Articles
THE USE OF LEAF ANALYSIS IN PREDICTING STORAGE QUALITY OF APPLES
Advantages were supposed to be that leaf sampling and determination of crop factors early in August would make possible timely recommendations of measures to be taken to reduce losses in storage procedures to bitter pit and other related disorders, or even due to low temperature breakdown.
In addition, leaf analytical data can be used to determine fertilizer requirements.
During 1969–1972, the reliability of this prediction has been tested in an extensive joint correlation study in 28 orchards, in which several persons cooperated.
Numerous crop factors and leaf and fruit analytical data were recorded.
The results were analysed by Dr J. Van der Boon and Mr A. Das of the Institute for Soil Fertility in Groningen.
The main conclusion was that prediction of bitter pit class based on crop factors and on the (K+Mg)/Ca ratio in the leaves correlated well with bitter pit after storage, but only in years of severe bitter pit infestation.
At their best correlation coefficients were approximately r=+0.75. In years with moderate or little susceptibility to bitter pit, more pit was systematically predicted than actually appeared.
The large year-to-year variations suggest that other factors apparently have an influence on bitter pit as well.
In a literature study on Cox’s Orange Pippin, covering a period of 28 years estimations were made of relative differences in annual losses on a country-wide scale, due to bitter pit.
Also, estimations were made of year-to-year variations in bearing levels and in fruit size (irrespective of bearing). Data on weather conditions (temperature, sunshine, precipitation) were recorded.
Significant correlations were found to exist between estimated annual variations in fruit size and bitter pit, and deviations from normal average temperatures in June-September.