ISHS Acta Horticulturae 313: III International Symposium on Computer Modelling in Fruit Research and Orchard Management
THE DYNAMIC APPLE TREE SYSTEM: POMOLOGICAL AND CLIMATIC RELATIONSHIPS |
| Authors: | J. Zhang, G.F. Thiele |
| Abstract:
Fifteen Royal Gala apple orchards in the three main apple producing regions of New Zealand were continuously monitored for three growing seasons. One orchard is in the third additional year (6 years) of monitoring for the purpose of model validation. The orchards were 5–8 years old during the first monitoring season. Twelve of the orchards were on MM106 rootstock and the remainder on M793. Tree density ranged from 455–1102/ha. Five trees were monitored for flower and fruit numbers and fruit quality in each orchard. Climatic data from 7 meterological stations was used, incorporating temperature, sunshine hours and rainfall. For each year the orchards were monitored, climatic data was recorded for the period October in the previous growing season until harvest time (March) of the present season. Correlation calculations were attempted for all monthly combinations. Contour maps of correlation coefficients between tree parameters and monthly combinations of climatic data are presented to show the major effects of climate on fruit production. The production of multiple regressions has been focused on a range of tree parameters with relevant climatic data from the contour maps added to refine the mathematical relationships. Higher maximum temperatures in late summer (February to March) produced higher fruit set (r=0.54**) the following spring suggesting an effect on quality of the flower. Lower maximum temperatures in the late dormancy period (August to September) produced a higher fruit set (r=-0.40**) as well. The natural simple regression between fruit set and flower number per cross sectional area gives an r value of -0.47** indicating that the more flowers on a tree the lower the percentage fruit set. Introduction of the climatic effects produces a refined multiple regression with an r value at 0.82**. There appears to be an influence of sunshine hours and temperature in the early spring on the percentage of fruit thinned and this relationship could provide the basis for more accurate estimation of fruit number after thinning. It is demonstrated how fruit number after thinning can provide information on total yield, fruit size and size distribution. Average fruit size was positively correlated with November to February temperatures in the previous season and also maximum temperatures in the December to January period prior to harvest. Negative correlation was found with minimum temperatures in May. All these improved the relationship between average fruit size and fruit number after thinning, but the maximum temperatures in December and January provided more accurate information (r=0.81**) for harvest predictions. This paper provides the basis for the apple tree system model and allows the development and manipulation of management strategies. | |
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