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High-throughput phenotyping with deep learning gives insight into the genetic architecture of flowering time in wheat.

GigaScience
BACKGROUND: Measurement of plant traits with precision and speed on large populations has emerged as a critical bottleneck in connecting genotype to phenotype in genetics and breeding. This bottleneck limits advancements in understanding plant genome...

Applications of Machine Learning Methods to Genomic Selection in Breeding Wheat for Rust Resistance.

The plant genome
New methods and algorithms are being developed for predicting untested phenotypes in schemes commonly used in genomic selection (GS). The prediction of disease resistance in GS has its own peculiarities: a) there is consensus about the additive natur...

Use of in vitro dry matter digestibility and gas production to predict apparent total tract digestibility of total dietary fiber for growing pigs.

Journal of animal science
In vitro DM disappearance (IVDMD) and gas production methods have been developed and used to measure in vivo nutrient digestibility of feed ingredients, but further validation is needed for ingredients containing high concentrations of insoluble fibe...

Cinnamic acid and fish flour affect wheat phenolic acids and flavonoid compounds, lipid peroxidation, proline levels under salt stress.

Acta biologica Hungarica
To elucidate the physiological mechanism of salt stress mitigated by cinnamic acid (CA) and fish flour (FF) pretreatment, wheat was pretreated with 20, 50 and 100 ppm CA and 1 g/10 mL FF for 2 d and was then cultivated. We investigated whether exogen...

Combining semi-automated image analysis techniques with machine learning algorithms to accelerate large-scale genetic studies.

GigaScience
Genetic analyses of plant root systems require large datasets of extracted architectural traits. To quantify such traits from images of root systems, researchers often have to choose between automated tools (that are prone to error and extract only a...

Deep machine learning provides state-of-the-art performance in image-based plant phenotyping.

GigaScience
In plant phenotyping, it has become important to be able to measure many features on large image sets in order to aid genetic discovery. The size of the datasets, now often captured robotically, often precludes manual inspection, hence the motivation...

[Estimation of Winter Wheat Biomass Using Visible Spectral and BP Based Artificial Neural Networks].

Guang pu xue yu guang pu fen xi = Guang pu
The objective of this study was to evaluate the feasibility of using color digital image analysis and back propagation (BP) based artificial neural networks (ANN) method to estimate above ground biomass at the canopy level of winter wheat field. Digi...