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Development of an Open-Source Thermal Image Processing Software for Improving Irrigation Management in Potato Crops (Solanum tuberosum L.)

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

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摘要

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 ( = 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 ), allowing a total water saving of 341.6 ± 63.65 and 515.7 ± 37.73 m ha 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.
机译:必须精确确定植物水的状态,以优化灌溉计划,从而最大化产量。红外热成像(IRT)可以用作检测气孔关闭的替代指标,以测量植物水分胁迫。在这项研究中,开发了一种开源软件(热图像处理器(TIPCIP)),该软件包括诸如热可见图像分割和形态学操作之类的图像处理技术,以估算马铃薯作物的作物水分胁迫指数(CWSI)。将结果与热电偶的CWSI进行了比较,发现相关性很高(= 0.84)。为了评估该软件的有效性,实施了两个实验。基于TIPCIP的冠层温度用于估算潮湿环境中整个生长季节的CWSI。根据CWSI阈值建立了两种灌溉时间不同的处理方法:0.4(T2)和0.7(T3),并与对照(T1,当土壤水分达到田间持水量的70%时进行灌溉)进行了比较。结果,T2没有显示出新鲜块茎产量的显着降低(34.5±3.72和44.3±2.66 t ha),在第一个和第二个实验中,总节水分别为341.6±63.65和515.7±37.73 m ha。这些发现鼓励通过启动实验来自动使用CWSI进行精确灌溉,无论是在大型环境中使用无人机,还是通过对TIPCIP进行处理,以处理来自基于智能手机的IRT传感器的数据,以用于小规模农户。

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