College of Information Science and Technology, Hebei Agricultural University, Baoding 071001, China.
Department of Biological Systems Engineering, Center for Precision and Automated Agricultural Systems, Washington State University, Prosser, WA 99350, USA.
Sensors (Basel). 2020 Jan 22;20(3):608. doi: 10.3390/s20030608.
Heat stress and resulting sunburn is a major abiotic stress in perineal specialty crops. For example, such stress to the maturing fruits on apple tree canopies can cause several physiological disorders that result in considerable crop losses and reduced marketability of the produce. Thus, there is a critical technological need to effectively monitor the abiotic stress under field conditions for timely actuation of remedial measures. Fruit surface temperature (FST) is one of the stress indicators that can reliably be used to predict apple fruit sunburn susceptibility. This study was therefore focused on development and in-field testing of a mobile FST monitoring tool that can be used for real-time crop stress monitoring. The tool integrates a smartphone connected thermal-Red-Green-Blue (RGB) imaging sensor and a custom developed application ('AppSense 1.0') for apple fruit sunburn prediction. This tool is configured to acquire and analyze imagery data onboard the smartphone to estimate FST. The tool also utilizes geolocation-specific weather data to estimate weather-based FST using an energy balance modeling approach. The 'AppSense 1.0' application, developed to work in the Android operating system, allows visual display, annotation and real-time sharing of the imagery, weather data and pertinent FST estimates. The developed tool was evaluated in orchard conditions during the 2019 crop production season on the Gala, Fuji, Red delicious and Honeycrisp apple cultivars. Overall, results showed no significant difference (t = 0.51, p = 0.6) between the mobile FST monitoring tool outputs, and ground truth FST data collected using a thermal probe which had accuracy of ±0.4 °C. Upon further refinements, such tool could aid growers in real-time apple fruit sunburn susceptibility prediction and assist in more effective actuation of apple fruit sunburn preventative measures. This tool also has the potential to be customized for in-field monitoring of the heat stressors in some of the sun-exposed perennial and annual specialty crops at produce maturation.
热应激和由此导致的晒伤是特用作物会阴区的主要非生物胁迫因素。例如，这种胁迫会对苹果树冠上成熟的果实造成几种生理障碍，导致大量作物损失和降低产品的市场适销性。因此，迫切需要有效地监测田间条件下的非生物胁迫，以便及时采取补救措施。果实表面温度 (FST) 是一种可靠的应激指标，可用于预测苹果果实晒伤易感性。因此，本研究集中于开发和现场测试一种移动 FST 监测工具，该工具可用于实时作物胁迫监测。该工具集成了连接智能手机的热红-绿-蓝 (RGB) 成像传感器和一个自定义开发的应用程序 ('AppSense 1.0'），用于预测苹果果实晒伤。该工具配置为在智能手机上获取和分析图像数据，以估计 FST。该工具还利用特定地理位置的天气数据，通过能量平衡建模方法估算基于天气的 FST。开发的工具在 2019 年作物生产季节的果园条件下进行了评估，用于 Gala、富士、红元帅和蜂蜜脆苹果品种。总体而言，结果表明，移动 FST 监测工具的输出与使用热敏探头收集的地面真实 FST 数据之间没有显著差异（t = 0.51，p = 0.6），热敏探头的精度为 ±0.4°C。经过进一步改进，这种工具可以帮助种植者实时预测苹果果实晒伤易感性，并协助更有效地采取苹果果实晒伤预防措施。该工具还有潜力定制为在一些特用作物的生产成熟期间，对暴露在阳光下的多年生和一年生特用作物的热应激因子进行现场监测。
