Written by Lav Khot, Basavaraj Amogi, B. Sallato, C. Torres, R. T. Peters, Washington State University, March 7, 2024
Introduction
Frequent heat waves are posing a significant challenge to agricultural production management globally and in the U.S. pacific northwest (PNW) region. The phenomenon, often referred to as a “heat dome,” is characterized by an unusually high-pressured atmosphere persisting over extended periods, accompanied by warmer minimum temperatures at night (NOAA, 2023; Still et al., 2023). In 2021, the PNW and parts of the Canada experienced record heat levels, leading to substantial losses in fruit crops. Such scenarios are becoming a serious challenge to fresh market apple growers in the region as they manage crop load and fruit quality during the summer months. The heat waves not only challenge effective use of mitigation techniques (e.g., overhead sprinklers, foggers, netting and combination of fogging and netting) aimed at minimizing crop losses but also impact fruit quality at harvest and during storage.
Methods
In this three-year project (2021-2023), we evaluated the above-mentioned heat stress mitigation techniques in cv. Honeycrisp and WA38 (Figure 1).
Figure 1. Heat stress mitigation treatments:
Impact of in-season heat mitigation by respective technique on fruit quality at harvest and after storage was studied. This project also piloted localized air temperature (Tair) sensing technology driven automated heat stress management in both cultivars with extended two seasons evaluation in cv. WA38 (Figure 2). Pertinent data was then used to understand cost effectiveness of each of the heat stress mitigation technology.
In ‘Honeycrisp,’ conventional evaporative cooling (‘conventional’), fogging, netting, and fognet (foggers installed underneath netting) treatments were evaluated in the commercial orchard block. In ‘WA38,’ only fogging and netting techniques were evaluated in the WSU IAREC research block. At both sites, untreated control with no heat mitigation (‘control’) was established to compare against heat stress mitigation techniques. Treatment effectiveness was assessed by monitoring fruit surface temperature (FST) and localized weather (air temperature, relative humidity, solar radiation, wind speed) throughout the season using a crop physiology sensing system (CPSS) installed in each treatment (five in Honeycrisp and three in WA38) including control. CPSS was prototyped and developed through USDA-NIFA funding (2018-2021) and has capability to automate FST driven cooling system actuation (Figure 2) as well as quantifying canopy stress and fruit color progression at user-defined intervals (e.g., 5-min) during daylight hours.
As a ground truth, actual FST, fruit growth progression attributes and amount of water use by respective cooling techniques were measured in each of the treatments throughout the season. Fruits harvested from each treatment were also evaluated for sunburn and storage disorders (e.g., bitter pit and soft scald) for six months.
Findings
Overall, conventional, fogging, and fognet reliably mitigated heat stress in cv. Honeycrisp with Tair and FST below respective critical thresholds of 90 °F and 113 °F. However, their effectiveness varied between seasons. On hotter days, conventional evaporative cooling with 25 min ON/OFF cycles (manual) occasionally failed to maintain FST below threshold during late afternoon hours (3:00 – 5:00 p.m. Pacific). Use of variable cycle frequency tied with changes in either or both Tair and FST (i.e., automation) would be ideal in such scenarios. This would also help reduce excess water use, about 56% in our trials, due to non-precise manual cyclic operational practices. Similarly, effectiveness of fogging which uses 7% less water compared to conventional cooling for equal operational hours, could be compromised if Tair continuously rises above 95 °F (FST > 113 °F). This could be overcome by reducing the spacing between foggers, placing them diagonally in adjacent rows, and consideration on using higher flow rate emitters to manage additional heat load on fruits. Project data suggest that FST threshold ranges between 86 and 95 °F (cv. Honeycrisp) would be the starting point to actuate automated fogging systems.
Similar to prior findings, netting treatments seemed to trap heat in air (and fruit) for extended hours lingering into the evenings and had delayed fruit color development. Fognet has higher installation costs, almost two times to fogging and conventional with comparable heat stress mitigation performance. In terms of mitigation techniques effects on cv. Honeycrisp fruit quality, control treatment consistently showed the highest incidence of sunburn. Conventional, fogging, fognet, and netting significantly reduced sunburn, but each had distinct effects on the fruit quality. Netting led to small sized fruits. Post-harvest storage analysis revealed that in the 2022 season, netting-treated fruits had significantly lower losses due to bitter pit and soft scald disorders, unlike in 2021 season. Variations in fruit growth progression between treatments and seasons were also observed, with average fruit size being higher in 2021 season. Overall, adoption of these mitigation techniques should be considered in relation to factors such as crop load, tree vigor, and fruit size, especially for the Honeycrisp variety.
In contrast, the impact of heat stress was minimal on WA38 with netting affecting fruit coloration in all three seasons.
Path Forward
For ease of automated heat stress mitigation, the project also focused on developing machine learning based FST estimation models that use weather (in-orchard or open field), and fruit size data as input. Datasets from this project are being used to develop a more comprehensive and robust FST estimation models in collaboration with WSU AgAID Institute. We hope to tie such model(s) with WSU AgWeatherNet station-specific weather forecasts to predict FST for a few days in advance, enabling growers to better plan the mitigation strategies.
Project Report and Additional information
Amogi, B. R. (2023). Edge-intelligence enabled infield sensing system for heat stress mitigation in apple orchards (Doctoral dissertation, Washington State University).
Goosman, N. D., Amogi, B. R., & Khot, L. R., 2024. Apple fruit surface temperature prediction using weather data-driven machine learning models. In 2023 IEEE International Workshop on Metrology for Agriculture and Forestry (MetroAgriFor) (pp. 429-433). IEEE.
Amogi, B. R., Ranjan, R., & Khot, L. R., 2023. Mask R-CNN aided fruit surface temperature monitoring algorithm with edge compute enabled internet of things system for automated apple heat stress management. Information Processing in Agriculture.
Amogi, B. R., Ranjan, R., & Khot, L. R., 2022. Reliable image processing algorithm for sunburn management in green apples. In 2022 IEEE Workshop on Metrology for Agriculture and Forestry (MetroAgriFor) (pp. 186-190). IEEE.
Amogi, B. R., Pukrongta, N., Sallato, B., & Khot, L. R., 2023. Edge Compute Algorithm Enabled Localized Crop Physiology Sensing System for Apple (Malus domestica Borkh.) Crop Water Stress Monitoring. Computers and Electronics in Agriculture. Manuscript Number: COMPAG-D-23-02187. (Under Review)
Amogi, B.R., Ranjan, R., Pukrongta, N., Mogollón M. R., Khot, L.R., Sallato, B.V., Torres, C.A., Peters, R.T., 2022. “Localized sensing data-driven efficacy evaluation of heat stress mitigation techniques in ‘Honeycrisp’ apples. Scientia Horticulturae. Manuscript Number: HORTI43522. (Under Review)
Contact
Lav Khot
Washington State University
lav.khot@wsu.edu
Basavaraj Amogi
Washington State University
basavaraj.amogi@wsu.edu
Bernardita Sallato
Washington State University
b.sallato@wsu.edu
Carolina Torres
Washington State University
ctorres@wsu.edu
Troy Peters
Washington State University
troy_peters@wsu.edu
Funding and acknowledgements
This report is summary of project funded in-parts by the Washington Tree Fruit Research Commission, USDA-NIFA/NSF Cyber-Physical Systems program (grant number: 1837001), and WNP00745. Authors acknowledge grower cooperators and Jain by Rivulis, USA for their in-kind support. We want to thank farm managers and their staff for managing the heat stress mitigation treatments and helping with the harvest. We would like to acknowledge Rakesh Ranjan, Nisit Pukrongta, Oswaldo Gonzalez, Rene Miguel, Juan Munguia, Nelson Goosman (AgAID Institute Intern) and members of WSU PrecisionAg Lab, Sallato lab, and Torress lab for their help in completion of this project.
