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ABSTRACTEfforts have been made to streamline the abstract as follows. If further changes are made we are concerned that the integrity of the content may be compromised. We hope you will understand. This study aimed to investigate the impact damage experienced by Pucheng crisp pears during various stages, including harvest, transportation, and processing. Drop impact tests were conducted on pears, considering drop height and collision contact material as factors influencing damage. The bruise area was used as an indicator for damage evaluation. Additionally, the pressure-sensitive film technique was employed to measure the contact stress distribution characteristics of Pucheng crisp pears after the drop impact. The relationship between contact stress distribution and damage area was examined, and the stress area range close to the damage area was determined. The results revealed that the damage area of pears increased linearly with the increasing drop height. Among the four contact materials, foam board exhibited the best cushioning properties, with a maximum safe drop height of 20 cm. The pressure distribution tended to follow a normal distribution, with a pressure range of 0.2-0.3 MPa covering the largest area, corresponding to the majority of the bruise area on the pears. Furthermore, the pressure area and average pressure were found to be related to the severity of bruising. When pears were dropped onto steel, rubber plate and corrugated board, for the former two the stress area exceeding 0.2 MPa closely approximated the damage area, with an average relative error of 7.2%. For the latter, the closest range was above 0.3 MPa, with an average relative error of 3.6%. However, when dropped onto foam board, the average relative error was 75%. This research provides valuable insights for designing packaging tools to minimize damage and serves as a theoretical basis for predicting and assessing pear bruise area using finite element analysis.

Achieving fast and accurate prediction of the fruit mechanical damage area is important to improve the accuracy and efficiency of apple quality grading. In this paper, the spectral data of all samples in the wavelength range from 376 to 1011 nm were collected, the sample set was divided by the physicochemical coeval distance method, and the spectral preprocessing methods were evaluated by establishing a full-wavelength artificial neural network model. The wavelength selection of spectral data was performed by competitive adaptive reweighted sampling, L1 parameter method, and the Pearson correlation coefficient method, and the partial least squares, artificial neural network, and support vector machine (Gaussian kernel) prediction models were established to predict the fruit bruise area size. The surface fitting was performed using the actual apple bruise area, and the regression surface equation of the damage time and damage height of the fruit was established. The results showed that (1) the preprocessing method of first-order difference + SG smoothing can make the prediction model more accurate; (2) the CARS-ANN prediction model has better prediction performance and higher operation efficiency, with the prediction set root mean square error of prediction and R-value of 0.1150 and 0.8675, respectively; (3) the sparrow search algorithm was used to optimize the model, which improved the accuracy of the prediction model. The root mean square error of prediction reached 0.0743 and The R-value reached 0.9739. (4) The relationship between spectral information, bruise area, damage time, and damage degree was obtained by combining the establishment of the fitted surface of the apple bruise area with the prediction model. This study is of application and extension value for the rapid nondestructive prediction of fruit bruise area. [ABSTRACT FROM AUTHOR]

Efforts have been made to streamline the abstract as follows. If further changes are made we are concerned that the integrity of the content may be compromised. We hope you will understand. This study aimed to investigate the impact damage experienced by Pucheng crisp pears during various stages, including harvest, transportation, and processing. Drop impact tests were conducted on pears, considering drop height and collision contact material as factors influencing damage. The bruise area was used as an indicator for damage evaluation. Additionally, the pressure-sensitive film technique was employed to measure the contact stress distribution characteristics of Pucheng crisp pears after the drop impact. The relationship between contact stress distribution and damage area was examined, and the stress area range close to the damage area was determined. The results revealed that the damage area of pears increased linearly with the increasing drop height. Among the four contact materials, foam board exhibited the best cushioning properties, with a maximum safe drop height of 20 cm. The pressure distribution tended to follow a normal distribution, with a pressure range of 0.2-0.3 MPa covering the largest area, corresponding to the majority of the bruise area on the pears. Furthermore, the pressure area and average pressure were found to be related to the severity of bruising. When pears were dropped onto steel, rubber plate and corrugated board, for the former two the stress area exceeding 0.2 MPa closely approximated the damage area, with an average relative error of 7.2%. For the latter, the closest range was above 0.3 MPa, with an average relative error of 3.6%. However, when dropped onto foam board, the average relative error was 75%. This research provides valuable insights for designing packaging tools to minimize damage and serves as a theoretical basis for predicting and assessing pear bruise area using finite element analysis. [ABSTRACT FROM AUTHOR]

Achieving fast and accurate prediction of the fruit mechanical damage area is important to improve the accuracy and efficiency of apple quality grading. In this paper, the spectral data of all samples in the wavelength range from 376 to 1011 nm were collected, the sample set was divided by the physicochemical coeval distance method, and the spectral preprocessing methods were evaluated by establishing a full-wavelength artificial neural network model. The wavelength selection of spectral data was performed by competitive adaptive reweighted sampling, L1 parameter method, and the Pearson correlation coefficient method, and the partial least squares, artificial neural network, and support vector machine (Gaussian kernel) prediction models were established to predict the fruit bruise area size. The surface fitting was performed using the actual apple bruise area, and the regression surface equation of the damage time and damage height of the fruit was established. The results showed that (1) the preprocessing method of first-order difference + SG smoothing can make the prediction model more accurate; (2) the CARS-ANN prediction model has better prediction performance and higher operation efficiency, with the prediction set root mean square error of prediction and R-value of 0.1150 and 0.8675, respectively; (3) the sparrow search algorithm was used to optimize the model, which improved the accuracy of the prediction model. The root mean square error of prediction reached 0.0743 and The R-value reached 0.9739. (4) The relationship between spectral information, bruise area, damage time, and damage degree was obtained by combining the establishment of the fitted surface of the apple bruise area with the prediction model. This study is of application and extension value for the rapid nondestructive prediction of fruit bruise area.

We evaluated the effect of both the change in velocity (Vc) and the peak acceleration (P/tcc) on the bruise area (BA) of apple fruit by shock tests. The results demonstrated that the BA of apple fruit caused by shock changes depends on a combination of Vc and PAcc. We also drew damage boundary curves (DBCs) corresponding to the BAs that were determined from the combination of Vc and PAcc. Moreover, by using a multiple regression analysis, we inferred that an increase in the BA of apple fruit due to shock is caused by an increase in the PAcc, rather than the Vc; the relative contributions of the independent variables in the regression for Vc and PAcc were 0.48 and 0.71, respectively. This finding will contribute to the consideration of measures to counteract the occurrence of bruising of apple fruit during transport. [ABSTRACT FROM AUTHOR]

In order to better design and modification of peach post harvesting systems such as sorting, conveying and packaging, selected engineering properties and bruise susceptibility of two Iranian peach varieties (Elberta and Spring time) were determined. Physical and mechanical properties such as dimensions, mass, volume, projected area, surface area, sphericity, static friction and rolling resistance coefficients on various surfaces, firmness and compressibility were measured. Also, effect of cultivar, drop height (50, 100 and 150 mm) and contact surface material (fruit, steel and rubber) on the bruise area and volume were investigated. Analysis of variance results indicated that cultivar had a significant effect (p<0.05) on certain engineering parameters such as dimensions, volume, mass, surface area, rolling resistance coefficient and firmness. The effect of cultivar on the bruise volume and area was not significant. The contact surface material and drop height had significant effect on the bruise area (p<0.01) and volume (p<0.05). Mean comparison of data revealed that the bruise area on all three contact materials was significantly different from each other, but on the rubber surface, it showed no significant differences in bruise volume. Also, bruise area was significantly different for 50 and 150 mm drop heights, while bruise volume had significant difference at all three drop heights. In general, results indicated that some engineering parameters are depended on cultivar and have more rules in designing of sorting and conveying systems. Also, in sorting or packaging lines safe drop height must be considered and it is closely related to the contact surface material. [ABSTRACT FROM AUTHOR]