Maturity, Ripening, and Quality Relationships 71
this inherent variability, providing improved consistency in quality and improved
confidence by buyers and consumers. Schouten et al. (1997) have developed a crop
growth model that uses individual fruit chronological age as a predictor of the shelf
life potential of greenhouse-grown cucumbers. They went further to develop a color
analysis model using red and green color intensity ratios (measured with a color
digital camera) as an accurate predictor of shelf life for 95% of the fruit within a
single grower harvest (Schouten et al., 2002). This approach could be used for any
green vegetable for which yellowing is the indicator of end of useful shelf life.
Another modeling approach has been to improve the reliability of the existing starch
indexing method used to estimate maturity in apples. Starch indexing often involves
assessment of the relative amount of clearing (area of tissue not reactive to iodine)
that is present at a point in time in an iodine-stained section of apple (Smith et al.,
1979). However, that approach is subject to a myriad of errors. As an alternative, a
nonlinear model can be assumed from past experience and sets of data points from
the current year fitted to the model, producing a modified model that would inher-
ently account for seasonal differences. As a result, the actual value collected at any
point in time during the season becomes less important than the pattern of changes
described by the model fitted with the actual value and the previously collected data
points for the season. Such an approach to using starch test values has been found
to greatly improve the predictive power of starch testing (Peirs et al., 2002). These
examples demonstrate that modeling can improve maturity estimation in nonclimac-
teric (cucumber) and climacteric (apple) fruits.
3.6 SUMMARY
Maturity has a great influence on quality and perceived deterioration in storage, but
it must be kept in mind that maturity is a relative measure and should be used
cautiously. Factors such as crop year, specific orchard, fruit position on the tree, and
temperature history during crop growth can influence the relative importance of
maturity on quality retention in apples (Knee and Smith, 1989; Ferguson et al.,
1999). For example, aroma may be significantly influenced by small differences in
maturity in some years in some orchards, but it may not be significantly influenced
until there are large maturity differences in other years (Knee and Smith, 1989). To
make matters worse, not all quality characters respond similarly in relation to maturity
in different years and in different orchards (Knee and Smith, 1989). It is for this reason
that single-criterion approaches to measuring maturity for harvest are considered to be
risky and multicharacter measures are recommended (Lau, 1985; Harker et al., 1997).
This also points to the fact that the molecular and biochemical bases of maturity and
ripening processes and their interactions are only superficially understood.
Proper and reliable estimation of optimal maturity for harvest or use can ensure
maximal quality and quality retention for all fruits and vegetables. However, there
are gaps in understanding of maturity criteria that will require further work. As in
the case of apples, improvements in maturity assessment have led to significant
improvements in storage quality in the past (Lau, 1985). If further improvements
are to be seen over the range of horticultural commodities grown worldwide, com-
modities other than apples must receive increased attention.