# Banana Cultivation and Research

**Type:** Topics  
**Canonical URL:** https://scholariq.org/topics/banana-cultivation-and-research/

## Facts

| Field | Value |
| --- | --- |
| Description | This cluster of papers focuses on the genetics, domestication, cultivation, and challenges faced by bananas, including topics such as Mycosphaerella fijiensis disease, drought tolerance, ensete ventricosum, AFLP markers, phenylphenalenones, and nutrient balance in banana and plantain cultivation. |
| Domain | Life Sciences |
| Field | Agricultural and Biological Sciences |
| OpenAlex ID | t12795 |
| Works | 34 |

## Topic papers all

Showing 15 of 34.

- [TRY plant trait database – enhanced coverage and open access](https://scholariq.org/papers/try-plant-trait-database-enhanced-coverage-and-open-access/)
- [Structure of papain refined at 1.65 Å resolution](https://scholariq.org/papers/structure-of-papain-refined-at-1-65-a-resolution/)
- [Deep Learning for Plant Diseases: Detection and Saliency Map Visualisation](https://scholariq.org/papers/deep-learning-for-plant-diseases-detection-and-saliency-map-visualisation/)
- [Detecting Bakanae disease in rice seedlings by machine vision](https://scholariq.org/papers/detecting-bakanae-disease-in-rice-seedlings-by-machine-vision/)
- [Prediction of Fruit Maturity, Quality, and Its Life Using Deep Learning Algorithms](https://scholariq.org/papers/prediction-of-fruit-maturity-quality-and-its-life-using-deep-learning-algorithms/)
- [Banana Plant Disease Classification Using Hybrid Convolutional Neural Network](https://scholariq.org/papers/banana-plant-disease-classification-using-hybrid-convolutional-neural-network/)
- [RhizoVision Crown: An Integrated Hardware and Software Platform for Root Crown Phenotyping](https://scholariq.org/papers/rhizovision-crown-an-integrated-hardware-and-software-platform-for-root-crown/)
- [Effect of processing on blood glucose and insulin responses to starch in legumes](https://scholariq.org/papers/effect-of-processing-on-blood-glucose-and-insulin-responses-to-starch-in-legumes/)
- [Comparative performance of four CNN-based deep learning variants in detecting Hispa pest, two fungal diseases, and NPK deficiency symptoms of rice (Oryza sativa)](https://scholariq.org/papers/comparative-performance-of-four-cnn-based-deep-learning-variants-in-detecting/)
- [Monitoring the Change Process of Banana Freshness by GoogLeNet](https://scholariq.org/papers/monitoring-the-change-process-of-banana-freshness-by-googlenet/)
- [Deep Learning model of sequential image classifier for crop disease detection in plantain tree cultivation](https://scholariq.org/papers/deep-learning-model-of-sequential-image-classifier-for-crop-disease-detection-in/)
- [A New View of Sooty Blotch and Flyspeck](https://scholariq.org/papers/a-new-view-of-sooty-blotch-and-flyspeck/)
- [Multi-label learning for crop leaf diseases recognition and severity estimation based on convolutional neural networks](https://scholariq.org/papers/multi-label-learning-for-crop-leaf-diseases-recognition-and-severity-estimation/)
- [SLViT: Shuffle-convolution-based lightweight Vision transformer for effective diagnosis of sugarcane leaf diseases](https://scholariq.org/papers/slvit-shuffle-convolution-based-lightweight-vision-transformer-for-effective/)
- [PD-TR: End-to-end plant diseases detection using a transformer](https://scholariq.org/papers/pd-tr-end-to-end-plant-diseases-detection-using-a-transformer/)

## Topic primary papers

- [TRY plant trait database – enhanced coverage and open access](https://scholariq.org/papers/try-plant-trait-database-enhanced-coverage-and-open-access/)
- [The role of Molecular Markers in Improvement of Fruit Crops](https://scholariq.org/papers/the-role-of-molecular-markers-in-improvement-of-fruit-crops/)
- [Pruning Severity in High Density Guava for Higher Returns](https://scholariq.org/papers/pruning-severity-in-high-density-guava-for-higher-returns/)
- [Anti-Ulcer Activities of Methanolic Extract of Musa Paradisiaca](https://scholariq.org/papers/anti-ulcer-activities-of-methanolic-extract-of-musa-paradisiaca/)
- [An Artificial Intelligence-Based System for Detecting Diseases in Apple Tree Branches](https://scholariq.org/papers/an-artificial-intelligence-based-system-for-detecting-diseases-in-apple-tree/)
- [Leveraging Deep Learning for Effective Pest Management in Plantain Tree Cultivation](https://scholariq.org/papers/leveraging-deep-learning-for-effective-pest-management-in-plantain-tree/)
- [Convolutional vision transformer for weed flora classification in banana plantations](https://scholariq.org/papers/convolutional-vision-transformer-for-weed-flora-classification-in-banana/)
- [Advances in Machine Learning and Deep Learning for Automated Banana Disease Detection: A Comprehensive Survey](https://scholariq.org/papers/advances-in-machine-learning-and-deep-learning-for-automated-banana-disease/)
- [Correction: Yue et al. YOLOv7-GCA: A Lightweight and High-Performance Model for Pepper Disease Detection. Agronomy 2024, 14, 618](https://scholariq.org/papers/correction-yue-et-al-yolov7-gca-a-lightweight-and-high-performance-model-for/)

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Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.