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Plant Leaves

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Machine learning improves our knowledge about miRNA functions towards plant abiotic stresses.

Scientific reports
During the last two decades, human has increased his knowledge about the role of miRNAs and their target genes in plant stress response. Biotic and abiotic stresses result in simultaneous tissue-specific up/down-regulation of several miRNAs. In this ...

Disease Classification in Eggplant Using Pre-trained VGG16 and MSVM.

Scientific reports
Currently, the application of deep learning in crop disease classification is one of the active areas of research for which an image dataset is required. Eggplant (Solanum melongena) is one of the important crops, but it is susceptible to serious dis...

Machine learning models for net photosynthetic rate prediction using poplar leaf phenotype data.

PloS one
BACKGROUND: As an essential component in reducing anthropogenic CO2 emissions to the atmosphere, tree planting is the key to keeping carbon dioxide emissions under control. In 1992, the United Nations agreed to take action at the Earth Summit to stab...

Self-Regulating Plant Robots: Bioinspired Heliotropism and Nyctinasty.

Soft robotics
Self-regulation (or so-called homeostasis) is a property of all living organisms to maintain an internal stable state through specialized biofeedback mechanisms under varying external and internal conditions. Although these feedback mechanisms in liv...

Bio-transformation of green tea infusion with tannase and its improvement on adipocyte metabolism.

Enzyme and microbial technology
Catechins in green tea possess various health benefits. Enzymatic treatment improves physiological activities by inducing bioconversion of catechins. Here, we investigated the effect of green tea infusion (GT) after tannase treatment, which transform...

Spectroscopy based novel spectral indices, PCA- and PLSR-coupled machine learning models for salinity stress phenotyping of rice.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Identification and development of salinity tolerant genotypes and varieties are one of the promising ways to improve productivity of salt-affected soils. Alternate methods to achieve this are required as the conventional methods are time-consuming an...

New approach in the characterization of bioactive compounds isolated from Calycotome spinosa (L.) Link leaves by the use of negative electrospray ionization LITMS, LC-ESI-MS/MS, as well as NMR analysis.

Bioorganic chemistry
Two novel compounds were isolated for the first time from Calycotome spinosa (L.) Link, an alkaloid 5-Hydroxy-1H-indole (4) and a cyclitol D-pinitol (5), together with the three well-known flavonoids; Chrysin-7-O-(β-D-glucopyranoside) (1), Chrysin-7-...

Machine Learning Enables High-Throughput Phenotyping for Analyses of the Genetic Architecture of Bulliform Cell Patterning in Maize.

G3 (Bethesda, Md.)
Bulliform cells comprise specialized cell types that develop on the adaxial (upper) surface of grass leaves, and are patterned to form linear rows along the proximodistal axis of the adult leaf blade. Bulliform cell patterning affects leaf angle and ...

Investigating potato late blight physiological differences across potato cultivars with spectroscopy and machine learning.

Plant science : an international journal of experimental plant biology
Understanding plant disease resistance is important in the integrated management of Phytophthora infestans, causal agent of potato late blight. Advanced field-based methods of disease detection that can identify infection before the onset of visual s...

Machine Learning Approaches to Improve Three Basic Plant Phenotyping Tasks Using Three-Dimensional Point Clouds.

Plant physiology
Developing automated methods to efficiently process large volumes of point cloud data remains a challenge for three-dimensional (3D) plant phenotyping applications. Here, we describe the development of machine learning methods to tackle three primary...