Thermal-RGB imagery and in-field weather sensing derived sweet cherry wetness prediction model

Ranjan, Rakesh; Sinha, Rajeev; Khot, Lav R.; Whiting, Matthew

doi:10.1016/j.scienta.2021.110782

Cited by 10 publications

(3 citation statements)

References 51 publications

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“…Recently, RGB-thermal cameras were applied to monitor fruit skin temperature in sweet cherries (Osroosh and Peters, 2019). On the other hand, (Ranjan et al, 2022) implemented two cultivarspecific wetness prediction models on sweet cherries cv Skeena and Selah. In this work, the authors used a combination of microclimate sensing for weather data, and RGB-thermal camera to obtain thermal images and precise data on the fruit wetness.…”

Section: Precision Farming and Machine Learningmentioning

confidence: 99%

Factors influencing fruit cracking: an environmental and agronomic perspective

La Spada,

Dominguez,

Continella

et al. 2024

Front. Plant Sci.

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Fruit cracking, a widespread physiological disorder affecting various fruit crops and vegetables, has profound implications for fruit quality and marketability. This mini review delves into the multifaceted factors contributing to fruit cracking and emphasizes the pivotal roles of environmental and agronomic factors in its occurrence. Environmental variables such as temperature, relative humidity, and light exposure are explored as determinants factors influencing fruit cracking susceptibility. Furthermore, the significance of mineral nutrition and plant growth regulators in mitigating fruit cracking risk is elucidated, being calcium deficiency identified as a prominent variable in various fruit species. In recent years, precision farming and monitoring systems have emerged as valuable tools for managing environmental factors and optimizing fruit production. By meticulously tracking parameters such as temperature, humidity, soil moisture, and fruit skin temperature, growers can make informed decisions to prevent or alleviate fruit cracking. In conclusion, effective prevention of fruit cracking necessitates a comprehensive approach that encompasses both environmental and agronomic factors.

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Section: Precision Farming and Machine Learningmentioning

confidence: 99%

Factors influencing fruit cracking: an environmental and agronomic perspective

La Spada,

Dominguez,

Continella

et al. 2024

Front. Plant Sci.

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“…In a recently reported study, researchers developed two models for predicting cherry surface humidity based on thermal-RGB images and weather sensing systems ( Ranjan et al., 2022 ). The input data of the first model is weather sensor data, and the input data of the other model combines the fruit surface temperature obtained from thermal image data.…”

Section: Phenotypic Information Acquisition and Related Applications ...mentioning

confidence: 99%

“…The wide applicability of RGB imaging equipment makes the study of phenotypic information based on RGB images a new research hotspot ( Blasco et al., 2017 ). In addition, thermal imaging technology was used in the study of fruit temperature ( Osroosh and Peters, 2019 ; Ranjan et al., 2022 ), and computer tomography technology ( Kritzinger et al., 2017 ; Karmoker et al., 2018 ) and laser backscatter imaging technology ( Adebayo et al., 2016 ; Mozaffari et al., 2022 ) were used in the study of fruit internal quality detection. The phenotypic information acquisition technology based on image technology avoids the measurement error caused by subjective factors in traditional detection methods ( Fu et al., 2020 ), and further improves the accuracy of phenotypic information acquisition.…”

Section: Introductionmentioning

confidence: 99%

A comprehensive review on acquisition of phenotypic information of Prunoideae fruits: Image technology

Huang

et al. 2023

Front. Plant Sci.

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Fruit phenotypic information reflects all the physical, physiological, biochemical characteristics and traits of fruit. Accurate access to phenotypic information is very necessary and meaningful for post-harvest storage, sales and deep processing. The methods of obtaining phenotypic information include traditional manual measurement and damage detection, which are inefficient and destructive. In the field of fruit phenotype research, image technology is increasingly mature, which greatly improves the efficiency of fruit phenotype information acquisition. This review paper mainly reviews the research on phenotypic information of Prunoideae fruit based on three imaging techniques (RGB imaging, hyperspectral imaging, multispectral imaging). Firstly, the classification was carried out according to the image type. On this basis, the review and summary of previous studies were completed from the perspectives of fruit maturity detection, fruit quality classification and fruit disease damage identification. Analysis of the advantages and disadvantages of various types of images in the study, and try to give the next research direction for improvement.

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