An intelligent procedure for watermelon ripeness detection based on vibration signals

Abbaszadeh, Rouzbeh; Moosavian, Ashkan; Rajabipour, Ali; Najafi, G.

doi:10.1007/s13197-013-1068-x

Cited by 32 publications

(17 citation statements)

References 30 publications

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“…Such data are useful for the nondestructive determination of fruit firmness and maturity (Abbaszadeh et al, 2015;Oveisi et al, 2014;. In this study, we further demonstrated through actual measurements that the f 3 /f 2 ratio is a powerful tool for the nondestructive detection of split pit in peaches.…”

Section: Future Use Of the Acoustic Vibration Methods For Commercial Pmentioning

confidence: 61%

“…This method has been developed to estimate fruit firmness . The f 2 frequency has also been used to evaluate flesh firmness and/or optimal ripeness of fruit, including melons (Taniwaki et al, 2009c, pears Oveisi et al, 2014;Taniwaki et al, 2009b;Terasaki et al, 2006), persimmons (Taniwaki et al, 2009a), kiwifruits (Terasaki et al, 2013), watermelons (Abbaszadeh et al, 2015), and grapes (Takahashi et al, 2010).…”

Section: Introductionmentioning

confidence: 99%

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Nondestructive Detection of Split Pit in Peaches Using an Acoustic Vibration Method

et al. 2018

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Split-pit in peach fruit is a problematic disorder. Split-pit fruit cannot be detected based on external appearance, and contamination of fruit by split-pit reduces its reliability in the marketplace. Here, we demonstrate that split-pit fruit can be identified by a nondestructive acoustic vibration method and a unique approach based on the ratio of the third (f 3 ) to the second (f 2 ) resonant frequency. The response-resonant frequency spectra showed that the peaks of f 2 frequencies in split-pit fruit were shifted to much lower values than those in normal fruit, whereas those of f 3 frequencies showed only small shifts. The calculated f 3 /f 2 ratios in most normal fruit were in the range of 1.35-1.4, whereas those in split-pit fruit were 1.45-2.0. Analysis of more than 300 fruit samples revealed that by setting the f 3 /f 2 cut-off value at >1.45, 95% of split-pit fruit in the fruit samples were detected, whereas only 1.5% of normal fruit were missorted as split-pit fruit. A model for simulating the vibration properties of peach fruit was developed by using the finite element method. The simulated vibration patterns showed that f 3 /f 2 values were increased by the insertion of split pit, indicating that, at least partially, the observed high f 3 /f 2 values in split-pit fruit directly reflected split-pit occurrence. These results clearly demonstrate that the use of f 3 /f 2 ratios obtained using an acoustic vibration method can effectively detect fruit with split-pit. The possibility of installing acoustic vibration devices in peach sorting lines and the application of portable devices to unpicked fruit on the tree are discussed.

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Section: Future Use Of the Acoustic Vibration Methods For Commercial Pmentioning

confidence: 61%

Section: Introductionmentioning

confidence: 99%

Nondestructive Detection of Split Pit in Peaches Using an Acoustic Vibration Method

et al. 2018

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“…The acoustic vibration method was initially developed to estimate fruit firmness , but has seen increasing use in the evaluation of the maturity of various agricultural products, including persimmons (Taniwaki et al, 2009a), pears Oveisi et al, 2014;Taniwaki et al, 2009b;Terasaki et al, 2006), grapes (Takahashi et al, 2010), kiwifruit (Terasaki et al, 2013), melons (Taniwaki et al, 2009c, and watermelons (Abbaszadeh et al, 2015;Ali et al, 2017). In addition to fruit firmness, Kadowaki et al (2012) adopted this method to detect the inner, local deterioration of Japanese pear fruit infected by core rot.…”

Section: Introductionmentioning

confidence: 99%

Nondestructive Detection of Split-pit Peach Fruit on Trees with an Acoustic Vibration Method

et al. 2018

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Split pit in peach (Prunus persica (L.) Batsch) fruit is an internal disorder that can have adverse effects on fruit quality and shelf stability. As it is difficult to distinguish split-pit fruit from normal fruit by appearance, a nondestructive detection method is desirable to determine accurately the timing of split-pit occurrence and remove unwanted fruit from trees. In our recent study, we used an acoustic vibration method for the nondestructive detection of split pit in harvested peach fruit. Here, we demonstrate that this method can be used to detect split pit in unpicked peach fruit. Time-course monitoring of growing fruit revealed that the ratio of the third (f 3 ) to the second (f 2 ) resonant frequency (f 3 /f 2 ), which is an indicator of split pit in harvested fruit, abruptly increased in unpicked split-pit fruit from early June to early July. In contrast, the f 3 /f 2 values of normal fruit remained low until harvest in late July. The increase in f 3 /f 2 values of split-pit fruit was observed in early June (stage II of fruit growth) and/or from late June to early July (stage III of fruit growth), suggesting that, at least under the experimental conditions in the current study, pit splitting occurred at these two different timings. Split-pit fruit detection rate at harvest increased towards the end of the second split-pit occurrence and split pit could be predicted with high accuracy thereafter. These results collectively suggested that the timing of split-pit occurrence in unpicked peach fruit could be predicted accurately by measuring f 3 /f 2 values and unwanted fruit with split pit could be distinguished from normal fruit on trees. We discuss the possible applications of the nondestructive acoustic vibration method in combination with fruit thinning and the future use of this method in research aiming to develop effective prevention methods or resistant cultivars with reduced split pit.

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“…[33] Laser Doppler Vibrometry (LDV) is one of the methods that has been investigated in determining ripeness of fruits. As in Figure 14, a watermelon fruit is placed on a shaker which is then vibrated according to random wave signal frequencies where the vibration spectrum response of the watermelon will be recorded by LDV [37]. Based on different spectrum patterns, the ripeness of the watermelon is then identified.…”

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confidence: 99%

Investigating Maturity State and Internal Properties of Fruits Using Non-destructive Techniques-a Review

et al. 2017

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An intelligent procedure for watermelon ripeness detection based on vibration signals

Cited by 32 publications

References 30 publications

Nondestructive Detection of Split Pit in Peaches Using an Acoustic Vibration Method

Nondestructive Detection of Split Pit in Peaches Using an Acoustic Vibration Method

Nondestructive Detection of Split-pit Peach Fruit on Trees with an Acoustic Vibration Method

Investigating Maturity State and Internal Properties of Fruits Using Non-destructive Techniques-a Review

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