AIMC Topic: Citrus

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Discrimination of Citri reticulatae pericarpium (CP) and Citrus reticulata 'chachi' (GCP): Focus on HPTLC, UHPLC techniques combined with machine learning and content differences of three specific flavonoids.

Journal of chromatography. A
The global consumption of Citri reticulatae pericarpium (Chenpi, CP) and Citrus reticulata 'chachi' (Guangchenpi, GCP) has been experiencing a steady increase, driven by its extensive applications in healthcare, flavoring, and therapeutic fields. Whi...

Unassailable citrus disease classification via multi-stage deep ensemble learning with vision transformers.

Scientific reports
To reduce losses from agriculture as well as enhance food security, we propose a three-stage deep ensemble for early citrus disease diagnosis from actual-field images of oranges (n = 2,240) as well as lemons (n = 208). To prevent leakage, augmentatio...

LUMIR: an LLM-driven unified agent framework for multi-task infrared spectroscopy reasoning.

Analytica chimica acta
Infrared spectroscopy enables rapid and non-destructive characterization of chemical and material properties, yet effective analysis typically requires workflows involving preprocessing, variable selection, and modeling. The construction and optimiza...

Genetic regulations of citrus flowering: insights towards climatic factors and modern biotechnological approaches.

Planta
The review highlights the intricate relationship between genetic and molecular mechanisms that regulate floral development and responses in citrus under diverse climatic conditions. Citrus, the world's top traded and third most produced fruit crop, h...

A Multi-kernel CNN model with attention mechanism for classification of citrus plants diseases.

Scientific reports
One of the primary challenges leading to a significant reduction in agricultural production is the prevalence of diseases affecting citrus plants. Prevention and monitoring the spread of citrus plant diseases is crucial for maintaining citrus product...

Multiclass semantic segmentation for prime disease detection with severity level identification in Citrus plant leaves.

Scientific reports
Agriculture provides the basics for producing food, driving economic growth, and maintaining environmental sustainability. On the other hand, plant diseases have the potential to reduce crop productivity and raise expenses, posing a risk to food secu...

Flavor characterization of aged Citri Reticulatae Pericarpium from core regions: An integrative approach utilizing GC-IMS, GC-MS, E-nose, E-tongue, and chemometrics.

Food chemistry
This study utilized GC-MS, GC-IMS, E-nose, and E-tongue to analyze the flavor characteristics of Guangchenpi (GCP) from five core producing areas aged 5 to 40 years. Key findings include: W1W, W2S, and W5S sensors in the e-nose and bitter, umami, swe...

Classifying Storage Temperature for Mandarin ( L.) Using Bioimpedance and Diameter Measurements with Machine Learning.

Sensors (Basel, Switzerland)
Mandarin ( L.) is consumed worldwide. Improper storage temperatures cause flavor loss and shorten shelf lives, reducing marketability. Mandarins' quality is difficult to assess visually, as they show no apparent changes during storage. Therefore, a s...

Integrating advanced deep learning techniques for enhanced detection and classification of citrus leaf and fruit diseases.

Scientific reports
In this study, we evaluate the performance of four deep learning models, EfficientNetB0, ResNet50, DenseNet121, and InceptionV3, for the classification of citrus diseases from images. Extensive experiments were conducted on a dataset of 759 images di...

Modelling of pome fruit pollen performance using machine learning.

Scientific reports
Agriculture, particularly fruit production, is considered a crucial industry with a significant economic impact in many countries. Extreme fluctuations in air temperature can negatively affect the flowering periods of fruit species. Therefore, it is ...