Investigating lodging in spearmint with overhead sprinklers compared to drag hoses using entropy values from low altitude RGB-imagery
INFORMATION PROCESSING IN AGRICULTURE(2022)
摘要
Lodging occurs when the crop canopy is too heavy for the strength of the stem and it falls over onto the ground. This decreases crop yield and quality, and it makes harvest difficult. A research experiment was set up in a spearmint field on a center pivot with mid elevation spray application (MESA) overhead sprinklers, where the water was applied from a "mid elevation" of 2 m above the ground level (AGL), and low elevation precision application (LEPA) sprinklers, where the water was emitted directly onto the soil surface through drag hoses without wetting the crop canopy. Every-other span of this full-size center pivot was configured with MESA and LEPA sprinklers alternatively. In 2018, imagery was collected with an unmanned aerial vehicle (UAV) from a cross section of this field. In 2019, a cross section was again collected, but in addition UAV imagery was collected from marked lodged and un-lodged areas of the field to validate the lodging detection method. These UAV-based imagery data were captured with a ground sample distance (GSD) of 0.03 m. This research introduces using the texture feature, which is based on image entropy, was used to evaluate the degree of lodging. The results from 2018 showed that the average entropy of the grayscale image from LEPA (5.5 (mean) +/- 0.27 (standard deviation)) was significantly (P < 0.0001) greater than the average entropy (5.0 +/- 0.25) of MESA. Also, the entropy value extracted from the images in 2019 from the marked un-lodged locations were significantly higher compared to that of the lodged areas. Overall, the LEPA irrigation treatment was significantly less lodged compared to MESA. Moreover, the entropy value, or texture feature, is a viable method for estimating lodging using low altitude RGB imagery.
更多查看译文
关键词
Lodging,Spearmint,Entropy value,Texture feature,LEPA and MESA irrigation systems
AI 理解论文
溯源树
样例
![](https://originalfileserver.aminer.cn/sys/aminer/pubs/mrt_preview.jpeg)
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要