A stockpile heated and ambient air dryer (SHAD) was developed as an alternative to conventional almond windrow drying. Previous experiments showe that the drying air produced by SHAD was undesirably distributed through the almond stockpile. Therefore, an air distributor was developed containing 12 outlets, arranged in 4 rows of 3 outlets each. This study describes the comprehensive process of the air distributor design, manufacturing, and its optimization. The optimization process employed both computational fluid dynamics simulations and in-field airflow validation measurements. Initial 4-row air distributor in-field validation measurements indicated airflow distribution percentages were 4.1%, 30.8%, 44.9%, and 20.2% for the outlets in rows 1 through 4. This showed that almonds located around row 1 would not receive sufficient air to properly dry. Thus, an optimized 3-row air distributor configuration was developed and validated to yield an airflow distribution percentage of 31.3%, 44.4%, and 24.3% for outlets in the second to fourth rows, respectively. The 3-row air distributor configuration is therefore desirable, as the middle and tallest section of the stockpile will receive the highest airflow. The air distributor therefore markedly enhanced the SHAD's air supply distribution.

An almond stockpile heated and ambient air dryer (SHAD) without an air distributor, did not adequately distribute air throughout the stockpile. Therefore, this project evaluated the effect of adding an air distributor within the SHAD A-frame as an alternative method to conventional windrow drying. Three stockpile drying tests were performed using ‘Nonpareil’, ‘Winter’, and ‘Monterey’ almond varieties with different initial (fresh) weights and kernel dry-basis moisture contents (MC) equal to 4763 kg and 11.8%, 2585 kg, and 11.5%, and 6849 kg and 21.5%, respectively. All tests were directly compared to conventional windrow drying. Almond quality parameters, including kernel MC, color, lipid oxidative stability, peroxide value, free fatty acid content, internal cavities, and insect injury were measured before and after drying. The SHAD with the air distributor properly maintained almond quality, while uniformly dehydrating almonds to the desired MC of ≤6 % within 7 days. Conventional windrow drying took up to 13.6 days, and the desired final MC was only achieved with the ‘Monterey’ variety. Thus, the SHAD fitted with a well-designed air distributor can be used to dehydrate almonds in a stockpile as an alternative to conventional windrow drying.

Stomatal conductance (g_s) is a crucial component of plant physiology, as it links plant productivity and water loss through transpiration. Estimating g_s indirectly through leaf temperature (T_l) measurement is common for reducing the high labor cost associated with direct g_s measurement. However, the relationship between observed T_l and g_s can be notably affected by local environmental conditions, canopy structure, measurement scale, sample size, and g_s itself. To better understand and quantify the variation in the relationship between T_l measurements to g_s, this study analyzed the sensitivity of T_l to g_s using a high-resolution three-dimensional model that resolves interactions between microclimate and canopy structure. The model was used to simulate the sensitivity of T_l to g_s across different environmental conditions, aggregation scales (point measurement, infrared thermometer, and thermographic image), and sample sizes. Results showed that leaf-level sensitivity of T_l to g_s was highest under conditions of high net radiation flux, high vapor pressure deficit, and low boundary layer conductance. The study findings also highlighted the trade-off between measurement scale and sample size to maximize sensitivity. Smaller scale measurements (e.g., thermocouple) provided maximal sensitivity because they allow for exclusion of shaded leaves and the ground, which have low sensitivity. However, large sample sizes (up to 50 to 75) may be needed to differentiate genotypes. Larger-scale measurements (e.g., thermal camera) reduced sample size requirements but include low-sensitivity elements in the measurement. This work provides a means of estimating leaf-level sensitivity and offers quantitative guidance for balancing scale and sample size issues.