1. Nondestructive Impact and Acoustic Testing For Quality Assessment of Apples by Itzhak Shmulevich, Naftali Galili and M. Scott Howarth A G E NG 2002 Budapest, Hungary June 30-July 4, 2002

2. The Department of Agricultural Engineering Technion-Israel Institute of Technology

3. Presentation outline u Introduction - firmness quality nondestructive measurements; u Impact technique vs. acoustic technique; u Experimental report on various fruits; u Results; u Discussion; u Conclusions.

4. QUALITY ASSESSMENT

5. Quality Factors of Agricultural Products u Appearance - visual u Texture - feel u Flavor - taste and smell u Safety u Nutritive Value

6. Texture u Texture can be defined by subjective terms such as: Firmness Mealiness, Hardness, Softness, Brittleness, Ripeness, Toughness, Chewiness, Smoothness, Crispness, Oiliness, Springiness, Toughness, Fibrousness, or Juiciness etc. Firmness Mealiness, Hardness, Softness, Brittleness, Ripeness, Toughness, Chewiness, Smoothness, Crispness, Oiliness, Springiness, Toughness, Fibrousness, or Juiciness etc.

7. Quality Sensing in Commercial Settings Requirements u Nondestructive u External and internal properties u Accuracy u Speed (5-15 fruits/sec) u Recognize inherent product variability

8. NONDESTRUCTIVE SENSOR TECHNOLOGY

9. NondestructiveFirmness Measurement Techniques Nondestructive Firmness Measurement Techniques u Fruit Response to Force u Detection by Impact Force u Forced Vibrations u Mechanical or Sonic Impulse u Ultrasonic Techniques u Indirect Firmness Measurement

10. Research Objective Research Objective  The motivation of the present work is to develop a fast nondestructive method for quality firmness testing of apples.  The general objective of the research is to compare sensing the fruit firmness using low mass impulse excitation tothe acoustic response for quality assessment of apples.

11. Texture Acoustic vs. Impact

12.  Relationship between turgor pressure and tissue rigidity E=3.6 p +2.5 x10 7 [ dynes/cm 2 ]  Modulus of Elasticity

13. NondestructiveFirmness Measurement Nondestructive Firmness Measurement Impact Force Technique

14. Quality Detection by Impact Force Time [ msec ] Force [N]

15. Low-Mass Impact (LMI) Firmness

16. IQ Firmness IQ TM Firmness Tester Sinclair International LTD

17. NondestructiveFirmness Measurement Nondestructive Firmness Measurement Acoustic Technique

18. Firmalon Prototype

19. Firmalon

20. Typical Acoustic Fruit Response Frequency Domain Time Domain

21. Microphone Based System for Acoustic Firmness Testing Source: J. De Baerdemaeker

22. Comparison Between Two Acoustic Test Methods Comparison Between Two Acoustic Test Methods Method-A: Microphone Method-A: Microphone Method-B: Piezoelectric-Film Sensor Method-B: Piezoelectric-Film Sensor Source: N. Galili & J. De Baerdemaeker

23. Acoustic Firmness Sensor A F S TM Source: AWETA

24. DestructiveFirmness Measurement Destructive Firmness Measurement

25. d sec N FpFp TpTp tdtd Quality Detection by Impact Force Chen. P (1996), Farabee (1991) Delwiche (1989,1991), Nahir et al. (1986 )

26. Quality Detection by Impact Source: Shmulevich et. al. ( 2000 )

27. The Acoustic Parameters of a Fruit Natural frequencies and firmness index - FI u Natural frequencies and firmness index - FI FI = f 2 m 2/3 {10 4 kg 2/3 s -2 } where: f - first spherical resonant frequency m - fruit’s mass. m - fruit’s mass.  Damping ratio -  u The centeroid of the frequency response - f c

28. Parameters extracted from the measurements Parameters extracted from the measurements Low-Mass Impulse parameters: Low-Mass Impulse parameters: C1 = Fp/Tp; C2 = F p /T p 2 ;  (-20); and fc(in). IQ, IT Acoustic parameters : f 1 ; FI ; and fc; Destructive parameters: E ; MT.

29. Method and Materials Three apples cultivers; Shelf life conditions: 20 0 C 50%RH; 25 fruits were tested daily both 25 fruits were tested daily both nondestructively and destructively; nondestructively and destructively; Destructive test - (MT, E’); Destructive test - (MT, E’);.

30. Results

31. Results - Rubber Spheres

36. Typical Acoustic Fruit Response Frequency Domain Time Domain

37. Golden Delicious n=270

38. Pearson linear correlation between the nondestructive and destructive tests, n=270 Golden Delicious -Apple, Correlation is significant at the 0.05 level

39. Results -Golden Delicious

41. Starking Apples n=270

42. Pearson linear correlation between the nondestructive and destructive tests, n=270 Starking -Apple, Correlation is significant at the 0.05 level

43. Results-Starking Apples

45. Granny Smith n=270 n=270

46. Pearson linear correlation between the nondestructive and destructive tests, n=270 Granny Smith -Apple, Correlation is significant at the 0.05 level

47. Results- Granny Smith

49. Summary The impact firmness parameter IQ and IT of The impact firmness parameter IQ and IT of the calibration balls, obtained by the instrumented hammer and the Sinclair sensor, were very close (R-average = 0.992), while the Sinclair sensor predicted slightly better the elastic modulus of the balls (R = 0.9992).

50. Summary (Cont,) The elastic modulus E’, which is the physical measurement of firmness, was predicted well by the IQ and IT impact parameters in Golden Delicious apples (R- average = 0.917). The elastic modulus E’, which is the physical measurement of firmness, was predicted well by the IQ and IT impact parameters in Golden Delicious apples (R- average = 0.917). The acoustic firmness index FI was equivalent to IQ in Golden Delicious, but improved the prediction of E’ in Starking and Granny Smith apples (R-average = 0.931). The acoustic firmness index FI was equivalent to IQ in Golden Delicious, but improved the prediction of E’ in Starking and Granny Smith apples (R-average = 0.931).

51. Summary (Cont.) High correlation was found between the individual readings of IT and IQ in all apples (R = 0.9867). Hence, the simple IT algorithm may replace the IQ algorithm, if quick firmness calculation is needed to increase the present operation speed of the low-impact sorter (600 fruit per minute per lane). High correlation was found between the individual readings of IT and IQ in all apples (R = 0.9867). Hence, the simple IT algorithm may replace the IQ algorithm, if quick firmness calculation is needed to increase the present operation speed of the low-impact sorter (600 fruit per minute per lane).

52. Summary (Cont.) The changes in the penetration force MT (the yield strength of fruit tissue) during the test period were very low, and their correlation with the elastic modulus and firmness parameters of all apples’ varieties was poor (R < 0.60). The changes in the penetration force MT (the yield strength of fruit tissue) during the test period were very low, and their correlation with the elastic modulus and firmness parameters of all apples’ varieties was poor (R < 0.60).

53. Summary (Cont.) These findings in the tested apple varieties indicate that the acoustic firmness index FI, if successfully applied in a sorting line, may improve the sorting capacity of a multi-sensor (FI and IQ) automatic machine. These findings in the tested apple varieties indicate that the acoustic firmness index FI, if successfully applied in a sorting line, may improve the sorting capacity of a multi-sensor (FI and IQ) automatic machine.

54. Thanks For Your Attention