The relation between Cripps’ Pink internal browning and pre-harvest temperatures, mineral nutrition, tree age, soil type etc. in two production areas after long term CA storage and the evaluation of the non-destructive NIR technique for sorting internal, brown fruit

Pre-harvest factors temperature, soil type, tree age and mineral composition of fruit were evaluated for their role in susceptibility towards various internal browning disorders under South African growing conditions. Near infrared reflectance (NIR) spectroscopy was assessed as a non-destructive sorting technique before browning development.

Minimum, maximum, the difference between minimum and maximum temperatures (max – min) and growing day degrees above 10 °C (GDD_>10°C) were measured on five farms in each of the two production regions, Elgin and the Koue Bokkeveld (KBV). These were calculated for different physiological growth periods. Correlations between temperature parameters measured during specific growth periods and the incidence of different browning types were investigated. The relationship between browning incidence and soil type, tree age and mineral content of fruit was evaluated using six orchards in the KBV. Mineral analysis of brown and non-brown fruit from each orchard was conducted. The browning incidence found for each orchard was related to the mineral content of brown and non-brown fruit. Mineral content of brown vs. non-brown fruit, fruit from sandy soil vs. clay soil and from old trees vs. young trees were compared. Correlations were done between mineral content and browning of fruit. NIR spectroscopy was performed after long term storage and again after ripening and browning development.

The production regions did not differ significantly according to temperature parameters except for average minimum temperatures. Browning incidence differed significantly between seasons. Diffuse browning was found in both seasons while radial browning was only found for 2011/2012. Incidence of diffuse browning was related to temperature differences (max – min) during the cell division period and high temperatures during the maturation stage. Incidence of radial browning was related to maximum temperatures during the early cell expansion phase. A third type of browning which exhibited browning patterns of both radial and diffuse browning was identified and named ‘combination’ browning.

Incidence of diffuse browning was affected by soil type and tree age while incidence of radial browning did not differ between soil types and tree age. Fruit harvested from orchards with sandy soil and young trees were prone to develop diffuse browning during lone term storage. Maturity of fruit harvested from orchards with young trees or sandy soil were more advanced compared to that of fruit harvested from orchards with old trees or clay soils. A comparison of the mineral content of brown fruit with that of non-brown fruit and correlations with browning incidence indicated that the browning is influenced by the ratios of K:Mg and K:N and the K content of fruit. A low K concentration and K:Mg ratio and high Ca:Mg ratios were associated with increased incidence of browning.

NIR spectroscopy proved to be an accurate means of determining TSS non-destructively. Prediction accuracy before browning development after storage for browning development after shelf-life depends on fruit number and an overall accuracy of between 82% and 71% was achieved.

The effect of temperature during fruit growth and development could possible predispose the fruit to browning development. This could be achieved by affecting the structure of the cell membrane, fruit density or by interrupting the accumulation of photosynthates.

Fruit harvested from young orchards were prone to development of IFB. Unbalanced mineral ratios related to low potassium levels and high Mg levels could affect the Ca content of fruit negatively. Without sufficient Ca the protection mechanisms of the fruit is insufficient for long storage purposes. NIR can successfully be used to predict TSS per fruit and browning prediction accuracy on a commercial line would increase with high fruit numbers of affected and non-affected fruit but should be evaluated.