Impact device for measuring the flesh firmness of kiwifruits

Ragni, Luigi; Berardinelli, Annachiara; Гуарниери, А.

doi:10.1016/j.jfoodeng.2009.09.006

Cited by 40 publications

(15 citation statements)

References 37 publications

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“…The tissue of beets is tight, with little void space between cells, and thus can sustain high compressive loading. Mean values for mechanical parameters F, A and S were 181.97 N, 192.85 N-mm and 60.62 N mm À1 , respectively, which are much higher than that for fruits (Valero et al, 2007;Ragni et al, 2010;Wang et al, 2012;Mendoza et al, 2014;Rowe et al, 2014). Based on the calculated mean, median and skewness values, the data of each property parameter were approximately normally distributed.…”

Section: Statistics Of Measured Parametersmentioning

confidence: 86%

Measurement of moisture, soluble solids, sucrose content and mechanical properties in sugar beet using portable visible and near-infrared spectroscopy

Pan

Zhu

et al. 2015

Postharvest Biology and Technology

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Section: Statistics Of Measured Parametersmentioning

confidence: 86%

Measurement of moisture, soluble solids, sucrose content and mechanical properties in sugar beet using portable visible and near-infrared spectroscopy

Pan

Zhu

et al. 2015

Postharvest Biology and Technology

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“…Ragni et al (2010) developed a simple impact device supported by statistical analysis. This technique could be taken into consideration for on-line prediction of the flesh firmness of kiwi fruits.…”

Section: Introductionmentioning

confidence: 99%

Quality changes of pear during shelf-life

Zsom¹,

Zsom-Muha

Dénes

et al. 2016

Progress in Agricultural Engineering Sciences

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Abstract. The aims of our research work were the investigation of postharvest changes of pear samples (Pyrus communis cv. Bosc kobak) during combined cold storage and shelf-life (storage at room temperature), the determination of quality changes by mainly non-destructive methods, the modeling of the changes of the non-destructive parameters (acoustic, impact stiffness coefficient, chlorophyll fluorescence parameters [Fv/Fm, Fm/F0]), and multivariate statistical analysis of the measured and predicted data based on the data of the non-destructive texture analysis (acoustic and impact methods), chlorophyll fluorescence analysis and laser scattering measurement. Storage Time Equivalent Value (STEV) was calculated and introduced based on mass-loss analysis. The changes of the non-destructive parameters were analyzed vs. this virtual storage time (STEV). The changes of acoustic, impact stiffness coefficient and chlorophyll fluorescence parameters can be predicted by exponential function. The predicted time constants of the parameters were 21.0, 45.8, 47.1, 83.4, acoustic, impact stiffness coefficient, Fm/F0, Fv/Fm, respectively. The lower the time constant, the quicker is the change of the given parameter during storage, the higher is its sensitivity. By this point of view, the percentage mass loss related sensitivity to the characterization of textural changes, the predicted acoustic stiffness coefficient was found to be more sensitive than the impact stiffness coefficient. The Fm/F0 value characterized more sensibly the changes of the chlorophyll fluorescence than in the literature commonly used Fv/Fm. The non-contact laser scattering method based significant PLS models were constructed to predict the quality related pear characteristics (mechanical properties, chlorophyll fluorescence parameters).

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“…In particular, it is worth citing their use in combination with nondestructive flesh colour readings (Valero et al, 2003), as successfully tested to determine the optimum harvest date and quality characteristics of apple Zude et al, 2006) or mandarin (Hernández Gómez et al, 2006) fruit, respectively, or with artificial neural network software to predict kiwifruit firmness (Ragni et al, 2010).…”

Section: Introductionmentioning

confidence: 99%