What was it all about?

Avocado productivity is influenced by irregular bearing, which is a significant industry challenge. The three drivers of irregular bearing are poor fruit set, high fruit abscission and biennial bearing.

This investment examined the methods and tools needed to monitor carbohydrate status in avocado orchards, as a way of predicting yield and understanding fruit set. The research team made recommendations for a pathway to develop a non-destructive method for rapid assessment of avocado carbohydrate status, at scale, in the field.

The team worked closely with levy-funded project, Maximising yield and reducing seasonal variation (AV16005), which provided strong evidence that tree physiology, as reflected by the carbohydrate status, is a key driver for fruit drop. That team was also investigating whether carbohydrate status is linked to flowering and fruit set, providing the ideal opportunity to identify a non-destructive system for evaluating the carbohydrate status of avocado trees.

As a first step, the team reviewed the available technologies and assessed them for potential development as a tool for commercial use. Two options were identified:

• Near-infrared (NIR) reflectance spectroscopy was found to have the greatest potential as a cost-effective and rapid way to assess carbohydrates in trees.
• Photothermal Quotient (PTQ) has been used successfully as a surrogate of carbohydrate levels for estimating yield in annual plants and to evaluate environmental stress impacts at different times during the reproductive cycle for yield influences.

Both approaches were subject to proof-of concept testing:

• NIR was assessed in a laboratory-based trial using field collected samples and hardware for on-the-go field measurements. Carbohydrate models and machine learning tools were applied to correlate features of the reflectance spectra with the identified carbohydrates. Results confirmed that NIR reflectance spectroscopy has potential as a tool to assess total non-structural carbohydrates.
• The use of PTQ as a tool was also tested, with regional long-term climatic data and seasonal environmental conditions assessed for potential impact on yield, with multi-season starch measurements from previous Australian and US studies. These studies showed a close association over several seasons between stem/branch starch levels and the monthly mean PTQ, indicating its potential for development as an in-season assessment tool.

These recommendations were shared with industry, for potential further development in support of the Australian avocado sector.