Growth and its partitioning in Prunus rootstocks in response to root zone temperature

Abstract

Abstract Rootstocks for stone fruit varieties differentially influence tree physiology and one possible explanation for these differences is that varieties vary in their response to root zone temperature (RZT). To examine the effects of RZT, two trials using actively growing plants of five different Prunus rootstocks with chill requirements between 100 and 1100 h were undertaken. Plants were grown at RZTs of 5, 13 and 19 °C for 6 weeks after which total dry matter accumulation and its partitioning amongst roots, stems and leaves was determined. In general, the magnitude of total dry matter and its component parts positively correlated with RZT and significant differences were found among varieties in the magnitude of total dry matter accumulation. Individual varieties ranked differently at the three RZTs with respect to total dry matter: in general, the same ranking was also seen in the ranking of each growth component. RZT significantly influenced partitioning causing differences in leaf, stem and root mass ratios. These differences were greatest at low RZTs and became less as RZT increased. Several patterns of partitioning were found. Firstly, the low chill varieties (Okinawa and Flordagold) were little affected by RZT with similar partitioning occurring at each RZT. Secondly, the higher chill varieties, Green Leaf Nemaguard (GL), Golden Queen (GQ) and Fay Elberta (FE), reacted more strongly to RZT and were particularly affected by the lowest RZT. For these varieties, the root mass ratio rose and stem mass ratio fell as RZT increased. However, with respect to leaf mass ratio, two different trends were found: the leaf mass ratio for FE and GQ positively correlated with RZT whilst the relationship for GL was negative. These findings suggest that the response to RZT is related to a variety's chill requirement; offer an explanation for differences in performance of rootstock–scion combinations at different locations; and will aid the development of more accurate tree performance models by taking RZT into account.