AIMC Topic: Plant Roots

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Deep learning-based association analysis of root image data and cucumber yield.

The Plant journal : for cell and molecular biology
The root system is important for the absorption of water and nutrients by plants. Cultivating and selecting a root system architecture (RSA) with good adaptability and ultrahigh productivity have become the primary goals of agricultural improvement. ...

The rhizodynamics robot: Automated imaging system for studying long-term dynamic root growth.

PloS one
The study of plant root growth in real time has been difficult to achieve in an automated, high-throughput, and systematic fashion. Dynamic imaging of plant roots is important in order to discover novel root growth behaviors and to deepen our underst...

Rapid analysis of hydrogen cyanide in fresh cassava roots using NIRSand machine learning algorithms: Meeting end user demand for low cyanogenic cassava.

The plant genome
This study focuses on meeting end-users' demand for cassava (Manihot esculenta Crantz) varieties with low cyanogenic potential (hydrogen cyanide potential [HCN]) by using near-infrared spectrometry (NIRS). This technology provides a fast, accurate, a...

Early Identification of Root Damages Caused by Western Corn Rootworms Using a Minimally Invasive Root Phenotyping Robot-MISIRoot.

Sensors (Basel, Switzerland)
Western corn rootworm (WCR) is one of the most devastating corn rootworm species in North America because of its ability to cause severe production loss and grain quality damage. To control the loss, it is important to identify the infection of WCR a...

Identification of geographical origins of Radix Paeoniae Alba using hyperspectral imaging with deep learning-based fusion approaches.

Food chemistry
The Radix Paeoniae Alba (Baishao) is a traditional Chinese medicine (TCM) with numerous clinical and nutritional benefits. Rapid and accurate identification of the geographical origins of Baishao is crucial for planters, traders and consumers. Hypers...

As good as human experts in detecting plant roots in minirhizotron images but efficient and reproducible: the convolutional neural network "RootDetector".

Scientific reports
Plant roots influence many ecological and biogeochemical processes, such as carbon, water and nutrient cycling. Because of difficult accessibility, knowledge on plant root growth dynamics in field conditions, however, is fragmentary at best. Minirhiz...

Estimation of Greenhouse Lettuce Growth Indices Based on a Two-Stage CNN Using RGB-D Images.

Sensors (Basel, Switzerland)
Growth indices can quantify crop productivity and establish optimal environmental, nutritional, and irrigation control strategies. A convolutional neural network (CNN)-based model is presented for estimating various growth indices (i.e., fresh weight...

Deep-learning-based removal of autofluorescence and fluorescence quantification in plant-colonizing bacteria in vivo.

The New phytologist
Fluorescence microscopy is common in bacteria-plant interaction studies. However, strong autofluorescence from plant tissues impedes in vivo studies on endophytes tagged with fluorescent proteins. To solve this problem, we developed a deep-learning-b...

An insight into the act of iron to impede arsenic toxicity in paddy agro-system.

Journal of environmental management
Surplus research on the widespread arsenic (As) revealed its disturbing role in obstructing the metabolic function of plants. Also, the predilection of As towards rice has been an interesting topic. Contrary to As, iron (Fe) is an essential micronutr...

Deep learning-based quantification of arbuscular mycorrhizal fungi in plant roots.

The New phytologist
Soil fungi establish mutualistic interactions with the roots of most vascular land plants. Arbuscular mycorrhizal (AM) fungi are among the most extensively characterised mycobionts to date. Current approaches to quantifying the extent of root colonis...