Towards an automated plant height measurement and tiller segmentation of rice crops using image processing

Plant phenotyping is the process of completely assessing the basic and complex characteristics of the plant, which includes height and tiller count. The International Rice Research Institute (IRRI) researchers does plant phenotyping to observe changes in the physical characteristics of the C4 rice crops after modifying its genetic makeup to increase yields without using too much water, land and fertilizer resources. As this advances, the traditional way of observing phenotypic data is still trailing behind. Automated plant phenotyping offers an effective substitute because it allows a regulated image analysis that can be reproduced due to the automation. This is to address the lack in accuracy, reproducibility and traceability in manual phenotyping. With this, an image processing system that automates the measuring of height and the counting of tillers of a rice crop, specifically the C4 rice, was developed. The system applies HSV and Thresholding for preprocessing, Canny Edge Detection (tiller) and Zhang-Suen Thinning Algorithm (height) for the plant structure and tracing and conversion for measuring the height. Tiller counting is done by counting the cluster of pixels in a given region of interest. Four experiments were conducted using different setups and different combinations of algorithms. The fourth experiment was able to get an average percentage error of 76.14% for the tiller count and 238.11% for the height measurement. Presence of shadows and hanging leaves heavily affected the results of this experiment. © Springer International Publishing AG, part of Springer Nature 2018

Terrestrial 3D laser scanning to track the increase in canopy height of both monocot and dicot crop species under field conditions

BACKGROUND: Plant growth is a good indicator of crop performance and can be measured by different methods and on different spatial and temporal scales. In this study, we measured the canopy height growth of maize (Zea mays), soybean (Glycine max) and wheat (Triticum aestivum) under field conditions by terrestrial laser scanning (TLS). We tested the hypotheses whether such measurements are capable to elucidate (1) differences in architecture that exist between genotypes; (2) genotypic differences between canopy height growth during the season and (3) short-term growth fluctuations (within 24 h), which could e.g. indicate responses to rapidly fluctuating environmental conditions. The canopies were scanned with a commercially available 3D laser scanner and canopy height growth over time was analyzed with a novel and simple approach using spherical targets with fixed positions during the whole season. This way, a high precision of the measurement was obtained allowing for comparison of canopy parameters (e.g. canopy height growth) at subsequent time points. RESULTS: Three filtering approaches for canopy height calculation from TLS were evaluated and the most suitable approach was used for the subsequent analyses. For wheat, high coefficients of determination (R(2)) of the linear regression between manually measured and TLS-derived canopy height were achieved. The temporal resolution that can be achieved with our approach depends on the scanned crop. For maize, a temporal resolution of several hours can be achieved, whereas soybean is ideally scanned only once per day, after leaves have reached their most horizontal orientation. Additionally, we could show for maize that plant architectural traits are potentially detectable with our method. CONCLUSIONS: The TLS approach presented here allows for measuring canopy height growth of different crops under field conditions with a high temporal resolution, depending on crop species. This method will enable advances in automated phenotyping for breeding and precision agriculture applications. In future studies, the TLS method can be readily applied to detect the effects of plant stresses such as drought, limited nutrient availability or compacted soil on different genotypes or on spatial variance in fields