Advancing sustainable and technology driven apple orchard production systems (AP19003)

What was it all about?

From 2020 to 2023, this project improved orchard design and crop load management in a variable climate by providing knowledge and tools to consistently deliver premium fruit that meets consumer expectations.

Physiological studies on chemical signalling, floral initiation, fruit quality and yield under different light environments, crop loads and rootstocks, and the calibration and validation of sensing technologies for estimates of productive performance and fruit quality were undertaken in the Sundial apple orchard at the Tatura SmartFarm and in commercial apple orchards. The technology was evaluated for its performance and suitability for the industry.

'ANABP 01' apples grown on M.26 and M.9 rootstocks achieved higher values of total tree light interception compared to Bud.9, and in turn intercepted light was positively correlated with yield. Fruit quality was best in Bud.9 but canopy vigour of trees grown on this rootstock may not be suitable to support higher crop loads and its sparseness may increase the risk of sunburn damage. Increasing light exposure led to improved fruit quality without significant sunburn, although the summer seasons in which the study was conducted were mild. Using UV-filter on fruit produced undesirable yellow-orange peel colouration indicating that UV light, in addition to visible light, is a key to the appealing dark-red colour development in this cultivar. Fruit from east – west rows of trees had the lowest overcolour and sweetness and were delayed in maturity.

In ‘Rosy Glow’, a crop load of 8 fruit per cm2 of trunk cross-sectional area achieved the most consistent return bloom and fruit quality over five seasons. In ‘Ruby Matilda’, 6.5 – 7 fruit per cm2 of trunk cross-sectional achieved return bloom and crop load consistency, while maintaining high yields and adequate fruit quality. In multileader trees, individual leaders should be used as management units—as opposed to whole trees—to reduce within-tree and -orchard spatial variability.

The spur bud metabolites hydroxycinnamates, coumarins, salicylates and flavanols were negatively affected by crop load in ‘Rosy Glow’. Cytokinin precursors and derivatives such as adenosine and inosine were positively correlated with crop load in ‘Ruby Matilda’ spur buds. Gibberellic acid differences were identified in fruitlet seeds from trees with different crop loads, linked to a negative regulation of flavanols via gibberellic acid.

Calibration and validation of a commercial platform for flower number, fruit number, fruit size and fruit colour prediction revealed prediction errors below ten per cent in commercial apple orchards. The platform could be used to extract data on canopy and crop parameter and to extrapolate orchard-specific relationships that can be used to limit spatial variability while maintaining high yields and quality.  The technology provided data quicker, more objectively and more reliably than if gathered by people on the ground. The use of technology such as the one used in this study is recommended for industry adoption in commercial orchards and for research application.

This project was part of the PIPS3 program for the apple and pear industry (the third iteration of the Productivity, Irrigation, Pests and Soils program). The other investments that made up this scope of work were:

• Strengthening cultural and biological management of pests and diseases in apple and pear orchards (AP19002)
• Developing smarter and sustainable pear orchards to maximise fruit quality, yield and labour efficiency (AP19005)
• Improved Australian apple and pear orchard soil health and plant nutrition (AP19006)
• Independent program coordination for apple and pear productivity, irrigation, pests and soils program (PIPS3) (AP19007)