AIMC Topic: Fruit

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Evaluation of conditional treatment effect of salt stress on tomato sugar content using causal machine learning: A pilot study.

PloS one
Exposing tomatoes to salt stress has been reported to increase the fruit sugar content (°Brix); however, the causal impact of this treatment under varying environmental conditions remains unclear. In this pilot study, a causal inference analysis was ...

Hybrid quantum neural network models for fruit quality assessment.

PloS one
This study investigates hybrid quantum neural networks for fruit quality assessment, with a focus on the impact of the entangling gate choice. Two architectures were developed: NNQEv1, utilizing controlled-NOT (CNOT) gates, and NNQEv2, employing cont...

Dual-modality fusion for mango disease classification using dynamic attention based ensemble of leaf & fruit images.

Scientific reports
Mango is one of the most beloved fruits and plays an indispensable role in the agricultural economies of many tropical countries like Pakistan, India, and other Southeast Asian countries. Similar to other fruits, mango cultivation is also threatened ...

OptiNet-B3: a lightweight explainable deep learning model for multiclass classification of fruit and leaf diseases.

Scientific reports
Early and accurate detection of diseases is very important for the health of crops and ensuring sustainable agricultural productivity. This paper proposes OptiNet-B3, a novel approach and an efficient deep model for the multiclass classification of f...

Explainable AI-driven interpretation of environmental drivers of tomato fruit expansion in smart greenhouses using IoT sensing.

Scientific reports
Tomato fruit expansion is a key physiological process that determines fruit size, marketability, and yield, yet its quantitative and threshold-based response to microclimatic factors in smart greenhouses has been insufficiently studied. This study de...

Novel transfer learning approach for detecting mango fruit type and quality assessment.

Scientific reports
Mango a widely consumed tropical fruit globally, showcases an extensive array of varieties distinguished by their distinct flavours, textures and appearances. The precise classification and assessment of mango varieties play a pivotal role in ensurin...

Machine learning-assisted aroma profile prediction in tomato puree based on flavoromics.

Food chemistry
Flavor serves as a key quality indicator in tomato puree (TP) processing; however, conventional methods often fall short in providing rapid and accurate assessments. To address this limitation, this study integrated flavoromics with machine learning ...

Multidimensional component quantitative analysis: Exploring commercial mango cultivars in China.

Food chemistry
Different mango cultivars exhibit distinct characteristics in food quality and nutraceutical value, influencing both market potential and consumer preference. We hypothesized that genotype-driven variation in metabolites underpins these quality diffe...

Multi head attention based deep learning framework for waxberry fruit object segmentation from high resolution remote sensing images.

Scientific reports
In some Asian countries, waxberries are special fruit that demand substantial labour for harvesting each season. To ease this burden, automated fruit-picking equipment has seen extensive development over the past decade. However, accurately segmentin...

The apple detection method based on multimodal features.

PloS one
Accurate detection of apples and other fruits in complex environments remains a formidable challenge due to the intricate interplay of varying lighting conditions, occlusions, and background clutter. Traditional detection methods, which primarily rel...