vigor-limiting rootstocks had increased light availability in the canopy leading to enhanced dry matter content and soluble solid concentration. Cumulative fruit size and weight showed ‘Rootpac® 20’ had the heaviest, and ‘ControllerTM 6’ the largest, fruit size. ‘MP-29’, the most dwarfing rootstock produced smaller fruit on average; however, fruit size was still commercially acceptable.

Compost, mulch and manures have been reported as a potential substitute for synthetic fertilizer in fruit orchards, can improve soil health as well as increase the sustainability of orchard systems. In this study, we compared two rates (10 tons/acre as compost 1x and 20tons/acre as compost 2x) of pre-plant incorporation of food waste compost (FWC) and growers’ standard rate of inorganic/chemical fertilizer (control) of a replanted and virgin peach orchards in South Carolina. Measurement includes soil health indicators such as soil nutritional status and macronutrient dynamics, yield, and fruit quality (specifically on the incidence of diseases and physiological disorders). We hypothesized that the pre-plant incorporation of organic matter with subsequent topical application would improve soil moisture and nutrient availability, increase yield, and enhance the quality of marketable fruits. Higher cation exchange capacity and buffering capacity was recorded in soil treated with FWC than in the control treatment. In the replanted orchard, the 2x treatment resulted in improving soil health indicators such as SOM, cation exchange capacity, phosphorus, soil infiltration, and soil moisture, but not in the virgin orchard compared to the control treatment. Soil extractable P was higher in the FWC treatment as compared to the control treatment, while the soil extractable K ranges from high to excessive K across all treatments. No significant difference between the yields from both orchards. However, we observed numerical differences in the yields of the 2x treatment compared to the 1x and control treatments. Our results show that the yearly application of compost provides the orchard’s nutritional requirement, increases yield, and lower disease pressure in both orchards compared to the control treatments.

Rootstocks are widely used for commercial orchard establishments throughout the world, as they facilitate scion adaptation to challenging edaphic and environmental conditions, as well as mitigate the impact of pests and diseases. Furthermore, rootstocks may influence physiological, biochemical, or phenological processes in the scion. Nevertheless, little is known about the influence of rootstocks on metabolomic profiles of Prunus scions, particularly in low-chill cultivars. This study aimed to determine the influence of rootstocks with varied chilling requirements on the metabolomic profiles of low-chill peaches. Scion ‘UFSun’ was grafted on low-(Flordaguard), medium-(P-22), and high-(MP-29, Guardian, and Nemaguard) chill requirement rootstocks, and grown in a greenhouse in Gainesville, Florida. Vegetative tissue samples were collected for extraction of metabolites. Untargeted compounds were analyzed using an Orbitrap Fusion Tribrid mass spectrometer system, interfaced with an automated A VanquishTM UHPLC system, and a total of 152 metabolites were detected. Potential differences in metabolomes associated with the rootstocks were analyzed by performing a partial least square–discriminant analysis (PLS-DA), although it was not possible to determine group differences when comparing all treatments. An orthogonal PLS-DA approach supported by permutational MANOVA test was implemented for paired comparison of plants grafted on Flordaguard (rootstock recommended for commercial production in Florida) vs. all other rootstocks, and differences were observed for all comparisons. For further confirmation of these results, and determination of the metabolites potentially differentially expressed due to rootstock influence, the Empirical Bayesian Analysis of Microarrays (EBAM) approach was implemented, as adjusted for analysis of metabolites in MetaboAnalyst 6.0. A total of 85, 52, 0, and 61 metabolites were dimmed as potentially differentially expressed when comparing trees grafted on Flordaguard vs. P-22, MP-29, Guardian, and Nemaguard, respectively. Most of these metabolites may be flavonoids, phenylpropanoids, and polyketides. According to our observations, low-, medium-, and high-chill rootstocks can influence the metabolomic profile of low-chill scions.

In the orchard production system, upright or pillar trees with vertical branch orientations have narrow architecture profiles and therefore can be suited to high-density planting to increase productivity. In plum (Prunus domestica), there are natural variations of tree forms that range from upright to more horizontal growth habit. Recently, researchers at the USDA-ARS Appalachian Fruit Research Station demonstrated that silencing TILLER ANGLE CONTROL 1 (TAC1) via RNA interference (RNAi) in ‘President’ plum led to pillar tree forms with upright lateral shoot growth, whereas silencing LAZY1 in ‘Stanley’ plum resulted in outward shoot orientations and weeping tree shape. The objective of this study was to assess the effects of tree architectures on canopy light availability and fruit quality using field-grown mature (7-year-old) TAC1 and LAZY1 silenced plum trees in comparison with their respective non-transgenic counterparts as controls. Our results indicated that slender canopy profiles due to silencing of TAC1 allowed significantly greater light availability without negative impacts on fruit size, soluble solids contents, or titratable acidity compared to non-transgenic plum with the same genetic background. Additionally, skin color of fruit was more uniform in TAC1-RNAi lines than in standard-shaped control trees, suggesting a positive correlation between canopy light distribution and fruit coloration in association with upright branch orientations. In contrast, light availability in LAZY1-RNAi tree was reduced significantly by over 50% compared to the control. Although there is no difference in fruit size, soluble solids content in fruit of the LAZY1-RNAi plum than that of the non-transgenic counterpart.

Phenological models use local temperature data to predict spring flower bud development and guide management decisions in temperate fruit crops. In high elevation continental regions such as the U.S. Intermountain West, changing climate brings more extreme temperature variability resulting in increased risk of spring freeze damage. We evaluated bloom dates of tart cherry (Prunus cerasus L. ‘Montmorency’) in a high elevation continental climate (1327 to 1484 m elevation, Utah) to test the validity of 50-year-old phenological models under current climatic conditions. Mature commercial tart cherry blocks were selected in proximity to existing weather stations (climate.usu.edu, FGNet). Bud stages were observed weekly in April and May of 2019 through 2023 with 3 to 8 locations monitored per year. Observed stages were compared to Utah Standard and Modified prediction models. Prediction error varied with year and stage of development, where 2023 bloom was on average 3 days earlier than predicted, compared to 2020 when bloom was 6 days later than predicted. Modern weather stations provide more detailed climatic data (hourly temperature, light, humidity, wind speed), and the opportunity to refine and improve existing models. Improved model reliability would provide better decision support for increasingly expensive freeze protection measures.

Temperate orchard sites have highly variable soils that contribute to uneven tree growth, providing a unique setting for precision management efforts. Precision management seeks to map spatial variability and implement variable rate management to optimize inputs. The objective of this study was to develop a platform for simultaneous measurement of tree growth and size to facilitate the enhancement of precision management practices in tart cherry (Prunus cerasus) orchards. Measurements included: canopy light interception; canopy height, volume, and width; and trunk cross sectional area (TCSA). Light interception (ceptometry) was by 15 30-cm line quantum sensors recording PAR at 0.6-second intervals, positioned on a UTV-mounted boom that passed under the canopy. Light interception was calculated based on data from a reference PAR sensor placed outside the orchard. Canopy height, width and volume of individual trees were measured using a side-scan LiDAR system mounted to the same UTV that generated point-cloud maps of each orchard row. These canopy measurements were then compared to point-cloud maps generated from aerial visual imaging (UAV). TCSA was estimated using a stereovision depth camera that captured paired visual spectrum (RGB) and point-cloud images, that were then aligned and segmented for individual tree trunks. Using pixel depth data, trunk widths for individual trees were estimated. The platform and associated sensors were used to map four commercial tart cherry orchard blocks (8-10 ha) located near Santaquin, Utah, USA, during the 2023 (ceptometry and UAV, only) and 2024 seasons at 2-week intervals. During the 2023 season, 8 ceptometry maps were generated with corresponding UAV-based maps. Side scan lidar data for 1 map of canopy height, width, and volume were collected in each of the 4 orchards, along with data for 1 TCSA map. Preliminary analysis shows strong spatial agreement among mapping techniques, indicating that the technologies are well suited to precision orchard management. Data for 2024 will also be presented, with multi-season tree growth analysis.

Tart cherry (Prunus cerasus) orchard sites are often chosen for favorable microclimates, and consequently exhibit highly diverse soil conditions that result in non-uniform tree growth and yield potential. There is increasing interest in utilizing precision management techniques to map tree vigor and implement variable rate management to optimize inputs and enhance uniformity. The objective of this study was to assess the variability of soil and canopy characteristics and implement prescription fertilizer rates based on the mapped variability. The study was conducted on four mature (18-22 years) commercial tart cherry orchard blocks (8-10 ha) located near Santaquin, Utah, USA. Soil variability maps for each orchard were generated through soil sampling, guided by surveying apparent electrical conductivity (ECa) using an electromagnetic induction meter. Spatial variability in tree vigor was quantified using satellite imagery provided by Simplot Smart Farm® Permanent Crop Analysis. Prescription fertilizer rates, derived from the variability maps, were applied to each block in the spring/summer of 2023 and 2024, which included granular fertilizer applied as a single application or as split applications based on each prescription map. Tree response to the prescription treatments were monitored every two weeks using a novel platform capable of mapping plant growth parameters including canopy height, volume, width, and density; and trunk cross sectional area (TCSA). By monitoring growth parameters within this timeframe, we were able to comprehensively evaluate within-seasonal fluctuations in growth. Soil sampling revealed significant correlations between ECa and soil texture. Preliminary results indicate significant within-orchard variations in mid-season tree vigor, that are also correlated with long-term growth characteristics (canopy size and density). Both long-term and short-term growth measures are also closely correlated with soil ECa (i.e. texture). The effect of variable fertilizer application within this soil texture variability will be discussed, offering insight into the effectiveness of precision management techniques in mitigating variability within tart cherry orchards.

Timing application of dormancy breaking products is essential for adequate bloom and yield in cherry. Available temperature-based chill accumulation models often fail to predict correct spray timing, particularly during years with unusual temperature patterns recently driven by climate change. One potential cause for the unreliability of the current models is their dependence on a single climatic variable, air temperature, to estimate the impact of weather on tree physiological processes. We hypothesized that using tree temperature, rather than air temperature, will increase the accuracy in predicting chill accumulation, especially in warm and sunny winters. Hence, our objective was to develop a framework to predict cherry tree temperature based on easily available environmental data. For three consecutive seasons and in three commercial cherry orchards across California, including the southernmost US cherry production region, we measured main climatic parameters at half hour intervals. At the same time, we monitored tree temperature with T-type thermocouples inserted below the bark of main branches. We developed predictions of tree temperature as a function of meteorological variables obtained from public weather stations using generalized additive models. Trees were, on average, 10 ºF warmer than the air during clear days, with differences being up to 20-25 ºF. Tree chill accumulation was about 8-12 chill portions lower than air chill accumulation. The difference was year- and site-specific, reflecting the importance of including diverse environmental parameters to estimate chill accumulation precisely. The ‘TreeChill model’ predicts tree temperature based only on environmental parameters easily achievable from public weather stations with a coefficient of determination of 0.956 resulting in only 0.4 chill portions difference between measured and predicted tree chill. This model will enable growers to implement tree temperature in their management decisions, including dormancy breaking agent applications, cultivar selection, pest control etc, increasing California cherry industry resilience to climate change. In the future, we plan to adapt the model to different crops and locations.