Prediction of Leaf Break Resistance of Green and Dry Alfalfa Leaves by Machine Learning Methods

Ercan, Uğur; Kabas, Onder; Moiceanu, Georgiana

doi:10.3390/app14041638

Cited by 3 publications

(1 citation statement)

References 56 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The root cause of these problems lies in its drying method. At present, common methods of alfalfa treatment include traditional natural drying and artificial drying [4]. The study conducted by Bambang Suwignyo et al revealed a decline in the quality of alfalfa, irrespective of whether it was naturally dried or subjected to hot air drying [5].…”

Section: Introductionmentioning

confidence: 99%

Influence of High-Voltage Corona Discharge on Drying Kinetics and Physicochemical Properties of Alfalfa at Various Air-Gap Spacings

Guo,

Qian,

Yuan

et al. 2024

Agronomy

View full text Add to dashboard Cite

The high nutritional value of alfalfa hay makes it a widely utilized component in animal feed. However, the current prevalent drying methods for forage have a significantly detrimental impact on the quality of alfalfa during the drying process. This study investigates the effects of high-voltage corona discharge (HVCD) treatment on post-cut alfalfa. Gradient experiments are conducted by adjusting the air-gap spacing at a voltage of 25 kV. The results demonstrate that as the distance decreases, there is an observed increase in the drying rate, rehydration rate, and color intensity of the HVCD-treated material. HVCD treatment significantly enhances crude protein content, which increases with decreasing air-gap spacing. Meanwhile, it negatively affects lignin, neutral detergent fiber (NDF), and acid detergent fiber (ADF) levels. The relative forage quality (RFQ) of alfalfa reaches its peak at an air-gap spacing of 7 cm. The application of HVCD disrupts the fiber structure and induces significant electroporation effects in cells. Minimal changes in functional groups preserve nutrient integrity. Furthermore, HVCD exhibits lower energy consumption compared to hot air dryers. The HVCD treatment is a highly efficient and effective method, with a gradual improvement in alfalfa hay quality as the air-gap distance decreases.

show abstract

Section: Introductionmentioning

confidence: 99%

Influence of High-Voltage Corona Discharge on Drying Kinetics and Physicochemical Properties of Alfalfa at Various Air-Gap Spacings

Guo,

Qian,

Yuan

et al. 2024

Agronomy

View full text Add to dashboard Cite

show abstract

Critical Drop Height Prediction of Loquat Fruit Based on Some Engineering Properties with Machine Learning Approach

Kabas,

Ercan,

Moiceanu

2024

Agronomy

View full text Add to dashboard Cite

The lowest height at which a product can fall without suffering severe harm is known as the “critical drop height” for agricultural products. It is a crucial factor to take into account for crops like loquats that are prone to bruising or damage upon impact. By establishing the minimum altitude at which the product can be dropped without experiencing substantial harm, suitable processing procedures may be established from harvest to the end consumer, thereby preserving product quality and worth. The critical drop height can be ascertained through swift, affordable, non-destructive, and non-traditional methods, rather than time-consuming and expensive laboratory trials. In the study, we aimed to estimate the critical drop height for loquat fruit using machine learning methods. Three different machine learning methods with different operating principles were applied. R2, MAE, RMSE, and MAPE metrics were used to assess the models. There were no obvious differences in both the comparisons within the models, namely the training and test results and the mutual comparisons of the models. However, with a slight difference, the SVMs model performed better in the training data set, and the ETs model performed better in the test data set. Plots were drawn to visualize model performances, and the results obtained from the plots and metrics support each other.

show abstract

Predicting High Technology Exports of Countries for Sustainable Economic Growth by Using Machine Learning Techniques: The Case of Turkey

Gulzar,

Oral,

Kayakus

et al. 2024

Sustainability

View full text Add to dashboard Cite

In this study, the estimation of high-tech exports for Turkey’s foreign trade target in line with sustainable development was carried out. The research was carried out for Turkey since it has been focusing on sustainable and environmentally friendly production and an export-oriented growth model, with a transformation in its economic growth strategy as of 2021, and high-tech products are a determining factor in the export target. In this research, three different machine learning techniques, namely artificial neural networks, logistic regression, and support vector regression, were used to determine a successful prediction method close to the ideal scenario. In the models, high technology exports for the period of 2007–2023 with data obtained from the World Bank were taken as the dependent variable, while the gross national product, number of patents, and research and development expenditures were taken as independent variables. By calculating the R2, MAPE, and MSE metrics, the success of the model with the least error was evaluated, and it was seen that artificial neural networks (ANNs) were the most successful model, with values of 94.2%, 0.011, and 0.073, respectively. The ANN model was followed by support regression and logistic regression.

show abstract

Prediction of Leaf Break Resistance of Green and Dry Alfalfa Leaves by Machine Learning Methods

Cited by 3 publications

References 56 publications

Influence of High-Voltage Corona Discharge on Drying Kinetics and Physicochemical Properties of Alfalfa at Various Air-Gap Spacings

Influence of High-Voltage Corona Discharge on Drying Kinetics and Physicochemical Properties of Alfalfa at Various Air-Gap Spacings

Critical Drop Height Prediction of Loquat Fruit Based on Some Engineering Properties with Machine Learning Approach

Predicting High Technology Exports of Countries for Sustainable Economic Growth by Using Machine Learning Techniques: The Case of Turkey

Contact Info

Product

Resources

About