Although leaf tissue analysis provides good information on the nutritional status of fruit trees; numerous studies of apples over several decades found only fruit mineral content particularly Ca was correlated to fruit quality.  Marcelle (1990a) found poor correlation between leaf and fruit mineral content in apples over a 12 year period, which would explain why leaf analysis is not particularly useful for predicting fruit quality.  Fruit quality attributes such as fruit colour, size, storage breakdown potential, bitter pit, stem-end cracking, lenticel breakdown and russetting in apples are of commercial interest to growers to be able to predict (Fallahi et al, 2010).  Most research on fruit analysis has been done on apples, so these results will mainly be discussed.

Researchers at the East Malling Research Station in the UK have published many studies on measuring fruit mineral content and relating the results to storage quality in Cox's Orange Pippin apples (Perring, 1968).  They found that Ca less than 3 mg/100 g fresh weight and P less than 8 mg/100 g fresh weight was likely to make Cox's Orange Pippin apples susceptible to senescent breakdown in early storage.  Over the years, more research has related apple fruit mineral analysis with bitter pit and other storage problems.  Studies have indicated that high Mg/Ca, K/Ca and N/Ca ratios may also lead to bitter pit (Amarante et al, 2013).

Fallahi et al. (2010) report that fruit analysis alone or with leaf tissue analysis was useful in making models to predict fruit quality.  From models, Ca and N in only fruit could be used to predict bitter pit in apples.  Monitoring Ca and N as well as P and K within a year as well as between years was found to be a reliable method to predict fruit quality.  Boron in fruit was found to be more sensitive than leaf B as an indicator of B soil and foliar applications.  Fruit B could be used to predict fruit softening and internal breakdown in storage.  Existing modeling therefore cannot give a perfect prediction on the storage quality of apples, but at least provides an indication of potential problems.

Fruit analysis can help determine fruit storage quality, but it does not allow a correction to be made.  For apples, early season fruitlet analysis (typically picked in early July) can allow a grower to proactively affect mineral levels if needed (Wolk et al., 1998; Brooks, 2001).  Fruitlet analysis therefore has an advantage over fruit analysis.  Large databases and software have been established in different parts of the world to allow growers to predict mineral content at harvest from fruitlet analysis (Brooks, 2001).  The software gives a percentage probability of a sub-optimal nutrient content occurring in the fruit at harvest.

With both fruit and fruitlet analysis, a mineral deficiency alone may not explain whether a quality or storage problem may occur.  Various orchard factors and cultural practices such as irrigation, rootstocks, fertigation, and foliar sprays have been found to affect apple fruit mineral composition as well (Fallahi et al., 2010).  Ross et al. (2020) examined the relationships among orchard growing factors, Staccato cherry fruit mineral content and fruit quality.  They found correlations between both orchard growing factors and cherry fruit mineral content with fruit quality.  Fruit quality prediction therefore may improve as other factors along with fruit and fruitlet mineral analyses are modelled. 

Fruit and Fruitlet Sampling

Reviewing the literature, there is no standardized procedure for taking and preparing fruit and fruitlet samples.  Several factors affect the accumulation of minerals in fruit so should be considered when obtaining samples and preparing them.  Most research has been done on apples, so suggestions can be found for their sampling.  For other fruits, little information is available.  Regardless, for any fruit, consistent procedures need to be followed so results can be compared over time. 

            Ferguson and Triggs (1990) made a few observations about taking apple samples for predicting bitter pit in Cox's Orange Pippin apples.  
They found:

•  sampling fewer fruit per tree over many trees minimized variability in mineral analyses and increased prediction of bitter bit. 

• There was as much variability between fruit within a tree than between trees.

• Taking opposite plugs of cortical tissue from each fruit also reduced variability. 

• Fruit from the upper parts of trees had less Ca and were more susceptible to bitter pit.

• Ca concentration decreased with increasing fruit weight, but this effect was half the decrease in trees with a heavy crop compared to trees with a light crop. 

• Fruit taken from the inside or the outside of a tree had similar Ca, Mg and K concentrations.  It is therefore important to have a sampling procedure that is consistent and provides a representative sample for analysis. 

For apples, fruit samples are usually taken 2-3 weeks before harvest and fruitlet samples are taken in early July (Brooks, 2011).  Marcelle (1990b) found most studies used a sample of 20 - 25 apples for analysis.  For fruitlets, Marcelle (1990b) suggests using 50 fruitlets picked in July. 

When preparing samples for analysis, the stems and seeds should not be used since these parts contain higher mineral content (Perring & Wilkinson, 1968).  Amarante et al. (2013) discuss several other factors to consider for preparing apple samples.  One is that the Ca concentration decreases from the stem to the calyx end of an apple due to the reduction in xylem functionality.  The calyx end of apples are therefore more susceptible to bitter pit.  Another factor is that the peel contains more mineral content than the flesh.  If there is any residual spray on the peel, this can affect values so fruit should be washed with distilled water prior to processing a sample.  Various papers have suggested different techniques to cut out samples using peel, flesh, or peel + flesh to get a consistent sample.  Amarante et al. (2013) found that peel was a better sample for Fuji apples that had low bitter pit susceptibility while flesh was a better sample for Catarina apples that had high bitter pit susceptibility.  Since several factors affect the amount of minerals that may be in a sample, a sampling procedure that is consistent must be used to get a reliable analysis.

Fruitlet analysis has been successfully used by the BC apple industry to help determine the storage potential of its crops for more than 30 years.  It has helped the apple industry differentiate between blocks with strong and weak storage potential and has served as a guide to growers in their nutrient programs to help them produce higher quality, longer storing fruit.  Leaf and fruitlet nutrient profiles can be used to assess the current year's status and to adjust next year’s nutrient management in the orchard.

In a study on sweet cherries in Okanagan Valley, BC by Wolk et al. (2014; not published), high leaf N was associated with lower fruit soluble solids and leaf Ca was negatively correlated with fruit pebbling.  They observed that the incidence of split cherries was greater in fruit with higher levels of B.  The extremely high levels of cherry leaf and fruitlet B found in a high percent of the orchards sampled in 2014 bears investigation as to whether or not there are any observable negative consequences.  In a more recent study currently submitted and under review, fruit P and K were negatively correlated with fruit respiration and pitting (Ross, et al. 2020).

Typical Fruit and Fruitlet Mineral Contents

            As previously mentioned, the mineral content in fruits and fruitlets can differ by variety, sampling time, preparation and analysis method among other factors.  Table 6 shows examples of typical values obtained in apples and cherries.  Table 7 gives an example of optimum values for Ambrosia fruitlets sampled six weeks before anticipated harvest on a fresh weight basis. Table 8 shows the minimum Ca concentrations in apple varieties to reduce the Bitter Pit incidents.