Real-time inspection of fruit by computer vision on a mobile harvesting platform under field conditions

Cubero, Sergio; Moltó, Enrique; Gutierrez, Abelardo; García-Navarrete, Oscar Leonardo; Juste, F.; Blasco, José

doi:10.1556/progress.6.2010.1

Cited by 9 publications

(7 citation statements)

References 7 publications

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“…Fruit size was determined by measuring the outer equatorial diameter (mm) of 50 fruits that were randomly selected from each tree under study using an automatic computer vision inspection system developed by IVIA [38,39]. This vision system consists of one industrial colour camera (Manta G-125C, Allied Vision Technologies GmbH, Germany) located on a line of fruit transport rollers, and a lighting system based on LED strips.…”

Section: Pruning Effect On Citrus Production: Yield and Fruit Sizementioning

confidence: 99%

Mechanical Pruning of ‘Clemenules’ Mandarins in Spain: Yield Effects and Economic Analysis

et al. 2022

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Pruning is one of the most expensive tasks in citrus production, and its mechanization could increase the productivity and competitiveness of citrus farms. The effect of mechanical pruning on yield depends on the variety, crop condition, and location; among other factors. The ‘Clemenules’ mandarin variety is one of the most important ones; therefore, the aim of this work was to study the effects of twelve pruning strategies on ‘Clemenules’ yield over four years, and to conduct an economic analysis. These strategies included fully manual pruning, annual alternation of mechanical/manual pruning, mechanical pruning with manual follow-up, and fully mechanical pruning with different types of cuttings. The results showed that pruning strategies affected the yield and fruit size in some years of the study but not when the four years overall are considered. Strategies that annually alternated mechanical pruning with manual pruning had higher yields than the fully mechanical approaches, and similar yields to the manual and control (no pruning) strategies. Furthermore, although the mechanical pruning costs per hectare were as minimum two times less than those with manual pruning, higher net value was achieved with the manual pruning approach followed by alternate annual mechanical/manual pruning. In conclusion, after four years of study, the pruning strategy with the best global results for ‘Clemenules’ mandarin was that which involved annually alternating mechanical (topping and one-sided hedging) and manual pruning. This strategy allows maintaining regular tree dimensions without dry branches inside.

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Section: Pruning Effect On Citrus Production: Yield and Fruit Sizementioning

confidence: 99%

Mechanical Pruning of ‘Clemenules’ Mandarins in Spain: Yield Effects and Economic Analysis

et al. 2022

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“…This prototype allows for the individualisation of all collected fruit as they move through the conveyor belts and incorporates an artificial vision system for inspecting the external quality of all of the produce while it is harvested. The features inspected by the vision system are size, shape and colour [23]. In addition, this prototype has two outlets to separate the fruit into two commercial categories (output bin 1 and output bin 2).…”

Section: Data Acquisitionmentioning

confidence: 99%

CitrusYield: A Dashboard for Mapping Yield and Fruit Quality of Citrus in Precision Agriculture

et al. 2020

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The application of new technologies in precision agriculture offers the possibility to link information to very specific crop locations. The spatial representation of these agricultural data through yield and fruit quality maps allows for crop management in a precise way that means that agricultural operations may be carried out considering intraorchard variability, thus resulting in greater efficiency. The aim of this work was to advance the development of new tools for the generation of yield and quality maps for precision agriculture. A new tool was implemented for citrus through a dashboard called CitrusYield that integrates the requirements demanded by technicians and farmers in terms of spatial distribution and the quality of their citrus production. The data for testing were collected by a prototype of a citrus harvest-assist platform. In order to obtain maps showing heterogeneity of production, an experimental plot with different varieties and variable production was chosen. The maps, tables and graphs showing different crop data were generated automatically by CitrusYield from the analysis of the data collected. The main advantage of knowing the differences in production between the swaths and areas inside the crop is to provide the grower with precise information to make accurate decisions for localised crop management, such as fertilisation, irrigation, pest and disease control, etc.

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“…Polarising filters were used to avoid bright spots. This mobile platform, which is described in Cubero et al (2010), is capable of presorting the harvested fruit into three different categories of quality in the field using the computer vision system. To do so, a series of rotating elements individualise the harvested fruit and separate the pieces into two lanes.…”

Section: Hardware Used For Data Acquisitionmentioning

confidence: 99%

In-Line Estimation of the Standard Colour Index of Citrus Fruits Using a Computer Vision System Developed For a Mobile Platform

Vidal

Talens

Prats-Montalbán

et al. 2012

Food Bioprocess Technol

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A key aspect for the consumer when it comes to deciding on a particular product is the colour. In order to make fruit available to consumers as early as possible, the collection of oranges and mandarins begins before they ripen fully and reach their typical orange colour. As a result they are therefore subjected to certain degreening treatments, depending on their standard colour citrus index at harvest. Recently, a mobile platform that incorporates a computer vision system capable of pre-sorting the fruit while it is being harvested has been developed as an aid in the harvesting task. However, due to the restrictions of working in the field, the computer vision system developed for this machine is limited in its technology and processing capacity compared to conventional systems. This work shows the optimised algorithms for estimating the colour of citrus in-line that were developed for this mobile platform and its performance is evaluated against that of a spectrophotometer used as a reference in the analysis of colour in food. The results obtained prove that our analysis system predicts the colour index of citrus with a good reliability 2 (R 2 = 0.925) working in real time. Findings also show that it is effective for classifying harvested fruits in the field according to their colour.

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Real-time inspection of fruit by computer vision on a mobile harvesting platform under field conditions

Cited by 9 publications

References 7 publications

Mechanical Pruning of ‘Clemenules’ Mandarins in Spain: Yield Effects and Economic Analysis

Mechanical Pruning of ‘Clemenules’ Mandarins in Spain: Yield Effects and Economic Analysis

CitrusYield: A Dashboard for Mapping Yield and Fruit Quality of Citrus in Precision Agriculture

In-Line Estimation of the Standard Colour Index of Citrus Fruits Using a Computer Vision System Developed For a Mobile Platform

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