Machine learning for plant breeding and biotechnology
M Niazian, G Niedbała - Agriculture, 2020 - mdpi.com
Classical univariate and multivariate statistics are the most common methods used for data
analysis in plant breeding and biotechnology studies. Evaluation of genetic diversity …
analysis in plant breeding and biotechnology studies. Evaluation of genetic diversity …
Prediction of loquat soluble solids and titratable acid content using fruit mineral elements by artificial neural network and multiple linear regression
Mineral nutrient elements have an important impact on fruit quality, especially on soluble
solids (SSC), titratable acid content (TAC) and the ratio of soluble solids to titratable acid …
solids (SSC), titratable acid content (TAC) and the ratio of soluble solids to titratable acid …
Building energy performance forecasting: A multiple linear regression approach
Different ways to evaluate the building energy balance can be found in literature, including
comprehensive techniques, statistical and machine-learning methods and hybrid …
comprehensive techniques, statistical and machine-learning methods and hybrid …
Artificial neural network modeling of novel coronavirus (COVID-19) incidence rates across the continental United States
Prediction of the COVID-19 incidence rate is a matter of global importance, particularly in the
United States. As of 4 June 2020, more than 1.8 million confirmed cases and over 108 …
United States. As of 4 June 2020, more than 1.8 million confirmed cases and over 108 …
The application of multiple linear regression and artificial neural network models for yield prediction of very early potato cultivars before harvest
Yield forecasting is a rational and scientific way of predicting future occurrences in
agriculture—the level of production effects. Its main purpose is reducing the risk in the …
agriculture—the level of production effects. Its main purpose is reducing the risk in the …
Prediction of total soluble solids and pH of strawberry fruits using RGB, HSV and HSL colour spaces and machine learning models
Determination of internal qualities such as total soluble solids (TSS) and pH is a paramount
concern in strawberry cultivation. Therefore, the main objective of the current study was to …
concern in strawberry cultivation. Therefore, the main objective of the current study was to …
Performance analysis of deep learning CNN models for variety classification in hazelnut
In evaluating agricultural products, knowing the specific product varieties is important for the
producer, the industrialist, and the consumer. Human labor is widely used in the …
producer, the industrialist, and the consumer. Human labor is widely used in the …
Integrating speed breeding with artificial intelligence for developing climate-smart crops
KK Rai - Molecular biology reports, 2022 - Springer
Introduction In climate change, breeding crop plants with improved productivity,
sustainability, and adaptability has become a daunting challenge to ensure global food …
sustainability, and adaptability has become a daunting challenge to ensure global food …
Application of artificial neural network for predicting maize production in South Africa
The use of crop modeling as a decision tool by farmers and other decision-makers in the
agricultural sector to improve production efficiency has been on the increase. In this study …
agricultural sector to improve production efficiency has been on the increase. In this study …
Prediction of sunflower grain yield under normal and salinity stress by RBF, MLP and, CNN models
S Khalifani, R Darvishzadeh, N Azad… - Industrial Crops and …, 2022 - Elsevier
Sunflower is one of the most valuable oilseeds in the world due to its high-quality oil and
wide adaptation to climatic and soil conditions. Salinity is one of the most harmful …
wide adaptation to climatic and soil conditions. Salinity is one of the most harmful …