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Longitudinal and transverse section of a terminal root. 

Longitudinal and transverse section of a terminal root. 

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Our perception of plants is determined by their visible organs: stem, branches and leaves. The underground parts of a plant are rarely seen; indeed the root system is usually hidden from sight. This is also reflected in science where the interaction between leaves and the atmosphere is much more studied than interactions between roots and soil. One...

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... anatomical characteristics are fundamental to understanding how roots grow ( Fig. 1) (Eissenstat and Volder, 2005), interact with the soil ( Hitz et al., 2008) and uptake nutrients. The primary root of a plant grows as a branched cylindrical organ into the soil (Evert, 2006;Giehl et al., 2013). Secondary roots develop from the primary root in order to find water and nutrients in the soil. The most external part of ...
Context 2
... conclusion, mycorrhizal fungi are a fundamental plant symbiont, able to alter their species composition not just according to the stages of soil development ( Lambers et al., 2008) but also according to tree age ( Dighton and Mason, 1985;Dighton et al., 1986;Gardes and Bruns, 1996) and health ( Montecchio et al., 2004). Ecological research on mycorrhizae up till now has favoured laboratory and greenhouse stu- dies ( Klironomos and Kendrick, 1993), as opposed to in the field (Bast et al., 2014, 2016). ...

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... Further, studies shows that the root systems of vegetation play a critical role in stabilizing slope failure by enhancing soil shear strength. The magnitude of cohesion depends on root characteristics of tree species such as distribution, tensile strength, interface friction with the soil, and orientation with respect to the principal direction of strain (Vannoppen et al. 2017;Naghdi et al. 2013;Centenaro et al. 2018). Root reinforcement is important on slope stability (Gonzalez-Ollauri and Mickovski 2017; Chirico, et al. 2013). ...
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The investigation of the complicated underground life via automatic technique is in high demand in recent days. Using Convolutional Neural Network (CNN) to detect soil in- vertebrates is an interesting approach, although most studies on the topic have focused on other solutions. The creation of state-of-the-art technique through this work will be a significant step in soil ecology, bio-science and agriculture in effectively exploring the different types of invertebrates, their behaviors and interactions. In this paper, generating and annotating images containing seven classes of invertebrates is firstly presented. Then various automatic detections of the invertebrates using YOLOv5 algorithm on these images are performed and evaluated. Index Terms—Soil fauna, invertebrate detection, small object detection, invertebrate dataset, YOLOv5, cluttered background