AIMC Topic: Seeds

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Research on variety identification of common bean seeds based on hyperspectral and deep learning.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Accurate, fast and non-destructive identification of varieties of common bean seeds is important for the cultivation and efficient utilization of common beans. This study is based on hyperspectral and deep learning to identify the varieties of common...

Effect of ethanol extract of nigella sativa L seeds and propofol on BDNF protein level as neuroplasticity and neuroprotection of traumatic brain injury in rats.

F1000Research
BACKGROUND: Traumatic brain injury (TBI) is a change in brain function or evidence of brain pathology caused by external mechanical forces. Brain Derived Neurotrophic Factor (BDNF) is a neurotropin that functions as a neuron protective. Nigella sativ...

Machine learning approach for high-throughput phenolic antioxidant screening in black Rice germplasm collection based on surface FTIR.

Food chemistry
Pigmented rice contains beneficial phenolic antioxidants but analysing them across germplasm collections is laborious and time-consuming. Here we utilised rapid surface Fourier transform infrared (FTIR) spectroscopy and machine learning algorithms (M...

Analyzing Medicago spp. seed morphology using GWAS and machine learning.

Scientific reports
Alfalfa is widely recognized as an important forage crop. To understand the morphological characteristics and genetic basis of seed morphology in alfalfa, we screened 318 Medicago spp., including 244 Medicago sativa subsp. sativa (alfalfa) and 23 oth...

Using VIS-NIR hyperspectral imaging and deep learning for non-destructive high-throughput quantification and visualization of nutrients in wheat grains.

Food chemistry
High-throughput and low-cost quantification of the nutrient content in crop grains is crucial for food processing and nutritional research. However, traditional methods are time-consuming and destructive. A high-throughput and low-cost method of quan...

A novel method combining deep learning with the Kennard-Stone algorithm for training dataset selection for image-based rice seed variety identification.

Journal of the science of food and agriculture
BACKGROUND: Different varieties of rice vary in planting time, stress resistance, and other characteristics. With advances in rice-breeding technology, the number of rice varieties has increased significantly, making variety identification crucial fo...

Rapid and nondestructive watermelon (Citrullus lanatus) seed viability detection based on visible near-infrared hyperspectral imaging technology and machine learning algorithms.

Journal of food science
The improper storage of seeds can potentially compromise agricultural productivity, leading to reduced crop yields. Therefore, assessing seed viability before sowing is of paramount importance. Although numerous techniques exist for evaluating seed c...

Application of artificial neural networks to classify Avena fatua and Avena sterilis based on seed traits: insights from European Avena populations primarily from the Balkan Region.

BMC plant biology
BACKGROUND: Avena fatua and A. sterilis are challenging to distinguish due to their strong similarities. However, Artificial Neural Networks (ANN) can effectively extract patterns and identify these species. We measured seed traits of Avena species f...

Discrimination of internal crack for rice seeds using near infrared spectroscopy.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
It is an important thing to identify internal crack in seeds from normal seeds for evaluating the quality of rice seeds (Oryza sativa L.). In this study, non-destructive discrimination of internal crack in rice seeds using near infrared spectroscopy ...

The use of image analysis to study the effect of moisture content on the physical properties of grains.

Scientific reports
Designing machines and equipment for post-harvest operations of agricultural products requires information about their physical properties. The aim of the work was to evaluate the possibility of introducing a new approach to predict the moisture cont...