Full Text Available
Note: Clicking the button above will open the full text document at the original institutional repository in a new window.
Quality Assessment and Predictive Modeling of Chickpea, Lentil and Camelina Yield: Effects of Nitrogen, Irrigation, Rainfed Conditions, and Intercropping Using Machine Learning Approaches
Saved in:
| Published in: | Legume Science |
|---|---|
| Format: | Online Article RSS Article |
| Published: |
2026
|
| Subjects: | |
| Tags: |
No Tags, Be the first to tag this record!
|
Similar Items: Quality Assessment and Predictive Modeling of Chickpea, Lentil and Camelina Yield: Effects of Nitrogen, Irrigation, Rainfed Conditions, and Intercropping Using Machine Learning Approaches
- Effect of chemical and organic fertilisation on yield and macro-micro content of Chickpea (Cicer arietinum L.) cultivars
- Data from an online survey on lentil consumption practices in France in 2022
- Early Planting and Optimized Nitrogen Rate Maximize Biomass Sorghum Yield and Profitability
- Staling Behavior of Chickpea‐Enriched Bread: A Dynamic Mechanical Analysis Approach
- Development of Chickpea‐Based Multigrain Gluten‐Free Crackers: Formulation Optimization and Evaluation of Nutritional, Antioxidant, and Quality Attributes
- Performance assessment of the Devegeçidi irrigation scheme based on irrigation performance indicators under climatic variability (2019–2024)