”INN” luv-Au is A? .514: ‘94. p 2W v ' 3. I ’ .gwmé. \ i» m .m. ; .-~ 4 x _ D ..; :2 . .1 a? :u" L'H‘” .‘n .‘.'.. w' , - ' ' ..‘.. , “Hg-H.» . :r. , ‘ ‘. a ‘ . ‘ “ . " .,..,,r"V,-<. ,-..‘. or}. .‘4‘ : S 223W 01% HIGAN STATE UNIVERSITY LIBRARIE llllllllllllllllllllllllllllllllllll 3 1293 00611 7844 This is to certify that the thesis entitled L EZRARY Mchigan State University Simulation of Packing Line Impacts for Apple Bruise Prediction presented by Sidney Scott Sober has been accepted towards fulfillment of the requirements for Masters degree in Agric. Engr. Tech. MW MHW Major professors August 24, 1989 MS U i: an Affirmative Action/Equal Opportunity Institution PLACE IN RETURN BOX to remove this checkout from your record. TO AVOID FINES return on or before due due. DATE DUE DATE DUE DATE DUE .\ '1 An vfif‘,‘ h‘ ,___. MSU Is An Affirmative ActioNEquel Opportunlty Inuitulon SIMULATION OP PACKING LIN! IMPACTS FOR APPLE BRUISB PREDICTION BY Sidney Scott Sober A THESIS Submitted to Michigan State University in partial fulfillment of the requirements for the degree of MASTER OP SCIENCE in Agricultural Engineering Technology Department of Agricultural Engineering 1989 ABSTRACT SIMULATION OF PACKING LIN! IMPACTS POR APPLE BRUISS PREDICTION BY Sidney Scott Sober Impact pulses recorded by an Instrumented Sphere (IS) as it moved with apples through 12 commercial apple packing lines were analyzed to determine peak G's and velocity change. The peak G's ranged from 20 g to 130 g (1 g = 9.81 m/sz) and velocity change ranged from 0.1 to 3.0 m/s. These impacts were simulated in the laboratory using different surfaces that were calibrated using the IS. Paula Red and Golden Delicious apples were dropped onto these surfaces and the resulting bruises were recorded. The lowest impact threshold for bruise development was 40 g for the Paula Red apples and 30 g for the Golden Delicious apples. This occurred 1 day after harvest for Paula Red and 3 days after harvest for Golden Delicious apples. Multiple linear regression models were formulated for each variety of apple. The equations explained 85 percent of the variation in bruise diameter for Paula Red and 56 percent for Golden Delicious apples. mandamus I would like to extend a sincere thanks to Dr. Thomas Bukrhardt and Dr. Roland Zapp, who served as my co-advisors. Also a special thanks to the people in the USDA-ARS for there support and help on the project. Most of all, a very special thank you to my parents Gary and Ruth Sober for their support and encouragement. I could not have come this far with out you. iii TABLE OP CONTENTS LIST OF TABLES O O O O O O O O O O 0 LIST OF FIGURES. . . . . . . . . . Chapter 1. 4. INTRODUCTION. . . . . . . . . . 1.1 Importance of the Study. . 1.2 Review of Literature. . . 1.3 Objectives of the Study. . Fruit Used in Testing. . . 4 Drop Test Procedure. . . . 2.5 Bruise Analysis. . . . . . 2 2 2 2 Results and Discussion. .1 Collecting Apple Packing Line Data. .2 Simulating Apple Line Impacts. .3 3.1 Controlled Atmosphere Stored Apples . 3.2 Fresh Apples: Medium and Large Velocity Change 3.3 Graphical Representation of the Data. 3.3.1 3.3.2 Data. . . . . 3.3 3 3. 3.4 Apples data. . . . 3.4 Minimum Thresholds of Bruising. 3.5 Statistical Analysis. . . Paula Red Apples Tested. General Trends in the Paula Red Apple Golden Delicious Apples Tested. General Trends in the Golden Delicious 3.5.1 MLRA Model for Paula Red Apples. 3.5.2 MLRA Model for Golden Delicious Apples. 3.6 MLRA Model Compared with Linear Models. CONCLUSIONS. . . . . . .'. . . iv 29 .29 .29 .29 .30 30 41 .41 .52 .54 .54 58 .61 .65 .67 Chapter 7. Page ”MlusO O O O O O O O O O O O O O O O O O O O O O 68 Definition of the Coefficient of Determination . 68 Statistical Results for Paula Red Apples. . . . .69 Statistical Results for Golden Delicious Apples. 75 Data for Paula Red Apples. . . . . . . . . . . . 81 Data for Golden Delicious Apples. . . . . . . . .83 0' WO O O O O O O O O O O O O O O O O O 86 LIST OP TABLES Table Page Table 2.1 Surfaces Tested. . . . . . . . . . . . . .14 Table 2.2 Impact Characteristics of Surfaces. . . . 15 Table 2.3 Surfaces Used in Impact Simulation. . . . 20 Table 3.1 Bruise Thresholds for Paula Red Apples. . 31 Table 3.2 Brusie Thresholds for Golden Delicious Apples O O O O O O O O O O O O O O O O O O 42 Table 3.3 Brusie Diameter Sensitivity, Paula Red Mm MOdel O O O O O O O O O O O O O O O O 57 Table 3.4 Bruise Diameter Sensitivity, Golden Delicious MLRA Model. . . . . . . . . . . 60 vi Figure Figure Figure Figure Figure Figure Figure Figure Figure Figure Figure Figure Figure Figure Figure Figure 3.2 3.3 3.5 LIST OP PIGURES Typical Impact Curve Showing Peak Acceleration and Velocity Change. . . . . Peak G Distribution of Apple Packing Line Impacts. . . . . . . . . . . . . . . Velocity Change Distribution of Apple Packing Line Impacts. . . . . . . . . . . Impact Duration Distribution of Apple Packing Line Impacts. . . . . . . . . . Drop Test Machine. . . . . . . . . . . . . Impact Surface characteristics Defined in Terms of Velocity Change and Peak G's. . . Bruise Diameter Measurements. . . . . . . Calculated Bruise Volume. . . . . . . . . Visible Surface Bruises on Small, Paula Red Apples 1 Day After Harvest. . . . . Bruises Observed After Peeling of Small, Paula Red Apples 1 Day After Harvest. . . Visible Surface Bruises on Medium, Paula Red Apples 1 Day After Harvest. . . . . . Bruises Observed After Peeling of Medium, Paula Red Apples 1 Day After Harvest. . . Visible Surface Bruises on Large, Paula Red Apples 1 Day After Harvest. . . . . . Bruises Observed After Peeling of Large, Paula Red Apples 1 Day After Harvest. . . Visible Surface Bruises on Small, Paula Red Apples 3 Days After Harvest. . . . . . vii 10 11 .13 .19 26 28 32 32 33 33 34 34 .35 Figure Figure Figure Figure Figure Figure Figure Figure Figure Figure Figure Figure Figure Figure Figure Figure Figure Figure Page Bruises Observed.After Peeling of Small, Paula Red Apples 3 Days After Harvest. . . . .35 Visible Surface Bruises on Medium, Paula Red Apples 3 Days After Harvest. . . . . . . .36 Bruises Observed After Peeling of Medium, Paula Red Apples 3 Days After Harvest. . . . .36 Visible Surface Bruises on Large, Paula Red Apples 3 Days After Harvest. . . . . . . .37 Bruises Observed After Peeling of Large, Paula Red Apples 3 Days After Harvest. . . . .37 Visible Surface Bruises on Small, Paula Red Apples 12 Days After Harvest. . . . . . . 38 Bruises Observed After Peeling of Small, Paula Red Apples 12 Days After Harvest. . . . 38 Visible Surface Bruises on Medium, Paula Red Apples 12 Days After Harvest. . . . . . . 39 Bruises Observed After Peeling of Medium, Paula Red Apples 12 Days After Harvest. . . . 39 Visible Surface Bruises on Large, Paula Red Apples 12 Days After Harvest. . . . . . . 40 Bruises Observed After Peeling of Large, Paula Red Apples 12 Days After Harvest. . . . 40 Visible Surface Bruises on Small, Golden Delicious Apples 1 Day After Harvest. . . . . 43 Bruises Observed After Peeling of Small, Golden Delicious Apples 1 Day After Harvest. .43 Visible Surface Bruises on Medium, Golden Delicious Apples 1 Day After Harvest. . . . . 44 Bruises Observed After Peeling of Medium, Golden Delicious Apples 1 Day After Harvest. .44 Visible Surface Bruises on Large, Golden Delicious Apples 1 Day After Harvest. . . . . 45 Bruises Observed After Peeling of Large, Golden Delicious Apples 1 Day After Harvest. .45 viii Figure Figure Figure Figure Figure Figure Figure Figure Figure Figure Figure Figure Figure Figure Figure Figure Figure Page Visible Surface Bruises on Small, Golden Delicious Apples 3 Days After Harvest. . .46 Bruises Observed After Peeling of Small, Golden Delicious Apples 3 Days After Harvest. 46 Visible Surface Bruises on Medium, Golden Delicious Apples 3 Days After Harvest. . . . .47 Bruises Observed After Peeling of Medium, Golden Delicious Apples 3 Days After Harvest. 47 Visible Surface Bruises on Large, Golden Delicious Apples 3 Days After Harvest. . . . .48 Bruises Observed After Peeling of Large, Golden Delicious Apples 3 Days After Harvest. 48 Visible Surface Bruises on Small, Golden Delicious Apples 12 Days After Harvest. . . . 49 Bruises Observed After Peeling of Small, Golden Delicious Apples 12 Days After Harvest 49 Visible Surface Bruises on Medium, Golden Delicious Apples 12 Days After Harvest. . . . 50 Bruises Observed After Peeling of Medium, Golden Delicious Apples 12 Days After Harvest 50 Visible Surface Bruises on Large, Golden Delicious Apples 12 Days After Harvest. . . 51 Bruises Observed After Peeling of Large, Golden Delicious Apples 12 Days After Harvest 50 Predicted Versus Measured Bruise Diameter for Paula Red Apples. . . . . . . . . . . . . . 56 Predicted Versus Measured Bruise Diameter for Golden Delicious apples. . . . . . . . . . . .59 Average Bruise Diameter Versus Peak G's for Golden Delicious apples. . . . . . . . . . . .63 Average Bruise Diameter Versus Velocity Change for Golden Delicious apples. . . . . 64 ix 1 . INTRODUCTION 1.1 W Mechanized fruit handling systems used in the packing of fresh produce have been in use for many years. Although mechanical packing lines-have greatly increased the efficiency of sorting and packing fresh fruit, they have also increased the occurrence of damage due to mechanical impact. The mechanical impact damage problem has been pointed out in many past studies. Held, at al. (1974) as cited by Finney, et al. (1974), reported that bruising of Golden Delicious apples caused approximately 23 percent of the fruit to fall below the standards necessary for the highest quality. Similarly, Peleg (1984) concluded that bruising losses, in some fruit and vegetable crops, may reach an estimated 30 percent of the yield. Bartram, et a1. (1983), in studying two packing houses, determined the situation to be worse. He concluded that 89 percent of the apples (Golden Delicious) were bruised after completing all mechanical packing house operations. This can be compared to 74 percent damaged before the operations. He also concluded that the average number of bruises per apple (larger than 6.4 mm in diameter) increased from 1 to 3 1 bruises. The bruising and downs-grading of quality, caused by apple packing lines, results in financial loss to the packing house operators. Since consumers demand unbruised fruit, improving apple quality on packing lines is of great importance to both producers and consumers. 1.2 KW Solid, nonbiological body impacts were examined by Goldsmith (1960). Mohsenin (1970) later applied these impact theories to agricultural products. Fluck and Ahmed (1973) examined the theoretical aspects of impact and specifically related them to fruits and vegetables. They also produced an extensive bibliography of related studies. They related the impact measurements to fruit damage levels using an instrumented falling mass system. They showed that bruising resulted from a complex relationship between acceleration, velocity change and impact duration, all of which must be considered. From this work improved bruise prediction models were developed. Finney, et al. (1975), used an instrumented pendulum to improve the understanding of impact characteristics and the damage to fruit. They developed force deformation relationships to describe impacts to fruit. However, they did not apply their work to any specific fruits or vegetables. Idchtensteiger, et al. (1988) , used an impact force transducer to record impact characteristics of fruit falling onto it. From these data force-time relationships were found. Many other studies have been reported using similar configurations. All the studies mentioned above ignored the actual conditions in apple packing houses, where most mechanical damage occurs. Brown, et al. (1987), ran unbruised apples through apple lines to determine actual bruise damage. However, the forces producing the bruises on the fruit were not measured, so bruising could not be predicted from the forces experienced by the apple. Siyami et al. (1986) developed a data acquisition system, the instrumented sphere (IS), to measure impact characteristics on operating apple packing lines. The IS with on-board sensors, microprocessor and memory was mounted on an impact table along with apples in order to develop some bruise prediction models. The early tests and analyses were done without actual apple packing line data. A predictor model was developed for the first generation IS as follows: ABD - 30 + Bl (AAD) + B2(MT) + B3(MA) + B4(MA)2 + 35(DV)2 Where: ABD = Average bruise diameter, mm AAD - Average apple diameter, mm MT - Magness-Taylor flesh firmness, kg MA = Maximum acceleration, m/s2 DV 8 Velocity change, m/s Bi - Regression coefficients However, these tests were conducted before impact measurements could be recorded by an IS as it traveled with apples on a packing line. ' The impact table tests were conducted using impacts of 30 g to 300 g, which are above conditions found in actual apple packing lines. 1-3 We}; The following research will continue Siyami's original research of sensing apple line impacts and formulating bruise prediction models. The specific objectives of the research are as follows: 1. To classify the impacts recorded on commercial apple packing lines, 2. To identify surface conditions and drop heights that can be used in laboratory tests to simulate the recorded impacts, 3. To identify the impact level thresholds which cause bruising for Paula Red and Golden Delicious apples, «4. To formulate regression equations from laboratory drop tests to predict average bruise diameter for Paula Red and Golden Delicious apples. 2 . PROCEDURE 2.1 W An 89 mm IS was used to record impact pulses experienced on operational apple packing lines, Zapp et al. (1989) . The self-contained unit differs from the unit used in Siyami's drop table tests in both size and internal construction. The new IS contains a triaxial accelerometer, a microprocessor, 32 K of RAM, a battery and other miscellaneous. circuitry to condition the accelerometer output. The 330 gram unit is foam-filled and cast in beeswax. Due to its small size and apple like-buoyancy, the new IS was able to collect data through the entire packing line. Four IS‘s were run simultaneously with apples through twelve packing houses 3 to 12 times in each packing house. Each IS was placed onto the apple packing line at the water flotation tank at the beginning of the apple packing line and continued through the undersize eliminator, washer, waxer, dryer, sizers and apple baggers. When an IS was impacted above a preset threshold, the characteristics of the shock impulse were recorded. The data recorded as an IS passed through the apple baggers were not used in this study, but instead are part of a separate on-going study. 5 6 After each completed pass through the apple packing line, the data were up-loaded to a portable computer for immediate verification, disk storage and for later detailed analysis. On each pass through the apple packing lines the IS's recorded from 8 to 50 impacts above a threshold of 50 g. In the laboratory, the binary IS files were converted to readable impact data. From the down-loaded data, impact duration, peak G and velocity change were calculated. For all of the tests a total of 2865 impacts were recorded and analyzed. Note that in the following text velocity change specifically refers to the integration of the impact curve, or the area under the impact curve. The term "G" is used to specify the acceleration of an object. It is the acceleration of the body (m/sz) divided by the acceleration of gravity (9.81 m/sz). A small case 9 is used to denote the acceleration due to gravity, 9.81 m/sz. Figure 2.1 shows a typical impact curve with velocity change and peak G's. In preliminary tests on the drop tester, apples were dropped from heights which resulted in accelerations below 20 g. It was determined that a single impact below 20 g was insufficient to produce apple bruising. Impacts above 130 g were rare and were neglected. Thus, after analyzing (the packing line data, 1895 impact pulses were classified between 20 g and 130 g. A histogram of the peak G (maximum acceleration) distribution is shown in Figure 2.2. As shown, 1664 impacts mmcnno >uwooH0> use cowuoumaooo< xmmm mafisozm o>u=o poomfiH HoOwQ%B H.~ shaman \. \ .\ \. \W\\.\\\.\ \. \ \.?\.“.\. w\. x \\x \ “x. \ x...\..\n,u\\ .w.\\..fl.:\. ...\\..\\\\.\u fiaV.\wwmmvmemmm&WMWAMW$WNWWRWK®N®RWNWWN&&NW&WW\v . .1.“.\i.\ .\\ \ axon \ w... ”(\\. \x \ \....\.\\. Tx . R. . x .. \\ in \C . t t e.\\ \\\ \\w\\.\wt \\\ x \ \\. s .\ , \ \. Aw \ \ . .\\\\.\\\..\ ,.\ \“\\\ \.H\.\.\ \\ «N . \\ \ \\h.\\\\\®\\u\\®\. \\. . ..\ \ .. . . \ . \ ._ ...\ “\\.. \\kaea. \&&a\xt.. \. ..\\\\. H \.\\\ \\\\\\\ o V_1o11111111111111111111111111111111111111111 900 800 700 600 500 400 .300 200 SiOVdWI JO BBBWHN 1O 20 30 4O 50 60 70 80 90 100110120130140 PEAK G'S Figure 2.2 Peak G Distribution of Apple Packing Line Impacts 9 occurred between 20 g and 60 9. Approximately 88% of the impacts experienced in normal packing operations are accounted for in the range between 20 g and 60 9. Figure 2.3 shows the distribution of velocity change corresponding to the impacts considered in Figure 2.2. Velocity change values ranged from 0.1 m/s to 4.5 m/s (however, only 2 impacts were recorded with velocity change greater than 3 m/s). The simulated surfaces cover the approximate range of the impacts recorded on the packing lines. Figure 2.4 illustrates the distribution of impact duration for the impacts shown in Figure 2.2. The recorded values ranged between 3.07 ms and 23.04 ms. In the study reported here, the impact duration was not used in determining impact characteristics because the. method of determining impact duration may incorporate excessive error due to the ambiguity in impact completion. For this reason, velocity change was identified as a more reliable measure of impact characteristics. Since velocity change is the integration of the impact curves, it tends to smooth the impact data. The error due to difficulty with determining the beginning and end of the impact curves becomes insignificant. Thus, given a certain level of maximum acceleration, the velocity change is a much better indicator of the type of impact. 2.2 SW After analyzing operating apple packing line data for impact characteristics and their distributions, laboratory simulations to reproduce similar impacts were undertaken. 10 o muonaEH mafia oswxoom mamas no cofiuonfiuumfio mmcmno huwoon> m.~ shaman a}: 8238 168.9 xv ma” .Hn mum hum mwF 0;. may DAV frbln—Lb-hl—n-nnb.hbbbhnl-bl—l-bbb—hbblnhlhb-b 0 tom loop rom— e room romN SlOVdWl .:lO HBBWDN 11 450- 400- l I If! C) CD CD CD CD (D U) C) U) C) U) CD "3 "3 C9 C9 r- '- SiO‘v’chl .10 HEBWHN AND CV N O) 1— ; P\ l 1 l 1‘ \\l \\\‘ 1\\\\\\‘ 1\\\\\\\\\\\‘ °’ l\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\‘ l\\\\\\\\\\\\\\\\\\\\\\\\\\\‘ " l\\\\\\\\\\\\\\\\\\\\\\\\‘ h\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\‘ ‘° C) U) C) U) n P F t\\\\\\\\\\\\\\\\\\\\\\\‘ n IMPACT DURATION (ms) Figure 2.4 Impact Duration Distribution of Apple Packing Line Impacts 12 The peak G's to be reproduced ranged between 20 g and 130 g, and velocity changes spanned the range of 0.20 m/s to 2.76 m/s, since these ranges correspond to the impact levels most likely to cause bruising. A programmable impact table originally used for reproducing calibrated shock pulses proved inadequate to replicate the type of impacts experienced on an actual operating apple packing line. This is due to a lower limit of 100 9 obtained from the impact table. Thus, a free-fall drop tester which allowed lower impact levels, as shown in Figure 2.5, was used to produce the desired impact characteristics. To arrive at the desired shock pulses, several materials, as tabulated in Table 2.1, were placed on the heavy steel plate of the drop tester. The IS was dropped onto each surface five to six times from a given height, to record the impact characteristics and to obtain an average for each combination of material and drop height. After each drop the surface was relocated to assure the contact area would not be compressed by a previous drop. This entire process is referred to as "calibrating the surface”. From a nominal 20 g to 90 9: peak G, velocity change, impact duration, and drop height were recorded and averaged for each surface. As shown in Table 2.2, different surfaces have different velocity changes and drop heights for the same nominal peak G level due to their properties. After choosing the surfaces that produced the desired 13 U 1 APPLE V2332" HEIGHT / 'Figure 2.5 Drop Test Machine 14 Table 2.1 Impact Surfaces Tested* Surface mm... Description 1 Steel Plate, 12.7 mm 2 Wood, 38 mm 3 Polymate 135 Polyurethane COS belting, over surface 1 4 Sheet Metal, 1.6 mm 5 Felt, 1.6 mm, over surface 1 6 Sheet metal covered with felt, both 1.6 mm 7 Ametek Microfoam, 2-1.6 mm plies, over surface 1 8 Ametek Microfoam, 1-3.2mm ply, over surface 1 9 222 White Ethafoam, 6.4 mm, over surface 1 10 Uniroyal ENS-FBC Ensolite, 6.4 mm, over surface 1 11 Uniroyal MLC Natural Ensolite, 6.4 mm, over surface 1 *Use of company or product name by Michigan State University or the 0.8. Department of Agriculture is for information purposes and does not imply approval or recommendation to the exclusion of other which may also be suitable. 15 Table 2.2 Impact Characteristics of Surfaces* Peak G's SD DV SD Duration SD Drop Ht. Surface (m/s) (ms) (Cm) Number 21.3 1.18 0.20 0.01 3.8 0.16 0.25 1 20.6 1.29 0.27 0.01 5.6 0.71 0.16 2 21.4 0.28 0.33 0.01 5.4 0.00 0.24 3 21.8 1.64 0.38 0.04 4.4 0.30 0.30 4 21.1 0.82 0.52 0.01 5.6 0.09 0.60 6 21.3 1.21 0.83 0.08 7.5 0.66 1.00 7 20.7 0.88 0.90 0.01 8.3 0.23 1.42 8 21.5 0.47 1.19 0.04 9.5 0.70 2.54 9 19.2 0.15 1.18 0.02 9.9 0.17 2.54 10 20.2 0.59 1.41 0.07 10.6 1.17 5.10 11 31.7 1.18 0.34 0.01 3.5 0.16 0.30 1 31.0 3.42 0.40 0.02 4.4 0.39 0.24 2 31.4 1.23 0.44 0.01 4.6 0.28 0.40 3 29.7 1.60 0.47 0.05 3.7 0.90 0.40 4 30.6 5.08 0.36 0.02 4.3 0.17 0.33 5 30.5 0.54 0.52 0.01 5.6 0.09 1.00 . 6 31.4 1.43 1.03 0.06 7.3 0.54 1.70 7 31.7 2.19 1.26 0.11 8.7 0.70 1.90 8 30.1 0.88 1.52 0.09 9.8 0.51 3.80 9 29.8 0.78 1.58 0.05 9.7 0.09 4.45 10 29.2 1.05 1.92 0.10 11.6 0.42 7.60 11 40.2 3.75 0.43 0.01 3.5 0.72 0.60 1 41.4 1.45 0.50 0.02 5.1 0.99 0.48 2 42.3 1.00 0.54 0.02 5.1 1.44 0.55 3 41.1 1.17 0.71 0.01 4.5 0.40 0.80 4 40.2 3.54 0.46 0.01 4.2 0.47 0.48 5 40.4 1.63 0.90 0.06 5.0 0.40 1.60 6 41.1 2.30 1.15 0.05 6.9 1.07 2.20 7 40.6 1.47 1.31 0.04 7.5 0.31 2.85 8 39.6 2.34 1.73 0.14 9.1 0.79 5.10 9 39.8 0.35 1.90 0.01 9.9 0.55 6.35 10 40.5 1.67 1.78 0.12 9.1 0.78 10.80 11 16 Table 2.2 (cont'd) Peak G's SD DV SD Duration SD Drop Ht. Surface (m/s) (ms) (Cm) Number 50.5 3.29 0.55 0.01 4.0 0.28 0.80 1 50.8 2.96 0.55 0.01 4.0 0.25 0.56 2 51.5 1.95 0.63 0.01 3.6 0.36 0.64 3 50.1 4.59 0.87 0.06 3.5 0.53 0.79 4 50.2 4.70 0.56 0.01 3.7 0.34 1.20 5 51.1 2.36 1.04 0.04 4.5 0.64 2.00 6 49.8 1.09 1.33 0.01 7.9 0.80 2.70 7 50.4 1.67 1.50 0.16 8.0 1.40 3.18 8 49.6 3.18 1.98 0.12 8.4 0.56 6.80 9 50.0 0.78 2.17 0.01 8.0 0.38 8.26 10 49.6 3.18 1.98 0.13 8.4 0.56 13.40 11 60.8 5.99 0.61 0.01 3.6 0.49 1.00 1 58.7 1.40 0.62 0.01 3.9 0.17 0.79 2 60.7 3.03 0.69 0.03 5.3 1.10 0.95 3 61.1 2.17 0.98 0.03 4.1 0.75 1.60 4 60.5 1.76 0.56 0.01 3.5 0.23 0.97 5 60.5 1.85 1.16 0.03 4.5 0.68 2.50 6 60.1 4.79 1.34 0.01 6.1 0.36 3.30 7 59.8 3.68 1.54 0.06 6.6 0.47 3.81 8 60.8 1.17 2.23 0.05 8.0 0.25 7.30 9 61.2 1.32 2.39 0.05 8.3 0.22 10.00 1 71.3 2.38 0.62 0.02 3.6 0.25 1.20 1 71.3 4.85 0.78 0.01 3.9 0.17 1.11 2 70.5 2.77 0.76 0.02 3.4 0.43 1.35 3 68.8 3.09 1.04 0.02 4.4 0.70 2.00 4 71.1 2.09 0.75 0.04 3.4 0.41 1.27 5 70.6 1.80 1.36 0.02 3.7 0.11 3.00 6 70.7 1.46 1.38 0.04 5.5 0.12 3.70 7 69.5 2.26 1.59 0.02 6.4 0.30 4.20 8 69.0 2.89 2.26 0.10 7.6 0.36 8.60 9 72.8 2.72 2.55 0.06 7.9 0.40 2.55 1 17 Table 2.2 (cont'd) Peak G's SD DV SD Duration SD Drop Ht. Surface (m/s) (ms) (Cm) Number 80.2 2.78 0.71 0.00 5.3 1.20 0.40 1 82.2 1.36 0.86 0.02 3.2 0.62 1.27 2 80.8 1.62 0.86 0.02 2.8 0.33 1.75 3 80.9 2.31 1.42 0.02 3.7 0.81 3.40 4 81.5 2.90 0.79 0.02 3.6 0.12 1.60 5 79.5 .96 1.52 0.01 3.8 0.00 3.70 6 80.3 4.21 1.48 0.05 5.3 0.24 4.00 7 78.4 7.59 1.68 0.12 6.1 0.57 5.50 8 79.3 2.93 2.46 0.08 7.6 0.44 9.60 9 80.5 2.31 2.76 0.06 7.9 0.40 13.50 1 90.3 1.05 0.78 0.01 4.9 0.92 1.70 1 89.8 7.43 0.94 0.01 3.7 0.33 1.51 2 92.2 2.29 0.92 0.01 2.8 0.42 1.75 3 91.6 2.49 1.74 0.30 5.5 1.78 3.80 4 91.1 4.59 0.87 0.07 3.5 0.17 1.75 5 89.9 5.02 1.74 0.11 5.9 1.88 4.50 6 89.2 6.04 1.56 0.06 5.2 0.22 4.50 7 91.4 13.82 1.70 0.07 5.5 0.29 5.90 8 91.9 2.23 2.53 0.10 7.1 1.10 10.60 9 91.9 3.21 2.84 0.09 7.3 0.33 14.60 1 *See Table 2.1 for identification of each suface. 18 characteristics, each was calibrated up to 130 g. From inspection of the characteristics for each surface, the steel plate was chosen to reproduce impacts of small velocity change (0.20 m/s to 1.02 m/s) since it produced the smallest velocity changes at each peak G level. For medium velocity changes 2 surfaces were used to keep the medium velocity changes between the small and large velocity changes. The surface used to reproduce medium velocity change at low peak G's (20 g to 70 g) is referred to as "medium-low” and the surface used at high peak G's (50 g to 130 g) is referred to as ”medium-high”. Ametek Microfoam, made of 2-1.6 mm plys, was used to reproduce medium-low velocity changes (0.83 m/s to 1.38 m/s) and a single 3.2 mm ply of Ametek Microfoam was used for medium-high velocity changes (1.68 m/s to 2.08 m/s). The 2 surfaces chosen to reproduce medium velocity change surfaces fall between the small and high velocity change surfaces at each peak G level as shown by the center curve in Figure 2.6. Note that both low-medium and high medium are included in this curve. Also each point in Figure 2.6 represents the average value at each peak G level. The White Ethafoam 6.4 mm thick was used to produce the highest velocity changes (1.4 m/s to 2.76 m/s) . This surface produced the highest velocity changes which corresponded to actual packing line conditions. Table 2.3 shows the impact characteristics for each material used in the test at each peak G level. 19 m.u Room use mucosa huwooHo> no makes a“ omswuma mowumwueuonuoso ooomuom noumaH o.~ shaman mb x onflsum oouoaoudmu m.~ shaman wZDJO> mmSmm Dw._.<.504 A 1 H AVG. BRUISE DIAMETER (mm) < EA 1 1 - O-O AVG. BRUISE DEPTH (mm) -100 ‘01; E E 3 H AVG. BRUISE VOLUME (ml) :0 > FEE 10'. H PROBABIUW or BRUISING (z) -90 80 E; 9 i __ ~80 gm 29.3 8‘ -70 Egg SC) 7_ y 2(7) U7 5; 'n L(5'5 3 , T ~50 m5 350: 51 IN— 0:33 4: A T J _'40 Cg 00% /' ~30 Q3“ {‘95: 3‘- “ i 2?? <0C 3 ' ~20 52: leJ 2': ..l. \1 LL12 1 : X/ / _10 \0/3 a - .4 3 0 . , , , . r . , . , . , . o 60 70 80 90 100 110 120 130 140 PEAK G'S Figure 3.1 Visible Surface Bruises on Small, Paula Red Apples 1 Day After Harvest. I2~ r110 > A : O—O AVG. anus: DIAMETER (m) < EA 11.:HAVG. amuse DEPTH (mm) 1 ¢ ¢ T L100 '0'“ E E 3 H AVG. amuse VOLUME (rm) :0; v 10: e—e pRoeAeIuw or amusmc (5:) ~90 00 (Iv 9: gm HE ~: __ ‘80 92w L1Jill. 8.: [—1] ELL] ; -70 —C $0 7.‘ :5 PM 9 -60 Om LIJm 6‘. '11 m5 : ~50 005 5m 51 m“ cum : -40 Cc a] 41 “§: (“5’ : -30‘ (£171 8< '1 2? <9C 3 ~20 52‘: IruJ 2: \3 LIJ<>r : ~10 {/3 2 ‘E , 3 OJ ' I ' l ' l ' l ' r ' r . I r 0 50 60 7O 80 90 100 110 120 130 140 PEAK G'S Figure 3.2 Bruises Observed After Peeling of Small, Paul Red Apples 1 Day After Harvest. RAGE BRUISE DEPTH(mm) F '5. AVERAGE BPUISE DIAMETER(mm) AV ER(mm) DEPTH(mm) P - l— BRUISE DIAMET BRUIS ': L. '5' b AVERAG AVERAG 33 14 e . AVG. BRUISE DIAMEIER (mm) ~200 13} O O AVG. BRUISE DEPTH (mm) ’ ? v—v AVG. BRUISE VOLUME (ml) — 180 12~j e e PROBABILIIY OF BRUISINC (z) » I P160 _),_ _ ' 7 r- 1 40 /” +120 == I #100 /) L-60 -1 I #40 3E SEE ,/’ l //// If. “‘EEE/ ~20 I I I I I I I ' I ”r O 60 7O 80 90 100 110 120 130 140 PEAK C'S Figure 3.3 Visible Surface Bruises on Medium, Paula Apples 1 Day After Harvest. 141 e . AVG. BRUISE OIAMEIER (mm) ~200 1 3} e—I AVG. BRUISE OEPIH (mm) » 3 o... AVG. BRUISE VOLUME (ml) - 180 12 '7 o e PROBABIUIY OF BRUISING (z) . 11g r160 10f ~ I 40 9% ~ 3.3 l— 120 7% ~ I 00 63 ~80 5; . 4 ‘I ~ 60 3? ' L40 2% L 1-; :20 0‘1“"— '1” I} rFfrfTrT r I T I Irv 0 20 30 40 50 60 7O 80 90 100 110 120 130 140 PEAK C'S (2)9A518l088 _-IO All‘llBVBOEld (mm "3 3Wn'IOA 35In88 Bows/xv Red (z)ONIs:nsa 30 MI‘HBVSOHd (umJ ”3)3Wfl'lO/\ 381088 saves/xv Figure 3.4 Bruises Observed After Peeling of Medium, Paula Red Apples 1 Day After Harvest. AVERAGE BRUISE DIAMETER(mm) AVERAGE BRUISE DEPTH(mm) AVERAGE BRUISE DIAMETER(mm) AVERAGE BRUISE DEPTH(mm) O) 34 e- e AVG. BRUISE DIAMETER (mm) I. I AVG. BRUISE DEPTH (mm) v—v AVG. BRUISE VOLUME (ml) T L240 ‘5 t—O PROBABILITY OF meme (7:) ~ 14 _220 1: ~2OO 1 P II 7‘80 10 -160 9 —140 3 ~120 7 L 6 r100 5 P80 4 -60 3 . 2 I40 0 I . I I I I I T O 60 70 80 90 100 110 120 130 140 PEAK G'S Figure 3.5 Visible Surface Bruises on Large, Paula OO-‘NUé C-‘NU-FU‘O'DVQ Apples 1 Day After Harvest. e—e AVG. 8RUI5E DIAMETER (mm) s-s AVG. BRUISE DEPTH (mm) v-v AVG. BRUISE VOLUME (ml) e-e PROBABILITY 0F BRUISING (z) - 1 .1 1.4“ '/ L240 1220 . I- ~2OO L180 L160 L140 ~120 3100 —80 L60 140 ~20 . 0 20 30 401—» PEAK G'S I E '“TT' . I r l' r E’I‘ I 50 60 7O 85 90 100 110120130 I40 AySIDHB :lO ALI'IISVBOEJd W no 3WDTOA 381088 BOVHBAV (w(%)0 Red ASISIHHB :10 Ali'IIBVBOtld “J no 3WleO/\ ESIDHB HOVHHAV (Lucas Figure 3.6 Bruises Observed After Peeling of Large, Paula Red Apples 1 Day After Harvest. 35 14 e- e AVG. BRUISE OIAMEIER (mm) ~120 A 1 3 e . AVG. BRUISE OEPIH (mm) 1 10 EA w v AVG. BRUISE VOLUME (mI) 1' E E 12 ’o e PROBABILITY OF BRUISING (7.) __100 FEE I I LIJ I l—90 {.3 *- 1 O 80 2 83 9 1 it D 8 I- 70 O LU ‘g g 6 ~ 50 0: CD 5 40 CD L69] 4 l— LU Q < 3 l" 30 <1! F20 0: DJ 2 LIJ > 0 I T I Y O 80 1 :50 1 40 Figure 3.7 Visible Surface Bruises on Small, Paula Red AVERAGE BRUISE DIAMETER(mm) ‘ AVERAGE BRUISE DEPTH(mm) \l m Figure PEAK Gfs Apples 3 Days After Harvest. e 0 AVG. BRUISE DIAMETER (mm) AslSlflHB :10 ALI—IIBVBOHcl W no END—10A 381088 30V83AV (Lucas Ee—e AVG. BRUISE DEPTH (mm) P120 2 —j '4 AVG. BRUISE VOLUME (cm) H 10 1301 _: e e PROBABILITY 0F BRUISING (z) :0 3“ 1 —¢——e—————e—— L 100 O C); 3 CD 3 ~90 > m 1 903 .3 ~80 r:_ g 1 _ J +- 70 I U) 1 m “I -50 (I19 ,3 3°C . ~40 E z -5 / (I'm 3 A30 2’; ‘1 0C 5 ~20 Q1 : 5 8,3 .3 ,i..-——E—--i—I/ ~10 3 “ ""‘ I I I I I T I .— I I I I I I 0 v 50 60 7O 80 90 100 1 10 120 130 140 PEAK G'S 3.8 Bruises Observed After Peeling of Small, Paula Red Apples 3 Days After Harvest. ~100 14 > A ‘1 o-o AVG. ems: OIAMEIER (m) ,f [$1 EA 13": .-- AVG. 8RUISE OEPIII (mm) / P90 ‘0 :0 E 1 2 J v- 0 AVG. BRUISE VOLUME (ml) // 1) )> \E/ E 3 e .. PROBABILIIY OF BRUISING (x) I / l-80 8 0 55? H 3 \\ s” ': "" l— __(.D EB: 133 ' l 70 cg £3 8: 4“ +60 ’27, D E 1 Om 011in 7—2 +50 ~1< (J1- : O 53 63 ~40 %E mg 4.3 I ~30 ggm. LIJ I Z?) gag 3-3 L20 2: LIJ _j i \2 < 1'3 0 v 0 fl r 1' I V I ‘r r V r T 70 80 90 100 110 120 130 140 PEAK G'S Figure 3.9 Visible Surface Bruises on Medium, Paula Red Apples 3 Days After Harvest. 14 H AVG. BRUISE DIAMETER (mm) r120 :1) A 13 H AVG. BRUISE DEPTH (mm) rfi EA s—v AVG. BRUISE VOLUME (an) H 10 "Um E E 12 we PROBABILITY or BRUISING (z) #100 81> FEE II 00% UJI L90 > 1-I— 10 11303 Luo_ Lao r‘IJ IEUJ 9 53C: 30 8 L70 I7) onl 0"1 £03 * 0 gm 5 ~40 E: ..8 4 gm 130 323‘: 3 02 < _ v 0 r I I T I r I r I I F I I I I r I r I r I O 30 40 50 60 70 80 90 100 110 120 130 140 PEAK G'S Figure 3.10 Bruises Observed After Peeling of Medium, Paula Red Apples 3 Days After Harvest. E BRUISE DEPTH(mm) AVERAGE BRUISE DIAMETER(mm) AVERAG 37 141.- 0 AVG. BRUISE DIAMETER (mm) :- ~140 13 3H AVG. BRUISE DEPTH (mm) I L130 1M AVG. BRUISE VOLUME (an) 12-5». PROBABILIIY 0F BRUISING (x) -__}: ~ 120 1 1 _: ¢ P1 10 10% ~ ~400 9% 4+ #90 8% L-80 7% ‘ '\ ~70 6% ~60 5% ~50 4; +40 3% 4~ +30 2% +20 1% gig 3E ~40 03L- I I I I I I I I I I 0 60 7O 80 90 100 1 10 120 130 140 PEAK G'S (2)0 Ismae 30 AIIIIavaoad (LULLJ no awnIOA asmaa BOVBBAV Figure 3.11 Visible Surface Bruises on Large, Paula Red Apples 3 Days After Harvest. (mgr!) mm) .r-:( EDI DIAL! 5'73. 3 b P :IRLJIS-Z BPLH: — — P .— VEPAG: fr“ .“(F'J_~ A A! 14 o o AVG. BRUISE DIAMEIER (mm) — 130 I 3 o I AVG. BRUISE DEPIH (mm) :9 v AVG. BRUOSE VOLUME (ml) F120 12 g.-. PROBABIUIY 0F BRUISING (5:) L110 “ g ~100 ‘2} _ ~90 81 - A_ _ ~80 74: ‘ "7O 6 . I ”6°. 4 j - - ~- /. I40 3_ ‘F J- J- I_3o 2 1 AL “20 w i5 \ E—H—E ~10 O'I‘I “I III I I’III I III I I I I I I I I I I 0 20. 30 40 50 60 70. 80 90 100 110 120 130 140 PEAK C'S Figure 3.12 Bruises Observed After Peeling of Large, Paula Red Apples 3 Days After Harvest. (2)0A3Ismaa 50 MHIGVEOHd (WMJ ”0 3WD‘IOA BSInae BOVEEAV AVERAGE BRUISE DIAMETER(mm) AVERAGE BRUISE DEPTH(mm) 38 12 .4 AVG. BRUISE DIAMETER (mm) +150 go—I AVG. BRUISE DEPIH (mm) 1-140 1 1 1 .- 1 AVG. BRUISE VOLUME (mI) L 1 30 105 .— . PROBABILIIY 0F BRUISING (z) 1 / ~120 .1 9 1 " , 1- 1 1 0 8‘3 I 1" 1 00 75 ~90 6 : +80 ‘3 ~70 5? // +50 49 ~50 3: /" +40 2 2? +30 1 // +20 11 +10 0 d I I I I I I I I I I I 0 7O 80 90 100 110 120 130 140 PEAK 6'8 0 A)01\$|Slf188 JO All'llBVElOHcl (WM 03 awnIOA aslnaa 30va3AV ( Figure 3.13 Visible Surface Bruises on Small, Paula Red (mm) AVERAGE BRUISE DIAMETER(mm) AVERAGE BRUISE DEPTH Apples 12 Days After Harvest. 12 o—e AVG. BRUISE DIAMETER (mm) 1: — 130 a“. AVG. BRU|SE DEPTH (mm) _120 1 1 1 H AVG. BRUISE VOLUME (ml) 10 _: o- . PROBABILITY OF aRUIsmc (x) -1 10 3 ~I 91 9:0 3 I- 31 7 1 +80 E +70 6? E60 5? '+50 4% ~40 35 ~30 2% ~20 1% +10 0: l ' I ' I ' T i I 1 r I O 50 60 70 80 90 100 110 120 130 140 PEAK G'S (2)0 Ismae 30 ALIIIavaoad (mm m BWFTIOA asmaa aovas/w Figure 3.14 Bruises Observed After Peeling Of Small, Paula Red Apples 12 Days After Harvest. EPTY—i(mm) BPUESE D BPUESE D G'— ‘G': —‘ - R 1' .11.- A‘./E. A R. 39 1 '13 o-o AVG. BRUISE DIAMETER (mm) F150 J<> 1 3.1-- AVG. BRUISE DEPTH (mm) _ +140 '01“ 3.--. AVG. BRUISE VOLUME (ml) __ L1 30 mil); 121.... PROBABILITY OF BRUISING (x) O C) 1 1— 120 u] 1 1 :1 0 >111 10-1 11 9201 i . +100 cg 9 ‘ - _ L ~90 1;}, _8.: L80 Om ""1 "F 1—70 35 6 . / L 1—60 23E 5 « " “ ~50 3: _m ‘1 /" ~40 Z?) 5 .1 P30 0: : -1- L. {5 1 I +10 3 3 *0 v 0 r’ —T' I - 1PT- 'Ir—T'I'T-I’ T‘w—T'fi— T r j— 1—‘-—1 60 70 80 90 100 10 120 130 140 PEAK G'S Figure 3.15 Visible Surface Bruises on Medium, Paula Red AVERAGE BRUISE DIAMETER(mm) AVERAGE BRUISE DEPTH(mm) Apples 12 Days After Harvest. 14:1 O-e AVG. BRUISE DIAMETER (mm) _150 > 1 3.: ti AVG. BRUISE DEPTH (mm) 1—140 131% SM AVG. BRUISE VOLUME (ml) +130 j0:13 12‘: H PROBABILH‘Y OF BRUISING (x) O > 4 P120 [DO 11 . >"1 : T ~110 w 10': __CD 93 ~100 CE 8—13 A ”'90 :5 7 I / 1—80 gm 1 . _ < 5 : _L .1. , 70 mo 1 ~60 1" 55 _L 7°C 1 _L ~50 g: 4.: ___m a / “1° 2?? 2.; / M I"“$” "1"“; L20 £3 1": / -— "' ‘- 1O 3 0’: A I I I I I I I I I I I— I I I I O 40 50 60 70 80 90 100 1 10 120 130 140 PEAK G'S Figure 3.16 Bruises Observed After Peeling of Medium, Paula Red Apples 12 Days After Harvest. (mm) R RUISE DEPTH(mm) F - L. DIAME“.r p - — R015 E B ‘A MU AVE RAG E B AAA/[CR1 AVG. BRUISE DIAMETER (mm) AVG. BRUISE DEPTH (mm) AVG. BRUISE VOLUME (m1) PROBABILIIY 0F BRUISIHG (7:) L oguq 0". ~1SO ~140 ~130 ~120 ~110 ~100 ~90 ~80 +70 ~60 ~50 ~40 ~30 +20 +10 ’ T" _'_'" '1" '7" "'1'" ‘7” """ 1"." “""‘T" PEAK G'S PO 140 (23):) 151058 50 AIITIBVBOBCI (1WJ I10 3111mm 381F188 BDVBBAV Figure 3.17 Visible Surface Bruises on Large, Paula Red R(mm) AVERAGE BRUIEE DEPTHImm) DIAM ET VERAGE BRUIS A ."\ Apples 12 Days After Harvest. AVG. BRUISE DIAMETER (mm) AVG. BRUISE DEPTH (mm) AVG. BRUISE VOLUME (ml) PROBABILITY 0F BRUISING (z) ’~150 +140 +130 +120 P110 +100 P90 +80 +70 +60 L50 +40 ~30 P20 1"10 I I I I I III II I I’I I I I I I 40 50 60 7O 80 90 100 110 120 1.30 PEAK G'S 0 140 (25):) 151038 30 All‘llBVBOHd (UlJUU no 3Wfl'lOA 381F188 asvaaAV Figure 3.18 Bruises Observed After Peeling of Large, Paula Red Apples 12 Days After Harvest. 41 bruising occurs is lower for apples with a greater mass. Days after harvest (1, 3 and 12 days) appear to decrease the average bruise diameter as the length of time the apples are stored increases. Also, the threshold of bruising and the peak G level at which 100 percent bruising occurs increase after the apple has been stored for a period of time. As shown by separate ongoing research, these trends may change if the period of storage was longer than 12 days. The graphs also show that bruise depth and bruise volume increase as the peak G level increases. Note that the bruise volume tends to have a greater increase in size for each peak G level than the other characteristics tested. 3-3.3 99W Table 3.2 and Figures 3.19 through 3.36 represent the bruise characteristics for Golden Delicious apples. Table 3.2 shows a summary of the threshold of bruising and 100 percent bruising for each of the graphs. The fifth and sixth columns show the threshold of bruising and the average bruise diameter at that peak G level. Column 7 shows the peak G level at which 100 percent bruising occurred and column 8 shows the average bruise diameter at each peak G level. 3.3-4 WWW As shown by the graphs for Golden Delicious apples, the threshold for bruising moves to a lower peak G level as the mass of the apples increases. Also, the peak G level where 42' Table 3.2 Bruise Thresholds for Golden Delicious Apples Fig. All Days Threshold Avg. 100% Avg. Num. Bruises Size After of Bruise Bruising Bruise Visible Harvest Bruising Dia. Dia. (G'S) (mm) (G'S) (Inn!) 3.19 Y S 1 50 8.18 80 9.98 3.20 N S 1 40 6.73 70 8.60 3.21 Y M 1 50 9.09 70 9.51 3.22 N M l 50 8.24 70 9.51 3.23 Y L 1 40 8.29 60 10.23 3.24 N L l 40 8.29 60 10.23 3.25 Y S 3 50 6.28 90 9.69 3.26 N S 3 40 6.49 90 9.69 3.27 Y M 3 60 9.31 80 10.66 3.28 N M 3 40 7.14 70 10.37 3.29 Y L 3 50 10.57 50 10.57 3.30 N L 3 30 4.16 50 10.57 3.31 Y S 12 70 9.27 120 10.28 3.32 N S 12 50 6.05 90 9.37 3.33 Y M 12 70 9.59 110 11.01 3.34 N M 12 50 6.33 110 10.69 3.35 Y L 12 60 8.16 130 11.68 3.36 N L 12 50 4.07 120 11.87 AVERAGE BRUISE DIAMETER(mm) AVERAGE BRUISE DEPTH(mm) Figure 3.19 Visible Surface Bruises on Small, Golden AVERAGE BRUISE D!AMETER(mm) AVERAGE BRUISE DEPTH(mm) 43 e- 0 AVG. BRUISE D|AMETER (mm) I4 AVG. BRUISE DEPTH (mm) H AVG. BRUISE VOLUME (ml) e~ o PROBABILITY 0F BRUISING (x) O-‘NUéU‘O‘SVCD —200 +190 —180 ~17O +160 ~150 ~140 +130 L120 L110 ~100 ~90 L-80 ~70 L60 L-50 L40 ~30 —20 10 T r . I "T'* I T’I * I ' I ‘ r . I ' 30 40 50 60 70 80 90 100110120130140 PEAK 0'3 0 Delicious Apples 1 Day After Harvest. “1'er AVG. BRUISE DIAMETER (mm) -?38 134p. AVG. BRUISE DEPTH (mm) SF. AVG. BRUISE VOLUME (ml) 130 123». PROBABILITY OF anuusmc (x) 5' 1 28 11? ~150 10% ~140 j ~130 95 ~120 8? ~110 74 ~100 3 .~90‘ 5? ~30 5E -70 3 P60 4? ~50 3% ~40 5 ~30 2 3 ~20 1? ~10 Oir- 0 PEAK G'S T“I ' I ' r' I T'I f’I‘fifl’I T" T ' l' 20 30 40 50 60 70 80 90 100110120130140 88 :10 MlWlBVBOc‘Jd ASISID UU ”3 ENG-10A ESIRHB EOVHBAV (w(%)0 8d BOVBBAV 01351088 :10 MHISVBO W ”3 ENG-10A 381088 (:4) (Lu Figure 3.20 Bruises Observed After Peeling of Small, Golden Delicious Apples 1 Day After Harvest. AVERAGE BRUISE DIAMETER(mm) AVERAGE BRUISE DEPTH(mm) Figure 3.21 Visible Surface Bruises on Medium, Golden AVERAGE BRUISE DIAMETER(mm) AVERAGE BRUISE DEPTH(mm) 44 14 o 0 AVG. BRUISE DIAMETER (mm) ~200 1 3 I-I AVG. BRUISE DEPTH (mm) *- ». AVG. BRUISE VOLUME (ml) 1— 180 12 . e PROBABILITY 0F BRUISING (z) I 11- P160 T I I 10 ' ~14O 9 I- 8 I _L :11_ r 1 20 7 ~100 5- , ~80 5 T , I 4 :60 3 J l P40 2 I- 1 -' I 0’ T I I I r I I j ‘r' W I I I T I I I O 30 4O 50 60 70 80 90 100 1 10 120 130 140 d-b—b-bd QO‘NU-F O-‘NU&UIO5\JQ PEAK G'S Delicious Apples 1 Day After Harvest. e '0 AVG. BRUISE DIAMETER (mm) I~l AVG. BRUISE DEPTH (mm) '4 AVG. BRUISE VOLUME (ml) o—e PROBABILITY 0F BRUISING (Z) T L... -1. 1r- -—{ V — 200 b -180 L160 1140 L120 L100 I ‘ ~80 I—BO I ~40 ~20 I- r I I r I I I T f I I I I r I I I Tfi I I 30 40 50 60 70 80 90 100 110 120 130 140 PEAK G'S 0 WSIHHB :IO MI'IIBVBOEId L“ “3 EWITIOA 381F188 BOVEIEIAV (w(z)0 (%)0|\SISIDHB JO Almavaoad (WUu no 3meA aslnaa 30va3Av Figure 3.22 Bruises Observed After Peeling of Medium, Golden Delicious Apples 1 Day After Harvest. (mm) AVERAGE BRUISE DEPTH(mm) AVERAGE BRUISE DIAMETER (DO-*NUJiU' O-‘NUPLDOVCD 45 0-0 AVG. BRUISE DIAMETER (mm) H AVG. BRUISE DEPTH (mm) H AVG. BRUISE VOLUME (ml) T 0—4 PROBABILITY 0F BRUISING (z) / . ~220 -&200 ~130 L160 ~14O L120 1100 20 PEAK G'S I I’TfiT'T‘TfF’lTIfiI‘I' 30 40 50 60 70 80 90100110120130140 Figure 3.23 Visible Surface Bruises on Large, Golden Delicious Apples 1 Day After Harvest. AVERAGE BRUISE DIAMETER(mm) AVERAGE BRUISE DEPTH(mm) DANG-#0103 O-‘NU-fi-U‘QVWO ea AVG. BRUISE DIAMETER (mm) H AVG. BRUISE DEPTH (mm) H AVG. BRUISE VOLUME (ml) e-e PROBABIUTY OF BRUISING (x) I E 9’ / [220 L~200 ~180 L160 1. :140 ~120 L ~100 #80 1- ~60 ~40 L ~20 F'Irilel‘1'F'lrlfilj 20 3O 40 50 60 70 80 90100110120130140 PEAK G'S 0 BOVHBAV ISIDHB :JO All'IIBVBOBd W “SSBWFTIOA BSIHBB (w(%)0 (%)OI\SISIDHEI _-IO MI'IIBVBOHd (muJ no 3meA asunae asvaaAv Figure 3.24 Bruises Observed After Peeling of Large, Golden Delicious Apples 1 Day After Harvest. AVERAGE BRUISE DIAMETER(mm) AVERAGE BRUISE DEPTH(mm) 14 13 12 00‘ O-‘NU-hUIOIVm 46 o- 0 AVG. BRUISE DIAMETER (mm) I- I AVG. BRUISE DEPTH (mm) F 0 AVG. BRUISE VOLUME (mI) o~ e PROBABILITY OF BRUISING (X) 200 190 1—180 L170 ~160 ~150 r140 ~130 L120 ~11O ~100 ~90 ~80 ~70 ~60 ~50 ~40 ~30 ~20 ~10 I I I r I I f fiI I I I I I I—I I I I 40 50 60. 7O 80 90 100 110 120 1.30 PEAK G'S , T 30 O 140 Figure 3.25 Visible Surface Bruises on Small, Golden Delicious Apples 3 Days After Harvest. E DIAMETER(mm) ERAGE BRUISE 0ERIH(mm) RAGE BRUIS AV E AV 0 0 AVG. BRUISE DIAMETER (mm) C 0 AVG. BRUISE DEPTH (mm) . .4 AVG. BRUISE VOLUME (ml) we PROBABILITY OF BRUISING (z) —200 ~190 ~180 ~17O 'r160 r150 ~140 ~130 ~120 ~110 +100 .~90 ~80 ~70 ~60 ~50 ~40 ~30 ~20 ~10 0 PEAK G'S " r'T'T'r‘TTIfT'Tr‘r'T'I‘ 20 30 40 50 60 70 80 90100110120130140 ASISIHBB :IO Ail'TIBVBOBcI UJ “3 EWITIOA 39088 BOVHBAV (w(%)9 (%)91\3|SII'188 .40 AlI'uaveoad (uJLLJ no 3meA asunaa HovaaAv Figure 3.26 Bruises Observed After Peeling of Small, Golden Delicious Apples 3 Days After Harvest. AVERAGE BRUISE DIAMETER(mm) AVERAGE BRUISE DEPTH(mm) 141 12—2 3 - AVG. BRUISE DEPTH (mm) . v- 0 AVG. BRUISE VOLUME (ml) 47 o 0 AVG. BRUISE DIAMETER (mm) o o PROBABILITY 0F BRUISING (X) ‘1 ~2é0 L200 P180 P160 1140 . f12o ~100 :30 P60 L40 :20 20 30 40 I- 0 r PEAK G'S IIIIIIITIIIIIIIIIII 50 60 70 80 90100110120130140 Figure 3.27 Visible Surface Bruises on Medium, Golden AVERAGE BRUISE DIAMETER(mm) AVERAGE BRUISE DEPTH(mm) Delicious Apples 3 Days After Harvest. 14 o-e AVG. BRUISE DIAMETER (mm) ~220 13 e—o AVG. BRUISE DEPTH (mm) » e 1 AVG. BRUISE VOLUME (ml) ~200 12 'o--o PROBABILITY or BRUISING (x) r P180 1 1 - L 9 ~140 3 L120 7 / . 6 . :- 1 00 5 ‘ ~80 4 1"'F ~60 3 ~40 2 . 0 T ' r rfifi T‘r r r' l r T r l ' I T l ‘ 0 40 50 60 70 80 90 100 110 120 130 140 PEAK G'S ”(2)0ASIsmaa .40 ALI'IIBVBOEId (ww no 3meA 351039 aovaaAv (mewsmaa :10 mlevaoad (Gum no 3meA BSIDBB asvaaAv Figure 3.28 Bruises Observed After Peeling of Medium, Golden Delicious Apples 3 Days After Harvest. AVERAGE BRUISE DIAMETER(mm) AVERAGE BRUISE DEPTH(mm) 48 16 H AVG. BRUISE DIAMETER (mm) . 15 H AVG. BRUISE DEPTH (mm) __ P260 ‘4 : 333:2:115 3333551331,.) 2‘ 724° ‘3 ~220 ‘2 , . lzoo 11 P180 '3 L160 8 3140 7 ~120 6 ~100 5 lao 4 ~60 : E—AO 1 ~20 0 . 0 PEAK 0'8 30" 40 5'0 . 610fi7IO 1 6'0 1 9'0 '100'110'15031301140 Figure 3.29 Visible Surface Bruises on Large, Golden Delicious Apples 3 Days After Harvest. AVERAGE BRUISE DIAMETER(mm) AVERAGE BRUISE DEPTH(mm) c—b—ul—A—b-Ja—I dNU-P-U‘O') O-‘NUPUOJVCDCOO e—e AVG. BRUISE DIAMETER (mm) H AVG. BRUISE DEPTH (mm) H AVG. BRUISE VOLUME (ml) H PROBABILITY 0F BRUISING (x) P’- 7 ~280 3260 ~240 l220 L200 1160 3160 r140 ~120 ~100 IIIII #mm 000 L20 0 ‘7 #1 I T I I I I . I I I 20 30 40 50 50 70 80 90 PEAK G'S r..,.1.,. 100110120130140 (%)OI\SISIDHEI _-IO AIHIBVBOBCI (LUUJ no 3meA BSIDBB BDVHBAV (wowsmaa 50 ALI'IIBVEIOEIcI (11111.. no 3WD‘IOA 351088 BOVBBAV Figure 3.30 Bruises Observed After Peeling of Large, Golden Delicious Apples 3 Days After Harvest. 49 14 .5. AVG. BRUISE DIAMETER (mm) C320 A H AVG. BRUISE DEPTH (mm) 1.. E’é‘ 13 F—v AVG. BRUISE VOLUME (m1) . 300 E 12 o—a PROBABILITY 0F BRUISING (x) . :230 E’é 11 T ~260 uJI P240 Ir- 1— 10 . LED. 9 P220 55 g B _P 200 D LIJ :- 180 M!) 7 ~160 1.1..) :3 6 I- 1 40 DOC . 0: (D 5 _P 1 20 53%; 4 J. :‘0" at: 0.1 T 60 Lu> 2 ~40 > < 1 /‘ ’~ 20 < , . 0 I I I I I f I I I I I I I T I l— I 0 50 60 70 80 90 100 1 10 120 130 1 40 PEAK G'S Figure 3.31 Visible Surface Bruises on Small, Golden Delicious Apples 12 Days After Harvest. 14 H AVG. BRUISE DIAMETER (mm) 320 A I—I AVG. BRUISE DEPTH (mm) EA '3 H AVG. BRUISE VOLUME (MI) 300 £5 12 HPROBABILITYOFBRUISINGm 280 Irv 11 . 250 ME 10 2‘0 go. 9 220 5.8 a 200 onJ 180 mg) 7 160 5303 6 140 0:03 5 I A 120 mg 4 ._...., L 100 84: 3 /_( A 80 EEEJ 60 51?: 2 -.r 40 < 1 /“ 20 0 I I FIT I I I I I I I r I T I T I 1 I I 0 60 70 80 90 100 110 120 130 140 3'0 40 ' PEAK G'S ASISIOBB :10 Ail-IIBVBOI‘Jd LU no BWITIOA 381088 BOVBEAV (w(z)0 ASISIDBB :10 AiIWIBVBOEId W no 3WD'IOA BSIDHB EOVHBAV (w(z)0 Figure 3.32 Bruises Observed After Peeling of Small, Golden' Delicious Apples 12 Days After Harvest. 14 13 12 11 10 ID AVERAGE BRUISE DIAMETER(mm) AVERAGE BRUISE DEPTH(mm) O-‘NU-AUIOIVO 50 e 0 AVG. BRUISE DIAMETER (mm) I I AVG. BRUISE DEPTH (mm) F4 AVG. BRUISE VOLUME (m1) e-oe PROBABILITY OF BRUISING (X) I / P320 r300 r280 T250 P240 E220 ~200 E180 P150 L140 L120 }100 PBO ~60 }40 ~20 '0 50 60 70 80 00 PEAK G'S . I . I . I . f . 100 110 120 130 140 Figure 3.33 Visible Surface Bruises on Medium, Golden ' Delicious Apples 12 Days After Harvest. 14 13 12 11 10 0 AVERAGE BRUISE DIAMETER(mm) AVERAGE BRUISE DEPTH(mm) O-‘NUfiUIme .— 0 AVG. BRUISE DIAMETER (mm) o-e AVG. BRUISE DEPTH (mm) v— v AVG. BRUISE VOLUME (ml) v e PROBABIUTY OF BRUISING (x) /-‘ lj i J] 11 8 115151038 _-10 ALI-IIBVBOUB LU no BWO‘IOA BSIOHB HOWE/W 7 D O r T'l'l ”#0, COO I I III I I I I I I I I I T'I r I I I 30 40 50 60 7O 80 90 100110120130140 PEAK G'S '0 ASISIFIEIB JO Ail-IIBVBOBd LU ”3 BWO'IOA BSIDBB EDVBBAV (w(z)0 (w(z)9 Figure 3.34 Bruises Observed After Peeling of Medium, Golden Delicious Apples 12 Days After Harvest. AVERAGE BRUISE DIAMETER(mm) AVERAGE BRUISE DEPTH(mm) AVERAGE BRUISE DIAMETER(mm) AVERAGE BRUISE DEPTH(mm) 51 .5 0 0 AVG. BRUISE DIAMETER (mm) I~I AVG. BRUISE DEPTH (mm) F. AVG. BRUISE VOLUME (ml) H PROBABILITY OF BRUISING (X) 13 ..L—O—n (Do-‘10 T I Ifi I 120 130 140 OdMU#mm\lm f , . , . , . 80 90 100 1 PEAK G'S Figure 3.35 Visible Surface Bruises on Large, Golden Delicious Apples 12 Days After Harvest. l ' T 40 50 f. 10 e—e AVG. BRUISE DIAMETER (mm) on AVG. BRUISE DEPTH (mm) H AVG. BRUISE VOLUME (m1) 6.. PROBABILITY or BRUISING (x) 14 13 12 11 P 10 . T- P280 to ‘I‘V M .5 O .L t40 // L20 I’ 0‘10meme FT F T F ' .T r T ' Tfi F f T ' T ‘ :50 4O '50 60 70 __ BO 90 100 110 120 1:50 140 PEAK C'S 1038 :IO MIWIBVBOHd IS w r1313meA asInBB BOVB3AV (w(z)0 ASISIFIHB :JO AiI'IIBVBOEIcI “J no EWO'IOA BSIDBB BOVHBAV (w(%)9 Figure 3.36 Bruises Observed After Peeling of Large, Golden Delicious Apples 12 Days After Harvest. 52 100 percent bruising occurs is lower for apples with a greater mass. Days after harvest (1, 3 and 12 days) appear to decrease the average bruise diameter as the length of storage time increases. Also, the threshold of bruising and peak G level at which 100 percent bruising occurs increased after the apples have been stored for a period of time. As with the Paula Red apples, the graphs show that bruise depth and bruise volume increase as the peak G level increases. Note that the bruise volume increases more rapidly and seems to be more responsive to the peak G level. It is also interesting to note that in the range from 80 g to 120 9 there is a noticeable dip in bruise volume in almost every Golden Delicious apple test. 3-4 WWW From the above data it can be concluded that the Paula Red apples have a threshold of visible bruising at 80 g cm steel. At this peak G level, 20 percent of the small, 40 percent of the medium and 10 percent of the large apples bruised 1 day after harvest. At 3 days after harvest 20 percent of the large apples bruised at this threshold, while medium and small did not bruise at this impact level. Paula Red apples had a threshold for observable bruising after peeling at 40 9. At this level 40 percent of the large apples and 10 percent of the small apples displayed bruising 1 day after harvest. However, no medium apples bruised 1 day after harvest at this level. At 3 days 53 after harvest 10 percent of the large apples bruised at the 40 g threshold, with no bruising occurring in the small and medium apples. Golden Delicious apples had a threshold for visible surface bruising at 40 g on steel. At this peak G level, 30 percent of the large apples tested 1 day after harvest displayed bruising, while the small and medium Golden Delicious apples did not bruise. Golden Delicious apples had a threshold for observable bruising after peeling at 30 g. At this level 30 percent of the large apples tested 3 days after harvest were bruised. No other apple sizes bruised at this G level. Although low G levels may only produce bruises below the surface of the apples, and are not visible to the consumer, apples that show bruising after peeling will still not satisfy the consumer. Therefore, apple packing lines should be designed or modified to keep impacts below the peak G at which any bruising occurs. In the above experiments, the lowest threshold for bruising, after peeling, was at 40 g for Paula Red apples and 30 g for Golden Delicious apples. To assure that apples are not bruised on the cheek area by the packing lines, peak G levels recorded on commercial apple lines should be held below the 30 g level. An even lower level is probably necessary to avoid bruising on the small radius portions of the apple on the blossom and stem ends. 54 3.5 W The data used for the multiple linear regression analysis (MLRA) were from the groups of apples that displayed 100 percent bruising. Groups of apples that did not show 100 percent bruising were excluded due to the high variability of bruising near the threshold level. Thus, all values used are the average of 10 bruises to provide better estimates. All MLRA models were based on forward stepping regression analysis. Also in the following analysis "R2" is used to represent the coefficient of determination for MLRA models and "r2" is used to represent the coefficient of determination for linear regression analysis (LRA) models. 3.5.1 W The dependent variable for the MLRA model is the average bruise diameter of 10 bruises at a given peak G level which caused 100 percent of the apples to bruise. There were a total of 42 cases in the analysis which left 41 degrees of freedom. See Appendix A.2 for the complete statistical report. The independent variables available for the analysis were; days after harvest; peak G level; velocity change; apple mass: and apple flesh firmness. After analysis the resulting equation explained 84.8 percent (R2-0.848) of the variation in the average bruise diameter (ABD) of the apples: ABD 8 0.875 + 3.04DV + 0.03451! + 0.05726 - 0.123D -0.0789F Where: ABD - Average bruise diameter of 10 apples, mm 55 DV - Velocity change, m/s M - Average apple Mass, g G - Peak acceleration, g D - Days after harVest F - Average apple Magness-Taylor firmness, N Figure 3.37 shows the predicted bruise diameter versus the measured bruise diameter. The linear regression line is shown with confidence belts for the predicted bruise diameter at the 95 percent level. Thus, there is a 95 percent probability the values will be in range of the confidence belts. The sensitivity of this model was tested by inputting values into the equation that were in the mid-range and the extremes of the data used to formulate the equation. The initial mid-range values are shown in the first line of Table 3.3. These values yield an ABD of 8.12 mm. Each variable was then changed one-by-one to its highest and lowest extremes, lines 3 and 5, holding all other variables constant. The results are shown in lines 4 and 6 of Table 3.3. As can be seen, varying the peak g level had the most pronounced affect on the ABD. At 70 g, ABD was 6.4 mm compared to the original 8.1 mm. When the maximum values were used the peak g level again had the greatest affect. At 130 g, ABD was 9.85 mm. Adso, by increasing the apple mass and days after harvest, changes of nearly 1 mm were observed in the ABD. In summary 1 day after harvest was the 56 meamnd pom mason you Mouoaowo omfisum consume: msmuo> omuowooum Pn.n 00:6wm AEEV KNEE/4.5 mmEmm ommamfifi NF : or m m P m. m h L L L e L L L L _ _ L L L W .590 H L .xnhd + TN H > In Ix. 1m I: I? \ mos: 00:02.68 Nmm I I - 0:: co_wmotmmm 19 00.41.35 or L0 000L024 ... .. (ww) HBLBWVICI 331080 CEIlOICIEIHd 57 Table 3.3 Bruise Diameter Sensitivity, Paula Red MLRA Model Independent Variable Variable and DV, M. G, D. F, ABD Status “/3 8“ 8'3 days N Midrange variable Value 0.83 140 100 3 71 ABD, average, mm 8 12 8 12 8.12 8 12 8 l2 Minimum variable value 0.62 116 70 l 67 A80, minimum. mm 7.48 7.27 6.40 8.37 8.44 Maximum variable value 1.02 175 130 12 75 A80, maximum, mm 8 70 9 36 9.85 7 02 7 81 Maximum possible condition 1.02 175 130 l 75 Maximum ABD, mm 11.40 11.40 11.40 11.40 11.40 ABD - Average bruise diameter. G - Peak acceleration. DV - Velocity change. 0 - Days after harvest. M - Average apple mass. F - Average Magness-Taylor flesh firmness. 58 most sensitive condition for Paula Red apples and large apples had larger bruises than small apples. These variable values are shown in line 7 of Table 3.3 The ABD is shown in line 8, and is very close to the 12.7 mm diameter bruise which will down-grade an apple from Extra Fancy to Fancy. 3-5-2 HLBA_M2dsl_f0I_§Qlden_nslisiens_bnnlss The dependent and independent variables for the Golden Delicious apples are the same as for the Paula Red apples. There were a total of 58 cases used in the analysis. See Appendix A.3 for the complete statistical report. The resulting MLRA equation explained 56.7 percent (R2=.0567) of the variation in the average bruise diameter: ABD I -2.16 + 3.35DV + 0.0140M + 0.02356 - 0.0560D + 0.0704F Where: ABD - Average bruise diameter of 10 apples, mm DV - Velocity change, m/s M = Average apple mass, g G - Peak acceleration, g D - Days after harvest F - Average Magness-Taylor firmness, N Figure 3.38 shows the predicted bruise diameter versus the measured bruise diameter, with confidence belts for the predicted diameter placed at the 95 percent level. Again, the sensitivity of the model was tested similar to the Paula Red model. The initial mid-range values are shown on the first line of Table 3.4. These values yield an ABD of 10.14 mm. The results for low and high extreme variable values, lines 3 and 5, are shown in lines 4 and 6 of Table 3.4. 59 m: HON HGHQEMHQ QWMam UOHQMMOZ mamHUNV UOHUMUUHQ whom thfih moaamd msofiowaoa covaou AEEV Ems/45 mmamm Exam/m: 11 n? N— : o— m m _ LLLLLLLLLLLL x. nmmd H ._ .XLVnd + oh H > .. Im 10 In: I: INF s In? \\ 00c: oocooccoo Nmm I l 1.: \ 0c: co_mmo._mmm 803.5 2 Lo omoLo>< a. HEIJEIWVICI ESIREIB GELOIGBHd 60 Table 3.4 Bruise Diameter Sensitivity, Golden Delicious MLRA Model Independent Variable Variable and DV, M, G, D, F, ABD Status m/s gm 8'3 days N Midrange variable Value 0.78 142 90 3 77 ABD, average, mm 10.14 10.14 10.14 10.14 10.14 Minimum variable value 0.55 166 50 l 73 ABD, minimum, mm 9.37 9.81 9.20 10.26 9.86 Maximum variable value 1.02 196 130 12 81 ABD, maximum, mm 10.95 10.56 11.08 9.64 10.43 Maximum possible condition 1.02 196 130 l 81 Maximum ABD, mm 12.70 12.70 12.70 12.70 12.70 ABD - Average bruise diameter. 0 - Peak acceleration. DV - Velocity change. 0 - Days after harvest. M - Average apple mass. F - Average Magness-Taylor flesh firmness. 61 As with the Paula Red apples, varying the peak g level had the largest affect on the ABD. At 50 g ABD was 9.2 mm compared to the original 10.14 m. At 130, ABD was 11.08 mm. Velocity change and apple mass produced the second and third largest variation, respectively. When all variables were set to produce the maximum ABD, a bruise of 12.70 mm diameter was predicted, equal to the size which will down- grade an apple. The regression models formulated in this experiment will be useful for predicting apple bruising from data that is easily obtained from the IS and apples on the packing lines. As indicated by the R2 values and the graphs of the actual data, the variation in actual bruising at each peak G level was very high. This is more evident in the Golden Delicious apples than in the Paula Red apples. Thus, the Paula Red model is a better predictor. Much of this variation can be attributed to the properties of the fruit. Differences in mass, curvature, firmness and cell structure may cause comparable apples dropped from the same height to have different bruises. 3.6 W In order to compare the Golden Delicious MLRA model to some LRA models; two LRA models were formulated. The first model considered only the peak G levels used in the MLRA model and the second considered only the velocity changes used in the MLRA model. The comparison is only carried out for the Golden Delicious apples since they were the most 62 sensitive to bruising and showed the greatest variation. The model for bruise diameter versus peak G forces was as follows: ABD - 7.2 + 0.0356 . . . . . . . . . . . . . . . .[3.3] Where: ABD = Average bruise diameter, mm G - Peak acceleration, g This linear regression model had a correlation of r = 0.606, 2 - 0.367, as shown in Figure 3.39. giving an r The second LRA model considered only velocity change as follows: ABD - 5.8 + 6.0DV . . . . . . . . . . . . . . . . [3.4] Where: ABD 8 Average bruise diameter, mm DV - Velocity change, m/s This equation had a correlation of r - 0.620, giving an r2 = 0.384, as shown in Figure 3.40. In these models, peak G can explain 36.7 percent of the variance in bruise diameter , while velocity change can explain 38.4 percent of the variance. This can be compared to the R2 - 0.567 for the Golden Delicious MLRA model which explains 56.7 percent of the variance in average bruise diameter. From the above comparisons, it can be concluded that using only peak acceleration or only velocity change to predict average bruise diameter is insufficient. Instead, a complex set of relationships exist between impact and fruit characteristics that determine bruising. 63 moaamd msOAOHaon cocaou you m.o xmom msmuo> Mouoaafio omfishm ommuo>< mn.n Guzman mb x mos: mocootcoo Nmm I I - 0c: co_mmmtoom $655 or .6 000.53. a. . L0 I pt I O) I F F l I") I If) (1111.11) B3l3wv10 381088 3OV83AV 64 P; mOHQQ< 0:0«0aaoo cooaou Mom mononu >0H00H0> msmuo> Mouoacwo omwshm omnuo>¢ oe.n enough Am\Ev moz 0; ad md Pd 0.0 0.0 P L . L L L L L L L L W owed H ._ .xo.m + md u > 1P 1m I: In— . mos: cocooccoo Nmm I I - 0:: P5800501 In? momSLn or Lo emote}. L. r ) 8313WVIO 381088 3OV83AV (11.1w \ 4 . CONCLUB IONS The following conclusions are made from the research reported here: 1. Impacts experienced on apple packing lines are capable of producing accelerations ranging from 20 g to 130 9. Approximately 84 percent of the impacts measured on the apple packing lines were between 20 and 60 g. Velocity changes corresponding to these impacts ranged from 0.1 m/s to 4.5 m/s, with only 2 impacts above 3 m/s. 2. The threshold of visible surface bruising in Paula Red apples occurred at 80 g with large apples. All apples showed bruising at 100 g or higher. The threshold of bruising after peeling occurred at 40 g and 100 percent bruising occurred at 80 g or higher. The threshold of visible surface bruising in Golden Delicious apples occurred at 40 g with large apples. All apples displayed bruising at 60 g or higher. After peeling the apples had a bruising threshold of 30 g and all apples were bruised at 50 g or higher. The CA Golden Delicious apples did not display any bruising at any peak G level on any of the surfaces used. 3. Multiple linear regression models were constructed for predicting average bruise diameter on Paula Red apples 65 66 giving R2-0.848 and Golden Delicious apples giving R2-0.565. The multiple regression models were based on the groups of apples that demonstrated 100 percent bruising at a given G level. Two linear regression models were also constructed for Golden Delicious apples using only peak G's or velocity change. The LRA model using only peak G's explained 36.7 percent of the variation in bruise diameter, while velocity change explained 38.4 percent of the variation in bruise diameter. It was concluded that LRA models were not sufficient to predict bruise diameter. 5. mm RESEARCH Although this research did find the threshold of bruising of apples based on peak G levels, more research needs to be conducted to isolate the velocity change at which bruising starts to occur at each G level. As outlined in the results, neither the medium or large velocity change surfaces produced bruising. Further tests must be performed to find surfaces that will produce velocity changes which will identify the threshold for bruising. From this information, bruising can be predicted if the Peak G level and velocity change are known. Also there appears to be a large change in bruise volume with increasing peak G level. This bruise characteristic may explain bruise damage response more completely than bruise diameter alone. Future research can explore what conditions affect bruise volume and how it may be practically used to grade apples. 67 6 . APPENDICES A.1 Definition of the Coefficient of Determination 68 A.1 Definition of the Coefficient of Determination The coefficient of determination is the amount of variation in the dependent variable that can be explained by the independent variables. It may be calculated by the following general formula: Rz-W Total SS(Y) or: R2 - §§(gg§ 39 1) Total SS(X) Where: R2 - Coefficient of determination SS - Sum of squares X - Independent variable Y - Dependent variable A.2 Statistical Results for Paula Red Apples 69 A.2 Statistical Results for Paula Red Apples Days after harvest Drop height (not used) Peak G's Velocity change, m/s Mass, g Magness-Taylor firmness, N Average bruise diameter, mm Average bruise depth, mm (not used) Average bruise volume, ml (not used) DmxlOIUIIhOJNI-‘E The coefficient of determination was used in Chapter 3 of the text. Readers who desire additional results may find them in this appendix. 7O lStep 1 Variable Entered 4 M u l t i p 1 e R e g r e s s i o n A n a l y s i s Multiple R .738 F Change 47.791 R Square .544 R Square Change .544 Adjusted R Square .633 Sun of Squares Change 67.26466 Std. Err. of Est. 1.18637 Percent of SS Change 54.44 Date: 05/14/89 Time: 17:00:00 Regression Std. Err. Beta Std. Err. Student Coefficient Reg. Coeff. Weight Beta Weight T value Sig. B( 4) 12.430700 1.798137 .7378 .1067 6.91 .00 B( 0) -1.8366130 A n a l y s i s O f V a r i a n c e Degrees of Error Sum of Squares Freedom Mean Square F-test Sig. Regression 67.2646600 1 67.264660 Residual 56.2990700 40 1.4074770 47.79 .000 Total 123.663700 42 cases from file: lOOPN.PRN A N A L Y S I S O F R E S I D U A L S =22:==22:======28882882838:8:38888833238238823388882282222:: Number of positive residuals: 16 Largest positive residual: 2.86798 Number of negative residuals: 26 Largest negative residual: -2.47187 Number of sign runs: 9 Significance of sign runs test: .0001 Average absolute residual: .922671 Residual sum of squares: 56.2991 Residual mean square: 1.40748 Residual standard deviation: 1.18637 Durbin-Watson statistic: .548666 Auto-correlation coefficient: .712 *******#*tit$3*tfit*******$******#***¥**t*t**#*************** 71 lStep 2 Variable Entered 5 M u l t i p l e R e g r e s s i o n A n a l y s i s Multiple R .839 F Change -l.547 R Square .703 R Square Change .159 Adjusted R Square .688 Sum of Squares Change 19.64954 Std. Err. of Est. .969397 Percent of SS Change 15.90 Date: 05/14/89 Regression Std. Err. Beta Coefficient Reg. Coeff. Weight BI 4) 12.529710 1.469437 .7437 B( 5) .30454800E-01 .66601108-02 .3988 B( 0) -6.2854600 Time: 17:00:00 Std. Err. Student Beta Weight T value Sig. .0872 8.53 .00 .0872 4.57 .00 A n a l y s i s O f V a r i a n c e Degrees of Error Sum of Squares Freedom Mean Square F-test Sig. Regression 86.9142000 2 43.457100 Residual 36.6495400 39 .93973180 46.24 .000 Total 123.563700 42 cases from file: 100PN.PRN A N A L Y S I S O F R E S I D U A L 3 Number of positive residuals: Largest positive residual: Number of negative residuals: Largest negative residual: Number of sign runs: Significance of sign runs test: Average absolute residual: Residual sum of squares: Residual mean square: Residual standard deviation: Durbin-Watson statistic: Auto-correlation coefficient: 19 2.01608 23 -l.56996 9 .0001 .786469 36.6495 .939732 .969398 .617627 .675 ***#*#**#*t***#*it!**********#**$*******#***#**********#**** 72 istep 3 Variable Entered l M u l t i p l e R e g r e s s i o n A n a l y s i 3 Multiple R .893 F Change 3.594 R Square .797 R Square Change .094 Adjusted R Square .781 Sun of Squares Change 11.60917 Std. Err. of Est. .811761 Percent of SS Change 9.40 Date: 05/14/89 Time: 17:00:01 Regression Std. Err. Beta Std. Err. Student Coefficient Reg. Coeff. Weight Beta Weight T value Sig. B( 4) 11.834960 1.241572 .7024 .0737 9.53 .00 B( 5) .335205408-01 .56247202-02 .4390 .0737 5.96 .00 B( 1) -.10897720 .259635lE-01 -.3120 .0743 -4.20 .00 B( 0) -5.5264590 A n a l y s i s O f V a r i a n c e Degrees of Error Sun of Squares Freedom Mean Square F-test Sig. Regression 98.5233700 3 32.841120 Residual 25.0403700 38 .65895720 49.84 .000 Total 123.563700 42 cases from file: 100PN.PRN Number of positive residuals: Largest positive residual: Number of negative residuals: Largest negative residual: Number of sign runs: Significance of sign runs test: Average absolute residual: Residual sum of squares: Residual mean square: Residual standard deviation: Durbin-Watson statistic: Auto-correlation coefficient: 23 1.46660 19 -l.99221 15 .0233 .636357 25.0404 .658957 .811762 1.02939 .442 *ttit**********3********$****¥*****##*I****************#¥#*# 73 iStep 4 Variable Entered 6 M u l t i p 1 e R e g r e s s i o n A n a l y s i 3 Multiple R .908 F Change -6.l38 R Square .825 R Square Change .028 Adjusted R Square .806 Sum of Squares Change 3.454451 Std. Err. of Est. .763808 Percent of SS Change 2.80 Date: 05/14/89 Time: 17:00:01 Regression Std. Err. Beta Std. Err. Student Coefficient Reg. Coeff. Weight Beta Weight T value Sig. B( 4) 12.068420 1.172162 .7163 .0696 10.30 .00 B( 5) .33768720E-01 .5293432E-02 .4422 .0693 6.38 .00 B( 1) -.12495470 .2529676E-01 -.3577 .0724 -4.94 .00 B( 6) -.7508324OE-01 .3085586E-01 -.1743 .0716 -2.43 .02 B( 0) -.74439310 A n a l y s i s 0 f V a r i a n c e Degrees of Error Sum of Squares Freedom Mean Square F-test Sig. Regression 101.977800 4 25.494460 Residual 21.5859000 37 .58340280 43.70 .000 Total 123.563700 42 cases from file 100PN.PRN A N A L Y S I S O F R E S I D U A L S =2:=3=====8=88323828283288888388888883888===:===3=========== Number of positive residuals: 20 Largest positive residual: 1.55655 Number of negative residuals: 22 Largest negative residual: -1.55331 Number of sign runs: 15 Significance of sign runs test: .0217 Average absolute residual: .589138 Residual sum of squares: 21.5859 Residual mean square: .583403 Residual standard deviation: .763808 Durbin-Watson statistic: 1.17294 Auto-correlation coefficient: .380 *1ttt3*********##**#**¥*lttlttttt¥¥$fi¥tti$¥******##********* 74 1Step 5 Variable Entered 3 M u l t i p l e R e g r e s s i o n A n a l y s i a Multiple R .921 F Change R Square .848 R Square Change Adjusted R Square .827 Sum of Squares Change Std. Err. of Est. .721373 Percent of SS Change 2.852249 2.31 Time: 17:00:02 Date: 05/14/89 Regression Std. Err. Beta Std. Err. Student Coefficient Reg. Coeff. Weight Beta Weight T value Sig. B( 4) 3.0407330 4.011817 .1805 .2381 .76 .45 B( 5) .35350720E-01 .50448058-02 .4629 .0661 7.01 .00 B( 1) -.12285880 .23908118-01 -.3517 .0684 -5.14 .00 B( 6) -.78886530E-01 .2918685E-01 -.1831 .0678 -2.70 .01 B( 3) .57389510E-01 .2451313E-Ol .5595 .2390 2.34 .02 B( 0) .87464130 A n a l y s i s 0 f V a r 1 a n c e Degrees of Error Sum of Squares Freedom Mean Square F-test Sig. Regression 104.830000 5 20.966010 Residual 18.7336700 36 .52037960 40.29 .000 Total 123.563700 42 cases from file: 100PN.PRN A N A L Y S I S O F R E S I D U A L S =2=2===2222332832::33888233382833888388=8====S=========322:: Number of positive residuals: 24 Largest positive residual: 1 34493 Number of negative residuals: 18 Largest negative residual: -1.69029 Number of sign runs: 18 Significance of sign runs test: .1635 Average absolute residual: .533213 Residual sum of squares: 18.7337 Residual mean square: .520380 Residual standard deviation: .721373 Durbin-Watson statistic: 1.21738 Auto-correlation coefficient: .360 ***t*tttiIIttt838**tt***#******I¥*******¥##****************** A.3 statistical Results for Golden Delicious Apples 75 A.3 Statistical Results for Golden Delicious Apples Days after harvest Drop height (not used) Peak G's Velocity change, m/s Mass, g Magness-Taylor firmness, N Average bruise diameter, mm Average bruise depth, mm (not used) Average bruise volume, ml (not used) somqmmauaH-IE The coefficient of determination was used in Chapter 3 of the text. Readers who desire additional results may find them in this appendix. lStep l M u l t i p l e 76 Variable Entered 4 (Forced Variable) R e g r e s s i o n A n a 1 y s i s Multiple R .620 F Change 34.880 R Square .384 R Square Change .384 Adjusted R Square .373 Sum of Squares Change 33.11325 Std. Err. of Est. .974348 Percent of SS Change 38.38 Date: 05/26/89 Time: 12:25:00 Regression Std. Err. Beta Std. Err. Student Coefficient Reg. Coeff. Weight Beta Weight T value Sig. B( 4) 6.0223430 1.019715 .6195 .1049 5.91 .00 B( 0) 5.7725400 A n a l y s i s 0 f V a r i a n c e Degrees of Error Sum of Squares Freedom Mean Square F-test Sig. Regression 33.1132400 1 33.113240 Residual 53.1638000 56 .94935360 34.88 .000 Total 86.2770800 58 cases from file 1000N.PRN A N A L Y S I S 0 F R E S I D U A L S 3::2::=2:3S88388888338823833828332833282322:3233828223323232 Number of positive residuals: 25 Largest positive residual: 2.56467 Number of negative residuals: 33 Largest negative residual: -1.94265 Number of sign runs: ‘ 25 Significance of sign runs test: .1430 Average absolute residual: .767856 Residual sum of squares: 53.1638 Residual mean square: .949354 Residual standard deviation: .974348 Durbin-Watson statistic: 1.15957 Auto-correlation coefficient: .415 *#*******Iii**********$#************************************* 77 IStep 2 Variable Entered 3 (Forced Variable) M u l t i p 1 e R e g r e s s i o n A n a l y s i 8 Multiple R .620 F Change -17.745 R Square .384 R Square Change ' .000 Adjusted R Square .361 Sum of Squares Change .7034501E-02 Std. Err. of Est. 983101 Percent of SS Change .01 Date: 05/26/89 Time: 12:25:01 Regression Std. Err. Beta Std. Err. Student Coefficient Reg. Coeff. Weight Beta Weight T value Sig. B( 4) 5.6330380 4.677782 .5795 .4812 1.20 .23 B( 3) .23712660E-02 .2779467E—01 .0411 .4812 .09 .93 B( 0) 5.8525020 A n a l y s i s 0 f V a r i a n c e Degrees of Error Sum of Squares Freedom Mean Square F-test Sig. Regression 33.1202700 2 16.560140 Residual 53.1567700 55 .96648680 17.13 .000 Total 86.2770800 58 cases from file: 1000N.PRN A N A L Y S I S O F R E S I D U A L S :2:3232:2333:=33332323833:28382283838888:883322218233:======= Number of positive residuals: 24 Largest positive residual: 2.57709 Number of negative residuals: 34 Largest negative residual: -1.95963 Number of sign runs: 23 Significance of sign runs test: .0617 Average absolute residual: .765349 Residual sum of squares: 53.1568 Residual mean square: .966487 Residual standard deviation: .983101 Durbin-Watson statistic: 1.15799 Auto-correlation coefficient: .416 *********#**#****************#****#**t*****************##*** 78 Step 3 Variable Entered 5 M u l t i p l e R e g r e s s i o n A n a l y s i 3 Multiple R .698 F Change -.075 R Square .487 R Square Change .103 Adjusted R Square .458 Sum of Squares Change 8.860987 Std. Err. of Est. .905700 Percent of 88 Change 10.27 Date: 05/26/89 Regression Std. Err. Beta Coefficient Reg. Coeff. Weight B( 4) 5.1405150 4.312099 .5288 B( 3) .98058840E-02 .2570609E-01 .1698 B( 5) .185328308-01 .5638780E-02 .3303 B( 0) 2.3445610 Std. Time: 12:25:02 Err. Student Beta Weight T value Sig. .4436 1.19 .24 .4450 .38 .70 .1005 3.29 .00 -------------------‘---------------——------------------—’---------- Degrees of Error Sum of Squares Freedom Mean Square F-test Sig. Regression 41.9812800 3 13.993760 Residual 44.2957600 54 .82029190 17.06 .000 Total 86.2770800 58 cases from file: 1000N.PRN A N A L Y S I S O F R E S I D U A L S =3=2===2:2:=22:2:22:23:3888::228:3:==3=================332:: Number of positive residuals: 28 Largest positive residual: 2.04892 Number of negative residuals: 30 Largest negative residual: -1.99670 Number of sign runs: 21 Significance of sign runs test: .0124 Average absolute residual: .723745 Residual sum of squares: 44.2958 Residual mean square: .820292 Residual standard deviation: .905700 Durbin-Watson statistic: 1.05363 Auto-correlation coefficient: .470 ******##***********#*****¥*****I**************************** 79 lStep 4 M u 1 t i p l e Variable Entered 6 R e g r e s s i o n A n a l y s i 3 Multiple R .730 F Change -1.973 R Square .532 R Square Change .046 Adjusted R Square .497 Sum of Squares Change 3.953396 Std. Err. of Est. .872455 Percent of SS Change 4.58 Date° 05/26/89 Time: 12:25:02 Regression Std. Err. Std. Err. Student Coefficient Reg. Coeff. Beta Weight T value Sig. B( 4) 3.7939750 4.195628 .4316 .90 .37 B( 3) .18514160E-01 .2505559E-01 .4338 .74 .46 B( 5) .13863470E-01 .5805369E-02 .1035 2.39 .02 B( 6) .63015350E-01 .2765057E-01 .1026 2.28 .03 B( 0) -1.6558710 A n a l y s i s 0 V a r i a n c e Degrees of Error Sum of Squares Freedom Mean Square F-test Sig. Regression 45.9346500 4 11.483660 Residual 40.3423800 53 .76117710 15.09 .000 Total 86.2770800 58 cases from file: 1000N.PRN A N A L Y S I S O F R E S I D U A L S =====::=====:=============================================== Number of positive residuals: Largest positive residual: Number of negative residuals: Largest negative residual: Number of sign runs: Significance of sign runs test: Average absolute residual: Residual sum of squares: Residual mean square: Residual standard deviation: Durbin-Watson statistic: Auto-correlation coefficient: 25 2.11713 33 -2.00934 23 .0540 .671524 40.3424 .761177 .872455 1.25461 .363 t**t***#***ttltfittttttttttlittttt***##*****#*********#****#* 80 lStep 5 Variable Entered 1 M u l t i p l e R e g r e s s i o n A n a l y s i 3 Multiple R .757 F Change -1.l65 R Square .572 R Square Change .040 Adjusted R Square .531 Sum of Squares Change 3.450067 Std. Err. of Est. .842299 Percent of SS Change 4.00 Date: 05/26/89 Time: 12:25:03 Regression Std. Err. Beta Std. Err. Student Coefficient Reg. Coeff. Weight Beta Weight T value Sig. B( 4) 3.3565320 4.055464 .3453 .4172 .83 .41 B( 3) .23514610E-01 .2429562E-01 .4071 .4206 .97 .34 B( 5) .i4012830E-01 .5605122E-02 .2498 .0999 2.50 .02 B( 6) .70446320E-01 .2690670E-01 .2615 .0999 2.62 .01 B( 1) -.56043950E-01 .2541449E-01 -.2055 .0932 -2.21 .03 B( 0) -2.1634130 A n a l y s i s O f V a r i a n c e Degrees of Error Sum of Squares Freedom Mean Square F-test Sig. Regression 49.3847400 5 9.8769470 Residual 36.8923100 52 .70946760 13.92 .000 Total 86.2770800 58 cases from file: 1006N.PRN A N A L Y S I S O F R E S I D U A L S 23:2:23.13333882323383838B8:333383333322:8238338388322:2:2:=3: Number of positive residuals: 30 Largest positive residual: 2.02768 Number of negative residuals: 28 Largest negative residual: -2.26639 Number of sign runs: 23 Significance of sign runs test: .0432 Average absolute residual: .633576 Residual sum of squares: 36.8923 Residual mean square: .709468 Residual standard deviation: .842299 Durbin-Watson statistic: 1.34584 Auto-correlation coefficient: .318 *#*********#*#********t**#****#****#********************¥*** 3.1 Data for Paula Red Apples 81 3.1 Data for Paula Red Apples Days after harvest Drop height (not used) Peak G's Velocity change, m/s Mass, 9 Magness-Taylor firmness, N Average bruise diameter, mm Average bruise depth, mm (not used) Average bruise volume, ml (not used) 82 1 2 3 4 5 6 7 8 9 l 1.8 101 0.83 113.8 72.28 6.01 0.89 16.29 1 2 110.4 0.85 115.1 68.41 7.2 1.27 28.92 1 2.3 121.2 0.9 117.62 67.08 7.62 1.1 29.82 1 3 128.5 1.02 117.2 70.42 9.93 1.49 62.99 1 1.7 90.3 0.78 144.1 69.84 7.95 1.2 32.98 1 1.8 101 0.83 139.96 70.28 9.29 1.59 58.62 1 2 110.4 0.85 139.66 70.73 9.91 1.85 75.64 1 2.3 121.2 019 136.06 67.84 9.88 1.5 59.78 1 3 128.5 1.02 136.42 66.95 11.57 2.4 140.52 1 1.4 80.2 0.71 165.48 62.28 9.41 0.66 30.29 1 1.7 90.3 0.78 170.52 64.19 9.2 1.17 43.28 1 1.8 101 0.83 170.28 66.19 10.29 1.56 70.37 1 2 110.4 0.85 180.34 63.39 11.06 1.77 91.77 1 2.3 121.2 0.9 171.16 63.52 12.22 2.42 157.02 1 3 128.5 1.02 179.6 67.84 12.78 2.79 194.89 3 1.4 80.2 0.71 116.88 67.97 6.18 0.64 10.78 3 1.7 90.3 0.78 119.96 65.30 7.29 0.94 21.72 3 1.8 101 0.83 118.83 64.10 7.46 1.15 28.08 3 2 110.4 0.85 115.92 68.19 9.49 1.17 41.54 3 2.3 121.2 0.9 113.02 56.85 9.41 1.12 42.71 3 3 128.5 1.0 118.18 55.07 10.71 1.74 83.7 3 1.7 90.3 0.78 144.62 66.06 7.62 0.91 23.6 3 1.8 101 0.83 141.44 69.53 8.87 1.41 47.84 3 2 110.4 0.85 138.64 59.61 9.87 1.88 78.18 3 2.3 121.2 0.9 142.8 72.28 8.92 1.09 37.21 3 3 128.5 1.02 145.82 65.83 10.23 1.25 53.81 3 3 128.5 1.02 178.14 70.06 10.67 1.23 59.68 12 1.8 101 0.83 124.84 63.61 7.55 1.19 30.48 12 2 110.4 0.85 119.02 62.72 8.18 1.41 42.56 12 2.3 121.2 0.9 117.2 71.30 8.41 1.69 53.53 12 3 128.5 1.0 120.74 63.83 9.53 2.04 86.82 12 1.2 71.3‘ 0.62 141.58 64.50 5.58 0.82 11.33 12 1.4 80.2 0.71 140.9 56.94 6.39 1.07 20.79 12 1.7 90.3 0.78 141.64 62.94 7.18 1.27 27.88 12 1.8 101 0.83 141.14 64.50 7.33 1.27 28.34 12 3 128.5 1.02 147.42 64.94 10.44 1.92 91.49 12 1.4 80.2 0.71 170.78 66.72 6.26 0.75 12.48 12 1.7 90.3 0.78 174.22 65.17 7.63 1.15 30.93 12 1.8 101 0.83 169.22 60.18 7.97 1.4 42.74 12 2 110.4 0.85 167.52 64.63 8.49 1.5 48.75 12 2.3 121.2 0.9 179.66 66.86 10.35 1.9 84.93 12 3 128.5 1.02 171.6 67.39 10.69 2.11 102.47 8.2 Data for Golden Delicious Apples 8.2 83 Data for Golden Delicious Apples Days after harvest Drop height (not used) Peak G's Velocity change, m/s Mass, g Magness-Taylor firmness, N Average bruise diameter, mm Average bruise depth, mm (not used) Average bruise volume, ml (not used) 84 1 2 3 4 5 6A 7 8 9 1 1.2 71.3 0.62 143.3 81.98 8.6 1.42 44.24 1 1.4 80.2 0.71 145.76 76.95 9.98 1.83 75.72 1 1.7 90.3 0.78 145.54 83.63 10.04 1.82 75.51 1 1.8 101 0.83 142.52 77.84 10.07 1.38 57.98 1 2 110.4 0.85 143.28 77.18 10.96 1.68 81.71 1 2.3 121.2 0.9 144.24 77.84 11.52 2.09 115.62 1 3 128.5 1.02 142.18 78.73 11.83 2.57 153.75 1 1.2 71.3 0.62 165.48 79.98 9.51 2 76.63 1 1.4 80.2 0.71 165.48 80.07 9.41 2 77.82 1 1.7 90.3 0.78 164.78 82.20 9.36 1.99 75.41 1 1.8 101 0.83 166.64 78.07 10.28 1.91 83.83 1 2 110.4 0.85 165.38 75.17 9.44 1.63 63.8 1 2.3 121.2 0.9 166.58 78.51 9.25 1.37 46.87 1 3 128.5 1.02 166.16 78.96 11.35 2.16 120.59 1 1 60.8 0.61 189.2 80.29 10.23 1.59 67.42 1 1.2 71.3 0.62 191.12 70.95 9.06 1.85 65.52 1 1.4 80.2 0.71 193.1 75.17 9.83 1.68 66.79 1 1.7 90.3 0.78 197 74.95 9.98 1.82 76.19 1 1.8 101 0.83 198.84 72.28 9.75 1.5 58.66 1 2 110.4 0.85 191.12 75.75 10.13 0.63 78.07 1 2.3 121.2 0.9 194.12 75.31 11.89 1.91 110.8 1 3 128.5 1.02 194.34 71.84 13.78 2.2 169.55 3 1.7 90.3 0.78 139.5 77.40 9.69 1.54 58.99 3 1.8 101 0.83 143.54 76.95 10.79 1.86 90.17 3 2 110.4 0.85 142.88 75.84 12.49 1.07 132.93 3 2.3 121.2 0.9 142.26 77.75 11.5 1.97 107.17 3 3 128.5 1.02 141.48 82.65 10.99 2.01 108.32 3 1.2 71.3 0.62 165.32 81.98 10.37 1.65 72.57 3 1.4 80.2 0.71 164.82 85.41 10.66 1.59 74.37 3 1.7 90.3 0.78 165.3 82.20 11.34 1.47 78.16 3 1.8 101 0.83 164.26 82.43 11.34 1.71 89.43 3 2 110.4 0.85 164.06 79.98 10.85 1.42 68.77 3 2.3 121.2 0.9 164.14 78.20 12.36 2.46 159.27 3 3 128.5 1.02 165.08 82.51 11.79 2.64 156.54 3 0.8 50.5 0.55 197.9 80.20 10.57 1.37 64.77 3 1 60.8 0.61 196 82.65 10.02 1.35 57.07 3 1.2 71.3 0.62 195.16 82.29 9.44 1.21 45.69 3 1.4 80.2 0.71 196.74 85.54 9.87 1.27 55.86 3 1.7 90.3 0.78 195.92 85.18 11.58 1.4 75.29 3 1.8 101 0.83 194.38 82.51 12.65 1.68 110.03 3 2 110.4 0.85 197.12 84.29 12.03 1.49 91.22 3 2.3 121.2 0.9 190.98 88.43 13.05 1.94 133.32 3 3 128.5 1.0 193.34 87.10 14.48 2.56 221.64 12 1.7 90.3 0.78 140.08 76.29 9.37 1.11 94.71 12 1.8 101 0.83 143.98 71.17 9.08 1.2 91.31 12 2 110.4 0.85 140.86 72.51 9.83 1.4 119.27 12 2.3 121.2 0.9 142.08 69.97 10.28 1.64 162.25 12 3 128.5 1.02 143.44 73.40 11.12 1.66 200.45 12 2 110.4 0.85 163.72 79.71 10.96 1.23 150.14 12 2.3 121.2 0.9 160.66 76.87 10.27 1.39 143.97 12 3 128.5 1.0 167.04 81.98 11.53 1.54 208.3 85 1 3 4 5 6 7 8 9 12 1.2 71.3 0.62 192.74 87.54 9.55 0.95 83.75 12 1.4 80.2 0.71 193.92 84.43 9.44 0.79 63.77 12 1.7 90.3 0.78 193.74 85.76 9.9 1.12 104.57 12 1 8 101 0.83 192.66 83.63 10.23 1.08 115.82 12 2 110.4 0.85 196.86 85.49 12.01 1.14 155.45 12 2 3 121.2 0.9 196.66 83.09 11.87 1.35 185.24 12 3 128.5 1.02 189.8 85.76 11.68 1.67 229 7 . REFERENCES 10. REFERENCES Bartram, R., J. Fountain, K. Olsen, and D. O'Rourke. 1983. Washington State apple condition at retail, 1982-83 (Eating Quality). Free. Wash. State Hort. Assoc. 79:36-46. Brown, G. R., C. L. Burton, S. A. Sarfent, N. L. Shutle Pason. 1987. Apple Packing Line Damage Assessment. ASAE Paper No. 87-6516. ASAE, St. Joseph, MI. Finney, Jr. E. E.and D. R. Massie. 1975. Instrumentation for testing the Responce of Fruits to Mechanical Damage. TRANSACTION of the ASAE 18(6):1184- 1187,1192. Pluck, R. C. and E. M. Ahmed. 1973. Impact Testing of Fruits and Vegetables. TRANSACTIONS of the ASAE 16(4):660-666. - Goldsmith. Impact, the Theory and Physical Behavior of Colliding Solids. 1960. Edward Arnold Publishers Ltd., London. 369 p. Held, W. R., A. Osterloh, and G. Schauer. 1974. Bedeutung und Ergebinsse der Entnahme von Einlagerprben. Gartenbau. 21(7):203-204. Lichtensteiger, M. J., R. G. Holmes, M. Y. Mandy and J. L. Blaisdell. 1988. Impact Parameters of Spherical Viscoelastic Objects. TRANSACTIONS of the ASAE 31(2): 595-602. . Mohsenin, N. N. 1970. Physical Properties of Plant and Animal Materials. Garden and Breach, Science Publishers, Inc., New York NY. Peleg,K. A Mathematical Model of Produce Damage Mechanisms. 1984. TRANSACTIONS of the ASAE 27(1):287- 293. Schoorl D., J. E. Holt. 1980. Bruise Resistance Measurement in Apples. Journal of Texture Studies 11(4):389-394. 86 11. 12. 87 Siyami S., G. K. Brown, G. J. Burgess, J. B. Gerrish, B. R. Tennes, C. L. Burton and R. H. Zapp. 1988. Apple Impact Bruise Prediction Models. TRANSACTIONS of the ASAE 31(4):1038-1046. Zapp, R., S. Ehlert, G. Brown, P. Armstrong, 8. Sober. 1989. Advanced Instrumented Sphere (IS) for Impact Measurements. ASAE Paper No. 89-6046. ASAE, St. Joseph, MI. "7111111111111!”@111)“