Transformations for non-destructive evaluation of brix in mango by reflectance spectroscopy and machine learning
Mango is a very popular climacteric fruit in America and Europe. Among the internal properties of the mango, total soluble solids (TSS) are an adequate indicator to estimate the quality of mango, however, the measurement of this indicator requires destructive tests. Several research have addressed s...
Guardado en:
| Autores principales: | , , , , , |
|---|---|
| Formato: | Artículo |
| Lenguaje: | inglés |
| Publicado: |
2023
|
| Materias: | |
| Acceso en línea: | Descargar el archivo Enlace permanente (DOI o Handle) Enlace permanente (DOI o Handle) |
| Etiquetas: |
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares: Transformations for non-destructive evaluation of brix in mango by reflectance spectroscopy and machine learning
- Feasibility of using spectral profiles for modeling water activity in five varieties of white quinoa grains
- Machine Learning for Credit Risk in the Reactive Peru Program: A Comparison of the Lasso and Ridge Regression Models
- Linear Regression with PM2.5 and PM10 Concentration for Air Quality in East Lima, Peru
- Estimating daily solar radiation in the Argentine Pampas
- Stacking ensemble based hyperparameters to diagnosing of heart disease: Future works
- Multi-step ahead ozone level forecasting using a component-based technique: A case study in Lima, Peru