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Prediction of Draft Force of a Chisel Cultivator Using Artificial Neural Networks and Its Comparison with Regression Model.
(Agronomy, 2020-02)
In this study, artificial neural networks (ANNs) were used to predict the draft force of a rigid tine chisel cultivator. The factorial experiment based on the randomized complete block design (RCBD) was used to obtain the ...
Non-Destructive Prediction of Titratable Acidity and Taste Index Properties of Gala Apple Using Combination of Different Hybrids ANN and PLSR-Model Based Spectral Data.
(Plants, 2020-12)
Non-destructive estimation of the internal properties of fruits and vegetables is very important, because better management can be provided for subsequent operations. Researchers and scientists around the world are focusing ...
Weed Classification for Site-SpecificWeed Management Using an Automated Stereo Computer-Vision Machine-Learning System in Rice Fields
(Plants, 2020-04)
Site-specific weed management and selective application of herbicides as eco-friendly techniques are still challenging tasks to perform, especially for densely cultivated crops, such as rice. This study is aimed at developing ...
Non-Destructive Estimation of Total Chlorophyll Content of Apple Fruit Based on Color Feature, Spectral Data and the Most EffectiveWavelengths Using Hybrid Artificial Neural Network-Imperialist Competitive Algorithm.
(Plants, 2020-11)
Non-destructive assessment of the physicochemical properties of food products, especially fruits, makes it possible to examine the internal quality without any damage. This is applicable at different stages of fruit growth, ...
Evaluation of the Changes in Thermal, Qualitative, and Antioxidant Properties of Terebinth (Pistacia atlantica) Fruit underDifferentDryingMethods.
(Agronomy, 2020-09)
This study aims to investigate the effect of different drying methods on the thermal, qualitative, and antioxidant properties and pH of terebinth. To perform the experiments in this study, the hot air (HA), infrared (IR), ...