The kiwifruit industry monitors quality by following cosmetic, shape, size, SSC accumulation, DM and time-variable defects (softening, rots and storage disorders) (Benge and Kay, 2003; Maguire and Mowat, 2003). The industry assesses fruit quality to meet in-market export and customer acceptable quality limits. For kiwifruit, the acceptable quality limits define the very small numbers of defects that consumers are willing to accept. These acceptable quality limits of defects ranges from 0 - 2% of the fruit lot but in some cases (e.g. packaging defects) it is up to 5% (Personal communication). For some quarantine related defects (diseases), there is a zero tolerance limit. However, an acceptable quality limit does not mean a desirable level. Consumers usually can tolerate a few more defects to a certain level higher than acceptable quality limit that is called threshold limit. However, the consumer is not willing to tolerate or accept the produce beyond the threshold limit (Reid and Sanders, 2007).
Product acceptability depends on quality and consumer’s acceptance limit of defects.
Acceptance limit is influenced by economical and psycho-social limits of the consumer, while the product quality is defined by inherent properties (Tijskens and Polderdijk, 1996). For kiwifruit, acceptance limits for quality aspects are defined by the industry to take into account the consumer acceptance and fruit quality after harvest. Flesh firmness is the key determinant of kiwifruit quality for export and consumption. The firmness of
‘Hayward’ kiwifruit at harvest generally ranges from 6 to 11 kgf, it considered to be eating soft at ~ 0.5 - 1.0 kgf (Woodward, 2006). New Zealand kiwifruit industry standards are such that lines of fruit should not be exported if the mean firmness (measured by penetrometer) falls below the export threshold level of 11.8 N or 1.2 kgf, and individual fruit firmness must be higher than 9.81 N or 1.0 kgf (Jackson and Harker, 1997; Benge, 1999). However, with the recent understandings of variability within kiwifruit populations, use of average firmness to compare lines for storage potential is discouraged. It has been redefined that fruit with lowest firmness have importance to dictate the longevity or storability of a lot (Tanner et al., 2012).
The acceptable quality limit for the frequency of soft defects in lot of kiwifruit is standardised as 1.3% (as upper specification limit; personal communication). Upper
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limits are set to assure the quality of a lot is at a desired threshold level when product reaches the customer. Standards are designed to be easy to follow for making rapid decisions regarding rejection or acceptance of a fruit lot. Numerical (in proportion or percent) limits of defects to accept and reject depends entirely on the sample size as a function of population or lot. Sample size has huge importance for crops like kiwifruit that exhibit substantial variation for flesh firmness between fruit within a batch (Feng et al., 2003a). Acceptable quality limits for different defects also varies with sample size to accept or reject a lot. The discrimination power of a sampling size can be explained in a graphical form known as operative characteristics (OC) curve (Reid and Sanders, 2007). An OC curve displays the probability or chance (%) of accepting a good or bad (both) batch, given various proportions (%) of defects in the lot (Figure 2.3).
Defect of lot (%) 0 1 2 3 4 5 6 7 8 9 10 P ro ba bilit y o f a cc ap ta nc e ( % ) 0 10 20 30 40 50 60 70 80 90 100 Sample size (n) = 300 9 3 6 12 15 Accaptance no (c)
Figure 2.3: Operating characteristics curves for sample size of 300 with different acceptance numbers.
Hypothetical OC curves have defects of lots on x-axis and probability of acceptance on y-axis. Each curve represents probability of acceptance or rejection of a lot (sample size (n) = 300) at particular acceptance number (c) of defects (known as lot quality or proportion of defects). Proportion of defects represents the acceptable quality levels, which a consumer can accept in the whole lot of produce (Reid and Sanders, 2007). The steeper the slope of the OC curve, the more discrimination can be derived between
‘good’ and ‘bad’ by the chosen sample size. Probabilities of lot acceptance with given different levels of defects are obtained by using cumulative binomial distribution (Reid and Sanders, 2007).
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For an acceptable limit of soft fruit (1.3%) in a lot, the OC curve can be interpreted for a sample size of 300, at acceptance number 9 (fruit with firmness less than 1 kgf), there is 99% probability of rejecting a lot with more than 1.3% of soft fruit. For a different sample size, the acceptance number will be different to meet the standard of acceptable quality limit. Likewise, the acceptance number can vary for different kinds of defects. Increase in sample size would require higher acceptance number. However, a decrease in sample size would result in lower acceptance number for any defect and it can decrease the chance of accepting a lot with acceptable quality limits. An increase in the proportion of defects in any particular lot can decrease the chance of accepting it (Reid and Sanders, 2007). Different sample sizes can be tested for the potential to reject or accept a lot at any particular acceptable quality limit.
Kiwifruit industry follows ISO-2859 regulations of quality control to select sample size from fruit populations to apply standards of acceptable limits for different types of defects. Sample size of 300 is usually observed as per ISO standards to test a population or lot of fruit for export threshold limits (personal communication). For ease of application, acceptable quality limits for any defect of kiwifruit has been manipulated to decipher fractile of a sample. Fractile is an industrial approach of evaluating a fruit lot as per export standards and generally described as a defined fraction of population above or below a specific threshold limit (Jordan and Loeffen, 2013). Presence of soft defect or fruit has prime importance to accept or reject a population of kiwifruit for export. Fractile of soft defects in a population is called soft fractile (SF). SF shows the firmness value of that softest fruit beyond which the acceptable quality limit exceeds and lot can be rejected if SF is less than 1 kgf. Acceptable quality limit of soft defect (1.3%) is assessed as SF, which becomes the acceptance number of 9th lowest firmness value of sample size of 300 fruit. This means for export threshold, any lot with 8 fruit having firmness less than 1 kgf in a sample of 300, is considered acceptable while lots with 9 or more fruit with firmness less than 1 kgf are rejected. SF represents the firmness of softest 3% fruit of a batch/line/lot/grower, which are the first to soften during storage. Industry usually monitors firmness losses during storage and uses SF information to compare different grower lines or batches for storage performance and to make inventory decisions (Adams et al., 2010).
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