AIMC Topic: Malus

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Comparing visible and near infrared 'point' spectroscopy and hyperspectral imaging techniques to visualize the variability of apple firmness.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
In this work, visible and near-infrared 'point' (Vis-NIR) spectroscopy and hyperspectral imaging (Vis-NIR-HSI) techniques were applied on three different apple cultivars to compare their firmness prediction performances based on a large intra-variabi...

Real-Time Prediction of Growth Characteristics for Individual Fruits Using Deep Learning.

Sensors (Basel, Switzerland)
Understanding the growth status of fruits can enable precise growth management and improve the product quality. Previous studies have rarely used deep learning to observe changes over time, and manual annotation is required to detect hidden regions o...

Design of Electronic Nose Detection System for Apple Quality Grading Based on Computational Fluid Dynamics Simulation and K-Nearest Neighbor Support Vector Machine.

Sensors (Basel, Switzerland)
Apples are one of the most widely planted fruits in the world, with an extremely high annual production. Several issues should be addressed to avoid the damaging of samples during the quality grading process of apples (e.g., the long detection period...

A method of detecting apple leaf diseases based on improved convolutional neural network.

PloS one
Apple tree diseases have perplexed orchard farmers for several years. At present, numerous studies have investigated deep learning for fruit and vegetable crop disease detection. Because of the complexity and variety of apple leaf veins and the diffi...

Hybrid neural network modeling and particle swarm optimization for improved ethanol production from cashew apple juice.

Bioprocess and biosystems engineering
A hybrid neural model (HNM) and particle swarm optimization (PSO) was used to optimize ethanol production by a flocculating yeast, grown on cashew apple juice. HNM was obtained by combining artificial neural network (ANN), which predicted reaction sp...

Apple Leaf Diseases Recognition Based on An Improved Convolutional Neural Network.

Sensors (Basel, Switzerland)
Scab, frogeye spot, and cedar rust are three common types of apple leaf diseases, and the rapid diagnosis and accurate identification of them play an important role in the development of apple production. In this work, an improved model based on VGG1...

Plant protection product dose rate estimation in apple orchards using a fuzzy logic system.

PloS one
In the process of applying a plant protection product mixed with water (spray mixture) at the prescribed concentration with conventional sprayers for chemical protection of tree canopies in an orchard, standard models are used to express the dose rat...

Automatic Image-Based Plant Disease Severity Estimation Using Deep Learning.

Computational intelligence and neuroscience
Automatic and accurate estimation of disease severity is essential for food security, disease management, and yield loss prediction. Deep learning, the latest breakthrough in computer vision, is promising for fine-grained disease severity classificat...

Quality stability and sensory attributes of apple juice processed by thermosonication, pulsed electric field and thermal processing.

Food science and technology international = Ciencia y tecnologia de los alimentos internacional
Worldwide, apple juice is the second most popular juice, after orange juice. It is susceptible to enzymatic browning spoilage by polyphenoloxidase, an endogenous enzyme. In this study, Royal Gala apple juice was treated by thermosonication (TS: 1.3 W...

Simultaneous determination of glucose, fructose, sucrose and sorbitol in the leaf and fruit peel of different apple cultivars by the HPLC-RI optimized method.

Food chemistry
A high performance liquid chromatography method with refractive index detection (HPLC-RI), for simultaneous determination of glucose, fructose, sucrose and sorbitol in leaf and/or apple peel samples from nine apple (Malus domestica Borkh.) cultivars ...