An intelligent mushroom strain selection model based on their quality characteristics

J Cervera-Gascó, JE Pardo, M Álvarez-Ortí… - Food Bioscience, 2023 - Elsevier
The great versatility of mushroom production and the significant nutritional and medicinal
properties of the crop make it a highly attractive product that is in continuous expansion …

Predictive Modeling Analysis for the Quality Indicators of Matsutake Mushrooms in Different Transport Environments

Y Wang, X Jin, L Yang, X He, X Wang - Foods, 2023 - mdpi.com
Matsutake mushrooms, known for their high value, present challenges due to their seasonal
availability, difficulties in harvesting, and short shelf life, making it crucial to extend their post …

Edible and poisonous mushrooms classification by machine learning algorithms

K Tutuncu, I Cinar, R Kursun… - 2022 11th Mediterranean …, 2022 - ieeexplore.ieee.org
Of the millions of mushroom species growing all around the world, one type is edible, while
the other is poisonous. It is not easy to distinguish edible and poisonous mushrooms from …

Computer vision and machine learning applied in the mushroom industry: A critical review

H Yin, W Yi, D Hu - Computers and Electronics in Agriculture, 2022 - Elsevier
Background Mushrooms are popular food items containing numerous vitamins, dietary
fibers, and a large number of proteins. As a result, mushrooms can increase the body's …

Progressive quality estimation of oyster mushrooms using neural network–based image analysis

T Sarkar, A Mukherjee, K Chatterjee, S Smaoui… - Quality Assurance and …, 2023 - qascf.com
We have developed an artificial intelligence–based quality prediction model for oyster
mushroom samples in this work. The proposed model tends to predict the progressively …

Performance of the Decision Tree Algorithm in the Classification of Edible and Poisonous Mushrooms with Information Gain Optimization

AR Rudiyanto, P Pujiono, MA Soeleman… - Scientific Journal of …, 2023 - journal.unnes.ac.id
Purpose: This study proposes a new mushroom classification model using a decision tree
algorithm to classify edible and poisonous mushrooms by applying machine learning whose …

Comparative analysis of statistical and supervised learning models for freshness assessment of oyster mushrooms

T Sarkar, A Mukherjee, K Chatterjee, MA Shariati… - Food Analytical …, 2022 - Springer
Automatic assessment of the quality of fruits and vegetables is a growing field of research in
this modern era in order to enable faster processing of good quality foods. In this work, we …

Modelling molecular and inorganic data of Amanita ponderosa mushrooms using artificial neural networks

C Salvador, MR Martins, H Vicente, J Neves… - Agroforestry …, 2013 - Springer
Wild edible mushrooms Amanita ponderosa Malençon and Heim are very appreciated in
gastronomy, with high export potential. This species grows in some microclimates, namely in …

Development of artificial vision system for quality assessment of oyster mushrooms

A Mukherjee, T Sarkar, K Chatterjee, D Lahiri… - Food Analytical …, 2022 - Springer
In this paper, we have illustrated a simple and effective method of assessing the fresh and
deteriorated oyster mushroom samples. Analysis of correlation coefficients is done very …

Efficiency of mushrooms for food production-fundamental strategic decision-making

DC Zied, JE Pardo, R Noble… - Journal of Food …, 2024 - Elsevier
This work seeks to understand the relationships between the proximate composition of the
substrates and the fruiting bodies, and the yield and cultivation time of the main cultivated …