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Thermographic surface quality evaluation of apple
Journal of Food Engineering 77 (2006) 162–168 www.elsevier.com/locate/jfoodeng
Thermographic surface quality evaluation of apple E.A. Veraverbeke a, P. Verboven a, J. Lammertyn a,*, P. Cronje a, J. De Baerdemaeker b, B.M. Nicolaı¨ a a
Department of Agro-Engineering and Economics, Flanders Centre/Laboratory of Postharvest Technology, Katholieke Universiteit Leuven, William de Croylaan 42, B-3001 Heverlee, Belgium b Laboratory for Agricultural Machinery and Processing, Katholieke Universiteit Leuven, Kateelpark Arenberg 30, 3001 Heverlee, Belgium Received 9 August 2004; accepted 18 June 2005 Available online 31 August 2005
Abstract Thermographic IR-imaging was used as a non-destructive tool to evaluate the surface quality of apples. Experiments were carried out on apple fruit of two different cultivars (Jonagored and Elshof) picked at two different picking dates (early and late). First, the emissivity of the apple skin was determined as 0.96 for both cultivars. Next, recordings were made of individual fruit of both cultivars cooled from 20 C to 12 C. In this experiment Elshof apples had a faster cooling rate and lower temperature than Jonagored apples. Finally, a storage experiment was carried out under standardised conditions with quality assessment after 4 and 8 months of CA storage and at each storage period after 0, 1, and 2 weeks of shelf life. Next to the determination of general quality parameters (weight, diameter), thermographic images of the surface of each apple were obtained. Temperature profiles were recorded for batches of four fruits and of all individual fruit within this batch while they were cooled from 12 C to 1 C. The surface cooling rate and final fruit surface temperature were estimated. All data were calibrated for background temperature and corrected for apple dimensions and convection coefficients. ANOVA analysis showed significant differences between both cultivars, picking dates and storage conditions for the cooling rate. The final surface temperature differed significantly between different storage and shelf life periods. Only the difference in cooling rate with a faster cooling for Elshof than for Jonagored was explained in terms of wax structural characteristics and transpiration rates. The results also show the importance of data correction. 2005 Elsevier Ltd. All rights reserved. Keywords: Apple; Wax; Surface quality; Thermography
1. Introduction Apples are naturally covered with an epicuticular wax layer, which protects the fruit from stress factors, such as moisture loss, mechanical damage, and microbiological infections. This wax layer also positively contributes to the visual quality of the produce by maintaining a good surface quality. An excessive wax production or chemical and structural changes in the wax during stor*
Corresponding author. Tel.: +32 16 32 23 76; fax: +32 16 32 29 55. E-mail address: [email protected] (J. Lammertyn). 0260-8774/$ - see front matter 2005 Elsevier Ltd. All rights reserved. doi:10.1016/j.jfoodeng.2005.06.059
age and shelf life can, however, contribute negatively to the organoleptic or visual quality of the fruit. In this case the wax layer gives the fruit an unpleasant bloom or turns the surface greasy and sticky. Of some apple cultivars, such as Jonagored, it is known that they are more susceptible to the development of greasy surfaces than other cultivars, such as Elshof. As visual quality constitutes one of the most important components determining the consumer demand and the economic value of the produce, optimisation of the wax layer quality is continuously aimed for. In some cases, artificial waxes, such as Carnauba and Shellac are applied (Glenn, Rom, Rasmussen, & Poovaiah, 1990)
E.A. Veraverbeke et al. / Journal of Food Engineering 77 (2006) 162–168
but more often optimal storage conditions combined with cultivars that have a low susceptibility to greasiness development are searched for. In previous research, the wax layer structure (Veraverbeke, Van Bruaene, Van Oostveldt, & Nicolaı¨, 2001a) and composition (Veraverbeke, Lammertyn, Saevels, & Nicolaı¨, 2001b) of three different apple cultivars were studied based on microscopic and gas chromatographic analysis. This allowed discrimination of the different apple cultivars based on their surface characteristics and related moisture loss during storage. Contrary to moisture loss, greasiness development is more difficult to quantify and until now no sufficient method exists to analyse greasiness. A full chemical analysis is also too complicated for routine evaluations. More research is, therefore, required to quantify wax and surface quality based on objective and non-destructive measurements. Thermography is an image processing technique, which transforms thermal radiation, recorded by a camera, into a thermographic image or thermogram. A thermogram is a representation of the specific temperature distribution at the object surface. Thermography is a very fast measuring technique, which allows measurement on moving objects. It also is a non-contact and non-destructive tool so that no mechanical injury or contamination of the study object can occur during measurement. Therefore, this technique has already found many applications as a diagnostic monitoring tool in industrial and medical settings (Jones, 1998; Thomas, Jones, & Donne, 2000). In biological sciences, thermography is used for amongst others stomatal conduction measurements (Jones, 1999; Prytz, Futsaether, & Johnsson, 2003), assessment of the uptake of herbicides (Chaerle et al., 2003) tracing of plant diseases and plant stress (Chaerle & Van der Straeten, 2000, 2001), plant freezing studies (Pearce, 2001) and heat production measurements (Lamprecht, Schmolz, Blanco, & Romero, 2002). Infrared thermography is also used as a non destructive analysis tool for measuring or controlling fruit quality. Studies have been carried out to use thermography for bruise detection on apple and tomato surfaces before the actual bruise is visible to the eye (Vereycken, 2002). Workmaster, Palta, and Wisniewski (1999) used infrared video thermography for the study of ice nucleation and propagation in cranberry uprights and fruit. In the same line, thermography was applied to test the use of a hydrophobic particle film as a barrier to extrinsic ice nucleation in tomato plants (Wisniewski, Glenn, & Fuller, 2002). For apple production, thermal imaging was used to estimate the number and diameter of apple fruit in an orchard during the growing season for yield prediction (Stajnko, Lakota, & Hocˇevar, 2004). In this work thermography was used as an alternative for colour measurements when canopy and fruit have about the same colour. Determination coefficients
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(R2) from 0.83 to 0.88 were obtained between manually measured fruit numbers and estimated fruit numbers based on a fruit detection algorithm. Related to surface and wax quality analysis this technique was used for the control of surface drying time of citrus fruit. Oranges were dried after washing and coating with an artificial wax. Strict control of the drying time is necessary to prevent sensory losses or a decrease in fresh fruit shelf life. With thermography the drying process was evaluated in terms of wax amount, air velocity and temperature. Higher values of each of these parameters resulted in shorter drying times (Fito, Ortola, De los Reyes, Fito, & De los Reyes, 2004). The objective of this work was to evaluate the potential of IR thermography for surface quality analysis of apple. It was assumed that differences in surface or wax quality (number of cracks, number of lenticels, level of wax smoothing,. . .) result in a different surface temperature through differences in transpiration and evaporation at the surface.
2. Materials and methods 2.1. Fruit Apples were harvested at the Proeftuin voor Pit—en Steenfruit in Velm (Belgium) at 3 September 2002 (early) and 9 September 2002 (late) for Elshof and at 16 September 2002 (early) and 23 September 2002 (late) for Jonagored. All fruit was stored in controlled atmosphere (CA) containers of about 1 m3 (Elshof: 2% O2, <1% CO2, 1 C, 95% RH; Jonagored: 1% O2, 2.5% CO2, 1 C, 95% RH) until analysis. After different periods of CA storage (4 and 8 months) apples were also stored at shelf life conditions for 0, 1 and 2 weeks in an incubator at 20 C. The relative humidity was not controlled. 2.2. Camera setup Two different types of cameras and camera setups were tested. A first type was used for the determination of the emissivity of apple and for measurements on individual apples. A second type was used for the recording of batches of apples in a storage experiment. For the emissivity and individual fruit measurements a camera setup developed at the Laboratory for Agricultural Machinery and Processing of the K. U. Leuven (Belgium) was used. This setup contained a ThermaCAMTMSC3000 camera (FLIR systems) provided with a lens with a resolution of 100 lm and a photon detector. The latter was cooled to minimise noise resulting from the thermal excitation of charged particles of the detector itself. The object to be measured was placed in a rusty iron cylinder in front of a cooled and also
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rusty iron background. This allowed a homogeneous distribution of the radiation over the surface with a clear difference in radiation between object and background. Cooled and rusty iron is characterised by a low emissivity and reflection. An automatic calibration for the ambient and camera temperature and for the air humidity was provided. Photon currents were recorded with the camera and analysed with ThermaCamTM Researcher 2000 Software to obtain a thermogram. The setup is shown in Fig. 1. For the storage experiment a new camera setup was built, which was more standardised for ambient conditions (ambient temperature, RH, air velocity, ambient reflection) and, which allowed simultaneous measurement of full batches of apples and of each individual apple within the batch. A schematic representation of this setup is provided in Fig. 2. For this setup an AVIO, Compact Thermo, (TVS2000 mkII series, France; Civil Engineering Department, K. U. Leuven, sensitivity 0.01 C) camera was used. This camera was placed on top of a wooden wind tunnel with a maximum distance between camera and object of 1 m. This allowed for the recording of full
batches of apples. In the wind tunnel, four apples were positioned on a tray in a line perpendicular to the airflow. The inside of the tunnel was completely covered with texturised black paint to obtain a minimal reflection. Throughout the tunnel an air stream was created by means of a fan. The complete setup was placed in a cool room at 1 C and a relative humidity of 86–87%. The relative humidity was continuously logged by means of an Escort Junior Logger (Escort, Techinnovators, New Zealand). Images were processed by means of PicEd AVIO TVS100 software. 2.3. Spectral emissivity (e) determination of apple skin For the emissivity measurements of apple skin, the ThermaCAMTMSC3000 camera setup was used. In this case no object was placed in the cylinder but a piece of apple skin was attached to the cooled background. Next to this piece of apple skin a piece of another material with known emissivity was attached. For these experiments two different materials were used: Scotch tape (e = 0.96) and plaster (e = 0.80–0.86). Measurements were carried out at a constant ambient temperature of 12 C by working in a cool room. Next, the surface temperature of both apple skin and reference material was set to 1 C by means of ice. The emissivity of the camera was set to that of the known material (Scotch tape or plaster). From the comparison of the absolute temperatures of both materials as registered by the camera at this emissivity, the emissivity of the unknown material—or in this case the apple skin—could be deduced. 2.4. Measurements on individual fruit
Fig. 1. ThermaCAMTMSC3000 setup.
For measurements on individual fruit the ThermaCAMTMSC3000 camera setup was used with 10 Jonagored and 10 Elshof apples of early picking dates. Temperature standardisation was realised by working at 12 C in a coolroom. The individual fruit were placed on a tray in the cylinder and were cooled from a temperature of 20 C to 12 C. The cooling process was followed every 15 min for four and a half hours with the ThermaCAMTMSC3000. The emissivity was set to 0.96. 2.5. Batch measurements
Fig. 2. Schematic representation of the setup for batch measurements with the AVIO camera.
In this experiment six batches of four apples randomly selected from the two cultivars were prepared after each CA storage period. First, the initial weight (g), largest equatorial diameter (m) and largest longitudinal diameter were determined of all apples in all 6 batches. Next, all apples were conditioned at 12 C and subsequently placed in the wind tunnel at 1 C. The cooling process was monitored by recording a thermogram of the whole batch of four apples every 15 min and this for four and a half hours.
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After the recording of thermograms four of the six batches were put under shelf life conditions while the two remaining batches were used for wax extraction and GC analysis which will not be discussed in this paper. After 1 week the four batches undergoing shelf life were analysed with the thermographic camera for a second time after which two batches were sent back to shelf life and two other batches were used for the chemical analysis. After a second week the remaining two batches in shelf life were analysed with the camera for a last time. During the experiments the air velocity was measured by means of a hot film anemometer (TSI, St. Paul, MN). 2.6. Data analysis In the absence of evaporative heat transfer, the transient temperature field inside the fruit is described by the Fourier equation oT ¼ ar2 T ot
ð1Þ
with a the thermal diffusivity of apple (m2s1), t the time (s), and T (C) the temperature. At the boundary a convection boundary condition applies a
oT h ¼ ðT 1 T Þ on qc
ð2Þ
with h (W/m2 C) the surface heat transfer coefficient, n the outward normal to the surface, q the density (kg/m3), and T1 the air temperature. It can be shown (Incropera & De Witt, 1990) that the solution of Eq. (1) subject to (2) at the apple surface is given by T S ¼ T 1 þ ðT S;0 T 1 ÞC expðkFoÞ
ð3Þ
with TS the surface temperature (C), T1 the air temperature, T0 the (uniform) initial temperature (C), C a constant, k a slope, and Fo the Fourier number, a dimensionless time defined by Fo ¼
at D2
ð4Þ
with D the diameter (m). Both C and k are a function of h and D through some transcedental equation. When evaporative cooling is important, latent heat transfer at the surface and moisture diffusion in the gas or liquid phase inside the fruit becomes important as well. The corresponding model equations are complicated and no analytical solution is available. Instead, a pragmatic approach has been followed here by assuming that evaporation accelerates cooling, and, hence, causes k to increase. Further, it also causes the surface temperature to drop below the air temperature. Therefore Eq. (3) was slightly modified as T S ¼ T S;1 þ ðT S;0 T S;1 Þ expðkFoÞ
ð5Þ
165
with TS,1 the final surface temperature (C). Note that the constant C was omitted to reduce the number of parameters to be estimated. A Matlab 5.3 (The Mathworks, Natick, USA) procedure was implemented to estimate the parameters TS,1 and k by fitting Eq. (5) to the surface temperature versus time data.These parameters were then compared between the different cultivars and different storage conditions tested. Note that they were dependent on the surface heat transfer coefficient, which in turn depends on the air velocity, the apple dimensions and the moisture exchange between the apple and the air (transpiration). The air velocity was shown to be related to the position of the apple on the tray (0.8–0.5 m s1 from position 1–4). From a statistical analysis of variance, TS,1 was significantly dependent on the apple diameter but not on the position. Further, k was significantly dependent on both diameter and position. The parameter TS,1 was, therefore, corrected a second time for diameter and k was corrected for position and diameter with SAS/STAT software version 8.2 (SAS Institute, Cary, NC, USA) (SAS/STAT UserÕs Guide, Version 8, 1999). This was done by expressing each parameter as a function of position and/or diameter by means of a generalised linear model. The corresponding residuals, which were, hence, independent of diameter and position, were then analysed by means of ANOVA with SAS/STAT software version 8.2 (SAS Institute, Cary, NC, USA) (SAS/STAT UserÕs Guide, Version 8, 1999) to describe the main effects of cultivar (Elshof and Jonagored), picking date (1 and 2), months of storage (4 and 8) and weeks of shelf life (0, 1, and 2).
3. Results and discussion 3.1. Spectral emissivity (e) of apple The spectral emissivity as measured in this work was 0.96 for both the apple cultivars Jonagored and Elshof. This indicates a very high emissivity for apple and no cultivar dependence in this case. To test this measured emissivity, temperature recordings of the camera were compared to temperature measurements with thermocouples attached right under the skin of the apple. These measurements were very similar at an emissivity of 0.96 (results not shown). This emissivity also corresponded to the emissivity of 0.95 measured for citrus fruit (Fito et al., 2004). 3.2. Measurements on individual fruit In a first series of experiments, differences in surface temperature, during a temperature equilibration from 20 C to 12 C were studied between apples of the Jonagored and Elshof cultivars. In these experiments
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19
18
Jonagold
Temp (°C)
17
16
15
Elshof 14
13
12 0
20
40
60 Time (min)
80
100
Fig. 3. Surface temperature of individual Jonagored en Elshof apples measured with the ThermaCAMTM during cooling from 20 C to 12 C.
Elshof apples in general cooled down faster and experienced a lower surface temperature than Jonagored apples. This is demonstrated in Fig. 3. This lower surface temperature of Elshof is explained by the higher moisture losses and transpiration rates at the surface of Elshof apples due to their more cracked wax layer and higher amount of lenticels (Veraverbeke et al., 2001a). This lower temperature could, however, also be related to the smaller average diameter of Elshof (64.44 ·
103 m) apples compared to Jonagored apples (75.85 · 103 m). Therefore, a more randomised storage experiment with batches of apples instead of individual fruit was set up. 3.3. Batch measurements In Fig. 4 an example of the thermograms of a batch of four apples at four different stages in a cooling
Fig. 4. Thermogram of a batch of four apples at the start of the cooling process (upper left picture) and at the end of the cooling process (lower right picture).
process from 12 C to 1 C is shown. From these thermographic images, temperature profiles representing the average temperature over the apple surface versus time were determined for the cooling of batches of four apples. Different profiles were obtained for every apple within the batch and for the background. These profiles were similar to the ones shown in Fig. 3 with Elshof in general having a faster cooling rate and lower surface temperature than Jonagored. After 4.5 h (total analysis time) the steady state temperature was not yet reached. Data were then corrected for apple dimensions and position as described in the materials and methods section to exclude differences in temperature due to apple dimensions and position rather than surface characteristics. This resulted in two diameter corrected TS,1 parameter(modelled final surface temperature) and a diameter and position corrected slope parameter (k, cooling rate). These two parameters were used to describe the main effects in cultivar, picking date, storage and shelf life. The results of the ANOVA analysis are presented in Table 1. For TS,1 significant differences were found between 4 and 8 months of storage and between 0, 1 and 2 weeks of shelf life. For k significant differences were found between Elshof and Jonagored, between early (1) and late (2) picking and between 4 and 8 months of storage. When TS,1 is plotted as a function of k these effects can be well illustrated as is shown in Figs. 5 and 6 for cultivar and storage, respectively. Note that, although in Fig. 5 the cultivars seem to be separated. However, further research is required to confirm this finding for example by including fruit from different orchards. The significant difference in cooling rate found between Elshof and Jonagored might be explained in terms of wax structure and transpiration as stated at the beginning of this paper. The more negative k-value of Elshof means a faster cooling for this cultivar than for Jonagored, which can be related to the more open wax structure of Elshof and thus higher transpiration rate at the
167
2
Jonagored
1 0 -0.25
-0.2
-0.15
-0.1
-0.05
diameter/ position corrected k
E.A. Veraverbeke et al. / Journal of Food Engineering 77 (2006) 162–168
diameter corrected TS,∞(°C)
0 -1
0.05
0.1
0.15
-2 -3 Elshof
-4 Elshof -5
Jonagored
diameter/ position corrected k
Fig. 5. Effect of cultivar expressed as a function of corrected TS,1 and corrected k for apples of early picking after 8 months CA storage and no shelf life.
6 4 4
8 2
4 months diameter corrected TS,∞(°C)
0 -0.2
-0.15
-0.1
-0.05
0
0.05
0.1
0.15
0.2
0.25
-2 8 months
-4 -6
Fig. 6. Effect of storage expressed as a function of corrected TS,1 and corrected k for Elshof apples of late picking after 1 week of shelf life.
surface. Higher transpiration results in faster cooling. The significant differences in TS,1 and k found for picking, storage and shelf life, however, can not be explained in terms of a more open wax structure and related increase in moisture loss. An alternative explanation
Table 1 ANOVA analysis Variable
Level
Diameter corrected TS,1 Tukey
p-Value and effect
Tukey
p-Value and effect
Cultivar
Elshof (E) Jonagored (J)
A A
0.6914
A B
0.0436 E
Picking
Early (1) Late (2)
A A
0.2512
A B
0.0034 1>2
Storage
4 months 8 months
A B
<0.001 4>8
A B
<0.001 4>8
Shelf life
0 weeks 1 week 2 weeks
A B C
<0.001 2>0>1
A A A
0.0701
Diameter/position corrected k
For every variable (cultivar, picking date, storage, shelf life) different letters indicate significant differences between the different levels for TS,1 and k based on a Tukey test with p < 0.05. For each variable also the significance level and specific effect is indicated at the right of each parameter.
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for these differences may be that they are related to thermophysical properties of the peel rather than to wax structure related properties. In this case the infrared camera is sensitive enough to register the main differences in wax structure among different cultivars but not sensitive enough to analyse the small changes that occur in the structure of the wax layer during storage. Finally, other possible confounding factors such as orchard, soil composition and microclimate can not be excluded at this point and should be investigated further. Working with larger datasets and more repetitions per variable level, however, holds potential to solve this problem. 4. Conclusion With infrared thermography the cooling rate and TS,1 of apples was monitored in relation to the fruit surface quality and wax layer structure before and during storage and shelf life. From the thermographic data a difference in cooling rate was detected between Elshof and Jonagored, which may be related to differences in wax structure between these apple cultivars. Changes in wax structure that occur during storage were not detected by means of thermographic imaging. This indicates the thermographic measurements to be sensitive enough to possibly detect the effects of cultivar related wax differences but not to detect the changes that occur in the wax during storage. The results of this analysis are however based on relatively few images taken in very specific conditions. More tests are necessary to demonstrate the stability of this technique in different conditions and for different cultivars. This paper, for the first time, demonstrates the importance of calibration and correction of thermographic data. Without this type of data processing the effect of apple dimensions, thermophysical properties of apple tissue and surface heat and moisture transfer coefficients on the monitored temperature differences is measured rather than the unique effect of surface characteristics. Acknowledgements The authors wish to thank the Flemish Government (project BIL 99/37), the K. U. Leuven (project OT 99/22), and the Ministry of SME and Agriculture (project S-6056) for their financial support. Author Els Veraverbeke is a postdoctoral fellow of the K. U. Leuven and authors Pieter Verboven and Jeroen Lammertyn are postdoctoral fellows of the Fund for Scientific Research-Flanders (Belgium) (FWO-Vlaanderen). The Department of Civil Engineering, Division Building Physics of the K. U. Leuven is acknowledged for the use of their camera.
References Chaerle, L., Hulsen, K., Hermans, C., Strasser, R. J., Valcke, R., Hofte, M., et al. (2003). Robotized time-lapse imaging to assess inplanta uptake of phenylurea herbicides and their microbial degradation. Physiologia Plantarum, 118(4), 613–619. Chaerle, L., & Van der Straeten, D. (2000). Imaging techniques and the early detection of plant stress. Trends in Plant Science, 5(11), 495–501. Chaerle, L., & Van der Straeten, D. (2001). Seeing is believing: imaging techniques to monitor plant health. Biochimica et Biophysica Acta gene structure and expression, 1519(3), 153–166. Fito, P. J., Ortola, M. D., De los Reyes, R., Fito, P., & De los Reyes, E. (2004). Control of citrus surface drying by image analysis of infrared thermography. Journal of Food Engineering, 61(3), 287–290. Glenn, G. M., Rom, C. R., Rasmussen, H. P., & Poovaiah, B. W. (1990). Influence of cuticular structure on the appearance of artificially waxed ÔDeliciousÕ apple fruit. Scientia Horticulturae, 42, 289–297. Incropera, F. P., & Witt, D. P. D. (1990). Fundamentals of heat and mass transfer. New York: Wiley. Jones, B. F. (1998). A reappraisal of the use of infrared thermal image analysis in medicine. IEEE Transactions on Medical Imaging, 17(6), 1019–1027. Jones, H. G. (1999). Use of thermography for quantitative studies of spatial and temporal variation of stomatal conductance over leaf surfaces. Plant Cell and Environment, 22(9), 1043–1055. Lamprecht, I., Schmolz, E., Blanco, L., & Romero, C. M. (2002). Flower ovens: thermal investigations on heat producing plants. Thermochimica Acta, 391(1–2), 107–118. Pearce, R. S. (2001). Plant freezing and damage. Annals of Botany, 87(4), 417–424. Prytz, G., Futsaether, C. M., & Johnsson, A. (2003). Thermography studies of the spatial and temporal variability in stomatal conductance of Avena leaves during stable and oscillatory transpiration. New Phytologist, 158(2), 249–258. SAS Institute Inc., SAS/STAT (1999). UserÕs Guide, Version 8, Cary, NC: SAS Institute Inc. Stajnko, D., Lakota, M., & Hocˇevar, M. (2004). Estimation of number and diameter of apple fruits in an orchard during the growing season by thermal imaging. Computers and Electronics in Agriculture, 42(1), 31–42. Thomas, R. A., Jones, N., & Donne, K. E. (2000). Infrared thermography and diagnostic monitoring. Imaging Science Journal, 48(1), 23–32. Veraverbeke, E. A., Lammertyn, J., Saevels, S., & Nicolaı¨, B. M. (2001b). Changes in chemical composition of three different apple (ÔMalus domesticaÕ Borkh.) cultivars during storage. Postharvest Biology and Technology, 23(3), 197–208. Veraverbeke, E. A., Van Bruaene, N., Van Oostveldt, P., & Nicolaı¨, B. M. (2001a). Non destructive analysis of the wax layer of apple (Ô Malus domesticaÕ Borkh.) by means of confocal laser scanning microscopy. Planta, 213, 525–533. Vereycken, R. (2002). Thermografische evaluatie van blutsschade bij tomaten (Thermographic evaluation of bruise damage on tomato). MSc Thesis, Faculty of Agricultural and Applied Biological Sciences, Katholieke Universiteit Leuven, Belgium. Wisniewski, M., Glenn, D. M., & Fuller, M. P. (2002). Use of a hydrophobic particle film as a barrier to extrinsic ice nucleation in tomato plants. Journal of the American Society for Horticultural Science, 127(3), 358–364. Workmaster, B. A. A., Palta, J. P., & Wisniewski, M. (1999). Ice nucleation and propagation in cranberry uprights and fruit using infrared video thermography. Journal of the American Society for Horticultural Science, 124(6), 619–625.
Thermographic surface quality evaluation of apple E.A. Veraverbeke a, P. Verboven a, J. Lammertyn a,*, P. Cronje a, J. De Baerdemaeker b, B.M. Nicolaı¨ a a
Department of Agro-Engineering and Economics, Flanders Centre/Laboratory of Postharvest Technology, Katholieke Universiteit Leuven, William de Croylaan 42, B-3001 Heverlee, Belgium b Laboratory for Agricultural Machinery and Processing, Katholieke Universiteit Leuven, Kateelpark Arenberg 30, 3001 Heverlee, Belgium Received 9 August 2004; accepted 18 June 2005 Available online 31 August 2005
Abstract Thermographic IR-imaging was used as a non-destructive tool to evaluate the surface quality of apples. Experiments were carried out on apple fruit of two different cultivars (Jonagored and Elshof) picked at two different picking dates (early and late). First, the emissivity of the apple skin was determined as 0.96 for both cultivars. Next, recordings were made of individual fruit of both cultivars cooled from 20 C to 12 C. In this experiment Elshof apples had a faster cooling rate and lower temperature than Jonagored apples. Finally, a storage experiment was carried out under standardised conditions with quality assessment after 4 and 8 months of CA storage and at each storage period after 0, 1, and 2 weeks of shelf life. Next to the determination of general quality parameters (weight, diameter), thermographic images of the surface of each apple were obtained. Temperature profiles were recorded for batches of four fruits and of all individual fruit within this batch while they were cooled from 12 C to 1 C. The surface cooling rate and final fruit surface temperature were estimated. All data were calibrated for background temperature and corrected for apple dimensions and convection coefficients. ANOVA analysis showed significant differences between both cultivars, picking dates and storage conditions for the cooling rate. The final surface temperature differed significantly between different storage and shelf life periods. Only the difference in cooling rate with a faster cooling for Elshof than for Jonagored was explained in terms of wax structural characteristics and transpiration rates. The results also show the importance of data correction. 2005 Elsevier Ltd. All rights reserved. Keywords: Apple; Wax; Surface quality; Thermography
1. Introduction Apples are naturally covered with an epicuticular wax layer, which protects the fruit from stress factors, such as moisture loss, mechanical damage, and microbiological infections. This wax layer also positively contributes to the visual quality of the produce by maintaining a good surface quality. An excessive wax production or chemical and structural changes in the wax during stor*
Corresponding author. Tel.: +32 16 32 23 76; fax: +32 16 32 29 55. E-mail address: [email protected] (J. Lammertyn). 0260-8774/$ - see front matter 2005 Elsevier Ltd. All rights reserved. doi:10.1016/j.jfoodeng.2005.06.059
age and shelf life can, however, contribute negatively to the organoleptic or visual quality of the fruit. In this case the wax layer gives the fruit an unpleasant bloom or turns the surface greasy and sticky. Of some apple cultivars, such as Jonagored, it is known that they are more susceptible to the development of greasy surfaces than other cultivars, such as Elshof. As visual quality constitutes one of the most important components determining the consumer demand and the economic value of the produce, optimisation of the wax layer quality is continuously aimed for. In some cases, artificial waxes, such as Carnauba and Shellac are applied (Glenn, Rom, Rasmussen, & Poovaiah, 1990)
E.A. Veraverbeke et al. / Journal of Food Engineering 77 (2006) 162–168
but more often optimal storage conditions combined with cultivars that have a low susceptibility to greasiness development are searched for. In previous research, the wax layer structure (Veraverbeke, Van Bruaene, Van Oostveldt, & Nicolaı¨, 2001a) and composition (Veraverbeke, Lammertyn, Saevels, & Nicolaı¨, 2001b) of three different apple cultivars were studied based on microscopic and gas chromatographic analysis. This allowed discrimination of the different apple cultivars based on their surface characteristics and related moisture loss during storage. Contrary to moisture loss, greasiness development is more difficult to quantify and until now no sufficient method exists to analyse greasiness. A full chemical analysis is also too complicated for routine evaluations. More research is, therefore, required to quantify wax and surface quality based on objective and non-destructive measurements. Thermography is an image processing technique, which transforms thermal radiation, recorded by a camera, into a thermographic image or thermogram. A thermogram is a representation of the specific temperature distribution at the object surface. Thermography is a very fast measuring technique, which allows measurement on moving objects. It also is a non-contact and non-destructive tool so that no mechanical injury or contamination of the study object can occur during measurement. Therefore, this technique has already found many applications as a diagnostic monitoring tool in industrial and medical settings (Jones, 1998; Thomas, Jones, & Donne, 2000). In biological sciences, thermography is used for amongst others stomatal conduction measurements (Jones, 1999; Prytz, Futsaether, & Johnsson, 2003), assessment of the uptake of herbicides (Chaerle et al., 2003) tracing of plant diseases and plant stress (Chaerle & Van der Straeten, 2000, 2001), plant freezing studies (Pearce, 2001) and heat production measurements (Lamprecht, Schmolz, Blanco, & Romero, 2002). Infrared thermography is also used as a non destructive analysis tool for measuring or controlling fruit quality. Studies have been carried out to use thermography for bruise detection on apple and tomato surfaces before the actual bruise is visible to the eye (Vereycken, 2002). Workmaster, Palta, and Wisniewski (1999) used infrared video thermography for the study of ice nucleation and propagation in cranberry uprights and fruit. In the same line, thermography was applied to test the use of a hydrophobic particle film as a barrier to extrinsic ice nucleation in tomato plants (Wisniewski, Glenn, & Fuller, 2002). For apple production, thermal imaging was used to estimate the number and diameter of apple fruit in an orchard during the growing season for yield prediction (Stajnko, Lakota, & Hocˇevar, 2004). In this work thermography was used as an alternative for colour measurements when canopy and fruit have about the same colour. Determination coefficients
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(R2) from 0.83 to 0.88 were obtained between manually measured fruit numbers and estimated fruit numbers based on a fruit detection algorithm. Related to surface and wax quality analysis this technique was used for the control of surface drying time of citrus fruit. Oranges were dried after washing and coating with an artificial wax. Strict control of the drying time is necessary to prevent sensory losses or a decrease in fresh fruit shelf life. With thermography the drying process was evaluated in terms of wax amount, air velocity and temperature. Higher values of each of these parameters resulted in shorter drying times (Fito, Ortola, De los Reyes, Fito, & De los Reyes, 2004). The objective of this work was to evaluate the potential of IR thermography for surface quality analysis of apple. It was assumed that differences in surface or wax quality (number of cracks, number of lenticels, level of wax smoothing,. . .) result in a different surface temperature through differences in transpiration and evaporation at the surface.
2. Materials and methods 2.1. Fruit Apples were harvested at the Proeftuin voor Pit—en Steenfruit in Velm (Belgium) at 3 September 2002 (early) and 9 September 2002 (late) for Elshof and at 16 September 2002 (early) and 23 September 2002 (late) for Jonagored. All fruit was stored in controlled atmosphere (CA) containers of about 1 m3 (Elshof: 2% O2, <1% CO2, 1 C, 95% RH; Jonagored: 1% O2, 2.5% CO2, 1 C, 95% RH) until analysis. After different periods of CA storage (4 and 8 months) apples were also stored at shelf life conditions for 0, 1 and 2 weeks in an incubator at 20 C. The relative humidity was not controlled. 2.2. Camera setup Two different types of cameras and camera setups were tested. A first type was used for the determination of the emissivity of apple and for measurements on individual apples. A second type was used for the recording of batches of apples in a storage experiment. For the emissivity and individual fruit measurements a camera setup developed at the Laboratory for Agricultural Machinery and Processing of the K. U. Leuven (Belgium) was used. This setup contained a ThermaCAMTMSC3000 camera (FLIR systems) provided with a lens with a resolution of 100 lm and a photon detector. The latter was cooled to minimise noise resulting from the thermal excitation of charged particles of the detector itself. The object to be measured was placed in a rusty iron cylinder in front of a cooled and also
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rusty iron background. This allowed a homogeneous distribution of the radiation over the surface with a clear difference in radiation between object and background. Cooled and rusty iron is characterised by a low emissivity and reflection. An automatic calibration for the ambient and camera temperature and for the air humidity was provided. Photon currents were recorded with the camera and analysed with ThermaCamTM Researcher 2000 Software to obtain a thermogram. The setup is shown in Fig. 1. For the storage experiment a new camera setup was built, which was more standardised for ambient conditions (ambient temperature, RH, air velocity, ambient reflection) and, which allowed simultaneous measurement of full batches of apples and of each individual apple within the batch. A schematic representation of this setup is provided in Fig. 2. For this setup an AVIO, Compact Thermo, (TVS2000 mkII series, France; Civil Engineering Department, K. U. Leuven, sensitivity 0.01 C) camera was used. This camera was placed on top of a wooden wind tunnel with a maximum distance between camera and object of 1 m. This allowed for the recording of full
batches of apples. In the wind tunnel, four apples were positioned on a tray in a line perpendicular to the airflow. The inside of the tunnel was completely covered with texturised black paint to obtain a minimal reflection. Throughout the tunnel an air stream was created by means of a fan. The complete setup was placed in a cool room at 1 C and a relative humidity of 86–87%. The relative humidity was continuously logged by means of an Escort Junior Logger (Escort, Techinnovators, New Zealand). Images were processed by means of PicEd AVIO TVS100 software. 2.3. Spectral emissivity (e) determination of apple skin For the emissivity measurements of apple skin, the ThermaCAMTMSC3000 camera setup was used. In this case no object was placed in the cylinder but a piece of apple skin was attached to the cooled background. Next to this piece of apple skin a piece of another material with known emissivity was attached. For these experiments two different materials were used: Scotch tape (e = 0.96) and plaster (e = 0.80–0.86). Measurements were carried out at a constant ambient temperature of 12 C by working in a cool room. Next, the surface temperature of both apple skin and reference material was set to 1 C by means of ice. The emissivity of the camera was set to that of the known material (Scotch tape or plaster). From the comparison of the absolute temperatures of both materials as registered by the camera at this emissivity, the emissivity of the unknown material—or in this case the apple skin—could be deduced. 2.4. Measurements on individual fruit
Fig. 1. ThermaCAMTMSC3000 setup.
For measurements on individual fruit the ThermaCAMTMSC3000 camera setup was used with 10 Jonagored and 10 Elshof apples of early picking dates. Temperature standardisation was realised by working at 12 C in a coolroom. The individual fruit were placed on a tray in the cylinder and were cooled from a temperature of 20 C to 12 C. The cooling process was followed every 15 min for four and a half hours with the ThermaCAMTMSC3000. The emissivity was set to 0.96. 2.5. Batch measurements
Fig. 2. Schematic representation of the setup for batch measurements with the AVIO camera.
In this experiment six batches of four apples randomly selected from the two cultivars were prepared after each CA storage period. First, the initial weight (g), largest equatorial diameter (m) and largest longitudinal diameter were determined of all apples in all 6 batches. Next, all apples were conditioned at 12 C and subsequently placed in the wind tunnel at 1 C. The cooling process was monitored by recording a thermogram of the whole batch of four apples every 15 min and this for four and a half hours.
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After the recording of thermograms four of the six batches were put under shelf life conditions while the two remaining batches were used for wax extraction and GC analysis which will not be discussed in this paper. After 1 week the four batches undergoing shelf life were analysed with the thermographic camera for a second time after which two batches were sent back to shelf life and two other batches were used for the chemical analysis. After a second week the remaining two batches in shelf life were analysed with the camera for a last time. During the experiments the air velocity was measured by means of a hot film anemometer (TSI, St. Paul, MN). 2.6. Data analysis In the absence of evaporative heat transfer, the transient temperature field inside the fruit is described by the Fourier equation oT ¼ ar2 T ot
ð1Þ
with a the thermal diffusivity of apple (m2s1), t the time (s), and T (C) the temperature. At the boundary a convection boundary condition applies a
oT h ¼ ðT 1 T Þ on qc
ð2Þ
with h (W/m2 C) the surface heat transfer coefficient, n the outward normal to the surface, q the density (kg/m3), and T1 the air temperature. It can be shown (Incropera & De Witt, 1990) that the solution of Eq. (1) subject to (2) at the apple surface is given by T S ¼ T 1 þ ðT S;0 T 1 ÞC expðkFoÞ
ð3Þ
with TS the surface temperature (C), T1 the air temperature, T0 the (uniform) initial temperature (C), C a constant, k a slope, and Fo the Fourier number, a dimensionless time defined by Fo ¼
at D2
ð4Þ
with D the diameter (m). Both C and k are a function of h and D through some transcedental equation. When evaporative cooling is important, latent heat transfer at the surface and moisture diffusion in the gas or liquid phase inside the fruit becomes important as well. The corresponding model equations are complicated and no analytical solution is available. Instead, a pragmatic approach has been followed here by assuming that evaporation accelerates cooling, and, hence, causes k to increase. Further, it also causes the surface temperature to drop below the air temperature. Therefore Eq. (3) was slightly modified as T S ¼ T S;1 þ ðT S;0 T S;1 Þ expðkFoÞ
ð5Þ
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with TS,1 the final surface temperature (C). Note that the constant C was omitted to reduce the number of parameters to be estimated. A Matlab 5.3 (The Mathworks, Natick, USA) procedure was implemented to estimate the parameters TS,1 and k by fitting Eq. (5) to the surface temperature versus time data.These parameters were then compared between the different cultivars and different storage conditions tested. Note that they were dependent on the surface heat transfer coefficient, which in turn depends on the air velocity, the apple dimensions and the moisture exchange between the apple and the air (transpiration). The air velocity was shown to be related to the position of the apple on the tray (0.8–0.5 m s1 from position 1–4). From a statistical analysis of variance, TS,1 was significantly dependent on the apple diameter but not on the position. Further, k was significantly dependent on both diameter and position. The parameter TS,1 was, therefore, corrected a second time for diameter and k was corrected for position and diameter with SAS/STAT software version 8.2 (SAS Institute, Cary, NC, USA) (SAS/STAT UserÕs Guide, Version 8, 1999). This was done by expressing each parameter as a function of position and/or diameter by means of a generalised linear model. The corresponding residuals, which were, hence, independent of diameter and position, were then analysed by means of ANOVA with SAS/STAT software version 8.2 (SAS Institute, Cary, NC, USA) (SAS/STAT UserÕs Guide, Version 8, 1999) to describe the main effects of cultivar (Elshof and Jonagored), picking date (1 and 2), months of storage (4 and 8) and weeks of shelf life (0, 1, and 2).
3. Results and discussion 3.1. Spectral emissivity (e) of apple The spectral emissivity as measured in this work was 0.96 for both the apple cultivars Jonagored and Elshof. This indicates a very high emissivity for apple and no cultivar dependence in this case. To test this measured emissivity, temperature recordings of the camera were compared to temperature measurements with thermocouples attached right under the skin of the apple. These measurements were very similar at an emissivity of 0.96 (results not shown). This emissivity also corresponded to the emissivity of 0.95 measured for citrus fruit (Fito et al., 2004). 3.2. Measurements on individual fruit In a first series of experiments, differences in surface temperature, during a temperature equilibration from 20 C to 12 C were studied between apples of the Jonagored and Elshof cultivars. In these experiments
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19
18
Jonagold
Temp (°C)
17
16
15
Elshof 14
13
12 0
20
40
60 Time (min)
80
100
Fig. 3. Surface temperature of individual Jonagored en Elshof apples measured with the ThermaCAMTM during cooling from 20 C to 12 C.
Elshof apples in general cooled down faster and experienced a lower surface temperature than Jonagored apples. This is demonstrated in Fig. 3. This lower surface temperature of Elshof is explained by the higher moisture losses and transpiration rates at the surface of Elshof apples due to their more cracked wax layer and higher amount of lenticels (Veraverbeke et al., 2001a). This lower temperature could, however, also be related to the smaller average diameter of Elshof (64.44 ·
103 m) apples compared to Jonagored apples (75.85 · 103 m). Therefore, a more randomised storage experiment with batches of apples instead of individual fruit was set up. 3.3. Batch measurements In Fig. 4 an example of the thermograms of a batch of four apples at four different stages in a cooling
Fig. 4. Thermogram of a batch of four apples at the start of the cooling process (upper left picture) and at the end of the cooling process (lower right picture).
process from 12 C to 1 C is shown. From these thermographic images, temperature profiles representing the average temperature over the apple surface versus time were determined for the cooling of batches of four apples. Different profiles were obtained for every apple within the batch and for the background. These profiles were similar to the ones shown in Fig. 3 with Elshof in general having a faster cooling rate and lower surface temperature than Jonagored. After 4.5 h (total analysis time) the steady state temperature was not yet reached. Data were then corrected for apple dimensions and position as described in the materials and methods section to exclude differences in temperature due to apple dimensions and position rather than surface characteristics. This resulted in two diameter corrected TS,1 parameter(modelled final surface temperature) and a diameter and position corrected slope parameter (k, cooling rate). These two parameters were used to describe the main effects in cultivar, picking date, storage and shelf life. The results of the ANOVA analysis are presented in Table 1. For TS,1 significant differences were found between 4 and 8 months of storage and between 0, 1 and 2 weeks of shelf life. For k significant differences were found between Elshof and Jonagored, between early (1) and late (2) picking and between 4 and 8 months of storage. When TS,1 is plotted as a function of k these effects can be well illustrated as is shown in Figs. 5 and 6 for cultivar and storage, respectively. Note that, although in Fig. 5 the cultivars seem to be separated. However, further research is required to confirm this finding for example by including fruit from different orchards. The significant difference in cooling rate found between Elshof and Jonagored might be explained in terms of wax structure and transpiration as stated at the beginning of this paper. The more negative k-value of Elshof means a faster cooling for this cultivar than for Jonagored, which can be related to the more open wax structure of Elshof and thus higher transpiration rate at the
167
2
Jonagored
1 0 -0.25
-0.2
-0.15
-0.1
-0.05
diameter/ position corrected k
E.A. Veraverbeke et al. / Journal of Food Engineering 77 (2006) 162–168
diameter corrected TS,∞(°C)
0 -1
0.05
0.1
0.15
-2 -3 Elshof
-4 Elshof -5
Jonagored
diameter/ position corrected k
Fig. 5. Effect of cultivar expressed as a function of corrected TS,1 and corrected k for apples of early picking after 8 months CA storage and no shelf life.
6 4 4
8 2
4 months diameter corrected TS,∞(°C)
0 -0.2
-0.15
-0.1
-0.05
0
0.05
0.1
0.15
0.2
0.25
-2 8 months
-4 -6
Fig. 6. Effect of storage expressed as a function of corrected TS,1 and corrected k for Elshof apples of late picking after 1 week of shelf life.
surface. Higher transpiration results in faster cooling. The significant differences in TS,1 and k found for picking, storage and shelf life, however, can not be explained in terms of a more open wax structure and related increase in moisture loss. An alternative explanation
Table 1 ANOVA analysis Variable
Level
Diameter corrected TS,1 Tukey
p-Value and effect
Tukey
p-Value and effect
Cultivar
Elshof (E) Jonagored (J)
A A
0.6914
A B
0.0436 E
Picking
Early (1) Late (2)
A A
0.2512
A B
0.0034 1>2
Storage
4 months 8 months
A B
<0.001 4>8
A B
<0.001 4>8
Shelf life
0 weeks 1 week 2 weeks
A B C
<0.001 2>0>1
A A A
0.0701
Diameter/position corrected k
For every variable (cultivar, picking date, storage, shelf life) different letters indicate significant differences between the different levels for TS,1 and k based on a Tukey test with p < 0.05. For each variable also the significance level and specific effect is indicated at the right of each parameter.
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for these differences may be that they are related to thermophysical properties of the peel rather than to wax structure related properties. In this case the infrared camera is sensitive enough to register the main differences in wax structure among different cultivars but not sensitive enough to analyse the small changes that occur in the structure of the wax layer during storage. Finally, other possible confounding factors such as orchard, soil composition and microclimate can not be excluded at this point and should be investigated further. Working with larger datasets and more repetitions per variable level, however, holds potential to solve this problem. 4. Conclusion With infrared thermography the cooling rate and TS,1 of apples was monitored in relation to the fruit surface quality and wax layer structure before and during storage and shelf life. From the thermographic data a difference in cooling rate was detected between Elshof and Jonagored, which may be related to differences in wax structure between these apple cultivars. Changes in wax structure that occur during storage were not detected by means of thermographic imaging. This indicates the thermographic measurements to be sensitive enough to possibly detect the effects of cultivar related wax differences but not to detect the changes that occur in the wax during storage. The results of this analysis are however based on relatively few images taken in very specific conditions. More tests are necessary to demonstrate the stability of this technique in different conditions and for different cultivars. This paper, for the first time, demonstrates the importance of calibration and correction of thermographic data. Without this type of data processing the effect of apple dimensions, thermophysical properties of apple tissue and surface heat and moisture transfer coefficients on the monitored temperature differences is measured rather than the unique effect of surface characteristics. Acknowledgements The authors wish to thank the Flemish Government (project BIL 99/37), the K. U. Leuven (project OT 99/22), and the Ministry of SME and Agriculture (project S-6056) for their financial support. Author Els Veraverbeke is a postdoctoral fellow of the K. U. Leuven and authors Pieter Verboven and Jeroen Lammertyn are postdoctoral fellows of the Fund for Scientific Research-Flanders (Belgium) (FWO-Vlaanderen). The Department of Civil Engineering, Division Building Physics of the K. U. Leuven is acknowledged for the use of their camera.
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