Postharvest Biology and Technology 21 2000 189 – 199
Prediction of the optimal picking date of different apple cultivars by means of VISNIR-spectroscopy
Ann Peirs
a,
, Jeroen Lammertyn
a
, Kristien Ooms
b
, Bart M. Nicolaı¨
a
a
Flanders Centre of Posthar6est TechnologyLaboratory of Posthar6est Technology, Willem de Croylaan
42
,
3001
Leu6en, Belgium
b
CQ Consultancy, Inno6atie- en Incubatiecentrum, Kapeldreef
60
,
3001
Leu6en, Belgium Received 17 November 1999; accepted 12 July 2000
Abstract
The use of visiblenear infrared VISNIR spectroscopy was evaluated to determine the internal quality and the optimal harvest dates of apples non-destructively. Calibration models were constructed with data from eight cultivars,
three orchards and 2 years, in order to make the models as robust as possible for future use. The prediction of the maturity, defined as the number of days before commercial harvest, was reasonably accurate. The most robust model
predicted the maturity with a validation correlation of 0.90 SEP = 7.4 days. The prediction of maturity, according to the Streif index, showed a validation correlation of 0.84 SEP = 0.18 kg brix × starch index for one orchard.
Maturity was orchard-dependent, however, and as a consequence, a combined prediction equation was not accurate. Individual quality characteristics soluble solids, Streif index, acidity and firmness were well predicted. The
calibration model for soluble solids content resulted in a validation correlation of 0.84 SEP = 0.73 brix for the results over 2 years from one orchard, but like the Streif index, was orchard-dependent and appeared to account
largely for the orchard dependence of the latter. Acidity and firmness were predicted with a validation correlation of 0.80 and 0.78 and SEPs of 2.07 ml NaOH and 1.13 kg for, respectively, two and three orchards over the 2 years.
© 2001 Elsevier Science B.V. All rights reserved.
Keywords
:
VISNIR-spectroscopy; Streif index; Apple www.elsevier.comlocatepostharvbio
1. Introduction
To ensure a long-term storage potential of ap- ples \ 6 months, it is essential that the fruits are
harvested within a well defined optimal harvest period. During this period, the respiratory activity
of the fruits is at its minimal and during subse- quent storage, controlled conditions are used to
minimise respiratory and quality losses. If apples are harvested too early, they will not ripen suffi-
ciently upon removal from storage and will have inferior organoleptic quality. In addition, early
harvest increases the risk of superficial scald de- velopment, an important storage disorder. Con-
versely, if the apples are harvested too late, they will soften and become mealy before or during
Corresponding author. Tel.: + 32-16-322668; fax: + 32- 16-322955.
E-mail address
:
ann.peirsagr.kuleuven.ac.be A. Peirs. 0925-521401 - see front matter © 2001 Elsevier Science B.V. All rights reserved.
PII: S 0 9 2 5 - 5 2 1 4 0 0 0 0 1 4 5 - 9
subsequent marketing. Even optimum storage conditions can not compensate for losses in stor-
age potential due to the improper timing of har- vest Skrynski, 1996.
If the optimal harvest period could be predicted well prior to harvest, it would also allow the
grower to maximise harvest labour use efficiency. Two systems are currently used to predict the
optimum date for harvest. The first method utilises meteorological parameters and the num-
ber of days after full bloom Luton and Hamer, 1983. These models are generally inexpensive and
relatively easy to use, but require a relatively long history of meteorological and physiological obser-
vations. Their primary deficiency is in the preci- sion of prediction during normal production
years, which is even poorer during years with atypical weather conditions.
The second method is based on the temporal pattern of changes in individual or multiple chem-
ical and physical properties of the fruit during a well defined period before harvest Truter et al.,
1985. In addition to firmness, ethylene produc- tion, stage of starch transition, colour, compo-
nents of taste e.g. sugar content, acidity and aroma e.g. esters and alcohols are important
indicators of maturity Lal Kaushal and Sharma, 1995.
Streif 1983
developed a
prediction method based on eight fruit quality attributes
which were later simplified to three Streif, 1996. The Streif index is a combination of firmness F,
soluble solids content R and starch stage S
Index = F kg
R brixS The Streif index decreases during maturation of
the fruit until reaching the threshold value for harvest e.g. 0.08 for ‘Jonagold’ fruit in Belgium.
At this point, fruit destined for extended storage must be harvested; a technique that is used by
commercial growers in Belgium.
In the following study, data on fruit size, ground and background colour, soluble solids
content, acidity, firmness and stage of starch tran- sition were collected weekly from different or-
chards starting in mid-July. The time course of these
maturity indices
was compared
with threshold values and previous data, and predicted
harvest dates were calculated for each cultivar. Due to the large number of samples required for
the accurate prediction of harvest date i.e. eight fruit per cultivar per week, a rapid, non-destruc-
tive method is needed.
Since the late 1980s, near infrared NIR-spec- troscopy has been evaluated for measuring the
internal composition
of biological
materials Kays, 1999. The advantages of this technology
are, 1 speed of measurement; 2 multiple at- tributes can be measured simultaneously; and 3
since it is non-destructive, repeated measurements could be made on the same sample. The latter
increases the accuracy in that measurements of quality attributes of individual fruit can be made
during development while still attached to the tree.
Soluble solids have been measured in a wide range of fruit using NIR spectroscopy Kays,
1999. Kawano 1994, Kawano et al. 1992 de- veloped a linear model, using four wavelengths,
which had a SEP of 0.50 brix. In contrast, McGlone and Kawano 1998 used the entire
wavelength region between 400 and 1100 nm to generate partial least squares PLS models for the
prediction of the firmness, dry matter, and soluble solids of kiwifruit 7.8 N, 0.42 and 0.39 brix,
respectively. For tomatoes, a good correlation was also found between spectral data and soluble
solids i.e. SEP = 0.69 brix, Ruiz-Altisent and Barreiro, 1996. NIR in the 850 – 1300 cm
− 1
re- gion has also been used to predict individual
sugars, ethanol, and glycerol. The SEP values were 2.45 glucose g l
− 1
and 3.86 fructose g l
− 1
. Also Lammertyn et al. 1998 obtained good vali-
dation correlation values of 0.95 and 0.93 for, respectively, the soluble solids content and the
acidity of ‘Jonagold’ apples. Other quality charac- teristics like firmness are more difficult to predict.
Ruiz-Altisent 1993 classified 97 ‘Golden Deli- cious’ apples correctly into three firmness classes
and 76 into five different firmness classes. The acidity of different apple cultivars was examined
by means of NIR reflectance spectroscopy by Lova´sz et al. 1994. So far visiblenear infrared
VISNIR reflectance spectroscopy has not been used to predict optimal picking dates of apple
fruits.
Table 1 The number of measuring sessions weekly per cultivar, year and orchard
Year Orchard
Jonagold Elstar
Boskoop Golden Delicious
Cox’s Orange Pippin Gala
Braeburn 7
7 1997
7 Velm
6 5
– –
8 7
6 7
Velm 6
1998 5
8 Rillaar
1998 8
6 7
7 –
– 4
2 2
2 2
– –
1998 –
Lendelede
The objective of this study was two-fold, i to evaluate the potential to measure the internal
quality characteristics of apples by VISNIR-spec- troscopy in the preclimacteric phase; and ii to
predict the optimal harvest date based on VIS NIR spectra. A special attempt was made to
establish sufficiently robust calibration models that are applicable to all the different cultivars
over different years.
2. Materials and methods
