Accurate determination of plant water status is mandatory to optimize irrigation scheduling and thus maximize yield. Infrared thermography (IRT) can be used as a proxy for detecting stomatal closure as a measure of plant water stress. In this study, an open-source software (Thermal Image Processor (TIPCIP)) that includes image processing techniques such as thermal-visible image segmentation and morphological operations was developed to estimate the crop water stress index (CWSI) in potato crops. Results were compared to the CWSI derived from thermocouples where a high correlation was found ( r P e a r s o n = 0.84). To evaluate the effectiveness of the software, two experiments were implemented. TIPCIP-based canopy temperature was used to estimate CWSI throughout the growing season, in a humid environment. Two treatments with different irrigation timings were established based on CWSI thresholds: 0.4 (T2) and 0.7 (T3), and compared against a control (T1, irrigated when soil moisture achieved 70% of field capacity). As a result, T2 showed no significant reduction in fresh tuber yield (34.5 ± 3.72 and 44.3 ± 2.66 t ha - 1 ), allowing a total water saving of 341.6 ± 63.65 and 515.7 ± 37.73 m 3 ha - 1 in the first and second experiment, respectively. The findings have encouraged the initiation of experiments to automate the use of the CWSI for precision irrigation using either UAVs in large settings or by adapting TIPCIP to process data from smartphone-based IRT sensors for applications in smallholder settings.

中文翻译：

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开发用于改善马铃薯作物（Solanum tuberosum L.）灌溉管理的开源热图像处理软件。


准确确定植物水分状况对于优化灌溉计划并从而最大限度地提高产量至关重要。红外热成像 (IRT) 可用作检测气孔关闭的代理，作为衡量植物水分胁迫的指标。在本研究中，开发了一种开源软件（热图像处理器（TIPCIP）），其中包括热可见光图像分割和形态学操作等图像处理技术，用于估计马铃薯作物的水分胁迫指数（CWSI）。将结果与源自热电偶的 CWSI 进行比较，发现具有高度相关性 (r Pearson = 0.84)。为了评估该软件的有效性，进行了两个实验。基于 TIPCIP 的冠层温度用于估计潮湿环境中整个生长季节的 CWSI。根据 CWSI 阈值：0.4（T2）和 0.7（T3），建立了两种不同灌溉时间的处理，并与对照（T1，当土壤湿度达到田间持水量的 70% 时进行灌溉）进行比较。结果，T2 鲜块茎产量没有显着下降（34.5 ± 3.72 和 44.3 ± 2.66 t ha - 1 ），第一和第二期总共节水量为 341.6 ± 63.65 和 515.7 ± 37.73 m 3 ha - 1分别进行实验。研究结果鼓励启动实验，以在大型环境中使用无人机自动使用 CWSI 进行精确灌溉，或者通过调整 TIPCIP 来处理来自基于智能手机的 IRT 传感器的数据，以应用于小农环境。