AIMC Topic: Oryza

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Instant White Rice with Pigmented Giant Embryonic Rice Improves Glucose Metabolism and Inhibits Oxidative Stress in High-Fat Diet-Fed Mice.

International journal for vitamin and nutrition research. Internationale Zeitschrift fur Vitamin- und Ernahrungsforschung. Journal international de vitaminologie et de nutrition
The effects of instant cooked rice made from a combination of white rice and pigmented giant embryonic Keunnunjami rice, in comparison with those of instant regular white or brown rice and instant non-pigmented giant embryonic brown rice, on the gluc...

Fully convolutional network for rice seedling and weed image segmentation at the seedling stage in paddy fields.

PloS one
To reduce the cost of production and the pollution of the environment that is due to the overapplication of herbicide in paddy fields, the location information of rice seedlings and weeds must be detected in site-specific weed management (SSWM). With...

A directed learning strategy integrating multiple omic data improves genomic prediction.

Plant biotechnology journal
Genomic prediction (GP) aims to construct a statistical model for predicting phenotypes using genome-wide markers and is a promising strategy for accelerating molecular plant breeding. However, current progress of phenotype prediction using genomic d...

Identification of optimal prediction models using multi-omic data for selecting hybrid rice.

Heredity
Genomic prediction benefits hybrid rice breeding by increasing selection intensity and accelerating breeding cycles. With the rapid advancement of technology, other omic data, such as metabolomic data and transcriptomic data, are readily available fo...

Rice Blast Disease Recognition Using a Deep Convolutional Neural Network.

Scientific reports
Rice disease recognition is crucial in automated rice disease diagnosis systems. At present, deep convolutional neural network (CNN) is generally considered the state-of-the-art solution in image recognition. In this paper, we propose a novel rice bl...

Fuzzy controller based E-nose classification of Sitophilus oryzae infestation in stored rice grain.

Food chemistry
Fuzzy controller artmap based algorithms via E-nose selective metal oxides sensor (MOS) data was applied for classification of S. oryzae infestation in rice grains. The screened defuzzified data of selective sensors was further applied to detect S. o...

Deep learning for DNase I hypersensitive sites identification.

BMC genomics
BACKGROUND: The DNase I hypersensitive sites (DHSs) are associated with the cis-regulatory DNA elements. An efficient method of identifying DHSs can enhance the understanding on the accessibility of chromatin. Despite a multitude of resources availab...

PENYEK: Automated brown planthopper detection from imperfect sticky pad images using deep convolutional neural network.

PloS one
Rice is a staple food in Asia and it contributes significantly to the Gross Domestic Product (GDP) of Malaysia and other developing countries. Brown Planthopper (BPH) causes high levels of economic loss in Malaysia. Identification of BPH presence and...

A novel nanobody and mimotope based immunoassay for rapid analysis of aflatoxin B1.

Talanta
Mimotopes could replace mycotoxins and their conjugates to develop immunoassay methods. The mimotopes obtained by phage display technology were mainly using monoclonal antibodies or polyclonal antibodies as targets. However, the mimotope of recombina...

A novel method for predicting cadmium concentration in rice grain using genetic algorithm and back-propagation neural network based on soil properties.

Environmental science and pollution research international
Heavy metal pollution is a global ecological safety issue, especially in crops, where it directly threatens regional ecological security and human health. In this study, the back-propagation (BP) neural network optimized by the genetic algorithm (GA)...