AIMC Topic: Fruit

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Lychee13-3634: A new lychee image dataset and classification methodological evaluation.

PloS one
The rapid and accurate classification of lychee varieties is crucial for improving production efficiency and optimizing market supply. Especially for the main production areas of lychee, efficient lychee classification is more urgent. However, there ...

Grape sugar content prediction with multispectral alignment and improved residual network.

Scientific reports
Sugar content is a crucial indicator of grape ripeness and grading, and developing non-contact and non-destructive sugar content detection devices is essential for grape-picking robots and sorting platforms. Spectroscopy, which can detect the chemica...

Determination of geographical origin of Hovenia dulcis found in Korea and China via inorganic element analysis using inductively coupled plasma spectroscopy and multivariate statistical analysis.

Food chemistry
The fruit of Hovenia dulcis, a popular Korean hangover remedy, is marketed as Korean and Chinese products. To protect domestic producers, ensure accurate labeling, and safeguard consumers, this study discriminated origin through inorganic element ana...

Intelligent pear variety classification models based on Bayesian optimization for deep learning and its interpretability analysis.

Scientific reports
Accurate classification of pear varieties is crucial for enhancing agricultural efficiency and ensuring consumer satisfaction. In this study, Bayesian optimized (BO) deep learning is utilized to identify and classify nine types of pears from 43,200 i...

Phenolic Profile as a Powerful Machine Learning Tool for Identification, Traceability, and Quality Control of Olive Cultivars.

Journal of agricultural and food chemistry
This study investigates the phenolic and fatty acid profiles of olives from four cultivars (Arbequina, Arbosana, Frantene, and Koroneiki), widely grown in the Mediterranean region and collected at different ripening stages in Italy. The aim was to a...

A new framework for evaluating land suitability for Goji (Lycium barbarum L.) cultivation across China.

Journal of environmental management
As a valuable Chinese medicinal herb and functional food, Goji (Lycium barbarum L.) berries have been consumed for more than 4500 years in China and have received extensive international attention. However, stakeholders have adopted traditional manag...

Near-infrared spectroscopy coupled with machine learning algorithms based on L1-norm and L21-norm to identify the geographical origins of Chinese wolfberry.

Food chemistry
The nutritional value of Chinese wolfberry varies depending on different geographical origins, even at the regional level. Therefore, a non-destructive and effective method has important implications for identifying the geographical origins of Chines...

DBA-ViNet: an effective deep learning framework for fruit disease detection and classification using explainable AI.

BMC plant biology
OBJECTIVE: The primary aim of this research is to develop an effective and robust model for identifying and classifying diseases in general fruits, particularly apples, guavas, mangoes, pomegranates, and oranges, utilizing computer vision techniques.

Tomato ripeness prediction using low resolution portable spectrometer and machine learning.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Tomato ripeness assessment is critical to ensure optimal product quality. This study proposes a novel approach to predict total soluble solids (TSS) and firmness, and classify tomato ripeness using a low-resolution AS7265x portable spectrometer combi...

Unraveling the sensory metabolome of blueberries: An integrated metabolomics and machine learning approach across cultivars and geographical origins.

Food chemistry
Consumer-driven blueberry quality improvement requires a deeper understanding of how metabolic composition influences sensory perception. This study integrates untargeted metabolomics and machine learning to identify biomarker metabolites shaping sen...