Henri Temianka Correspondence; (laykin)

https://digitalcommons.chapman.edu/temianka_correspondence/2281/thumbnail.jp

Multispectral images of peach related to firmness and maturity at harvest

wo multispectral maturity classifications for red soft-flesh peaches (‘Kingcrest’, ‘Rubyrich’ and ‘Richlady’ n = 260) are proposed and compared based on R (red) and R/IR (red divided by infrared) images obtained with a three CCD camera (800 nm, 675 nm and 450 nm). R/IR histograms were able to correct the effect of 3D shape on light reflectance and thus more Gaussian histograms were produced than R images. As fruits ripened, the R/IR histograms showed increasing levels of intensity. Reference measurements such as firmness and visible spectra also varied significantly as the fruit ripens, firmness decreased while reflectance at 680 nm increased (chlorophyll absorption peak)

A new method for pedicel/peduncle detection and size assessment of grapevine berries and other fruits by image analysis

[EN] The berry size of wine-grapes has often been considered to influence wine composition and quality, as it is related to the skin-to-pulp ratio of the berry and the concentration of skin-located compounds that play a key role in the wine quality. The size and weight of wine-grapes are usually measured by hand, making it a slow, tedious and inaccurate process. This paper focuses on two main objectives aimed at automating this process using image analysis: (1) to develop a fast and accurate method for detecting and removing the pedicel in images of berries, and (2) to accurately determine the size and weight of the berry. A method to detect the peduncle of fruits is presented based on a novel signature of the contour. This method has been developed specifically for grapevine berries, and was later extended and tested with an independent set of other fruits with different shapes and sizes such as peppers, pears, apples or mandarins. Using this approach, the system has been capable of correctly estimating the berry weight (R-2 > 0.96) and size (R-2 > 0.97) of wine-grapes and of assessing the size of other fruits like mandarins, apples, pears and red peppers (R-2 > 0.93). The proven performance of the image analysis methodology developed may be easily implemented in automated inspection systems to accurately estimate the weight of a wide range of fruits including wine-grapes. In this case, the implementation of this system on sorting tables after de-stemming may provide the winemaker with very useful information about the potential quality of the wine.This work has been partially funded by the Instituto Nacional de Investigacio´n y Tecnologı´a Agraria y Alimentaria de Espan˜ a (INIA) through research project RTA2012-00062-C04-01 and RTA2012-00062-C04-03 with the support of European FEDER funds, by the UPV-IVIA collaboration agreement through UPV2013000005, and by UPV-SP10120276 Project.Cubero García, S.; Diago, MP.; Blasco Ivars, J.; Tardáguila Laso, J.; Millán, B.; Aleixos Borrás, MN. (2014). A new method for pedicel/peduncle detection and size assessment of grapevine berries and other fruits by image analysis. Biosystems Engineering. 117:62-72. https://doi.org/10.1016/j.biosystemseng.2013.06.007S627211