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Technology driven apple orchards

Technology & Data

Researchers have been using smart tech and biotech to investigate how to improve orchard design, crop load management decisions, and fruit quality and production. 

For the past three years researchers at Agriculture Victoria have been working on the levy-funded PIPS3 Advancing sustainable and technology driven apple orchard production systems (AP19003) project. Now complete, there are four key outcomes from this project:  

  • Reliable sensing technology is now available to measure apple productivity. 
  • Plant signals associated with high bloom in the subsequent season were identified. 
  • Row orientation and rootstock vigour impact fruit exposure to direct sunlight. 
  • Increasing crop load reduces fruit quality, delays maturity and affects the following season flowering and fruit set. 

Mobile sensing platform (Green Atlas Cartographer) 

Using machine learning to analyse thousands of photos taken from two cameras mounted on a mobile platform – for example an ATV – fruit in an orchard can now be detected and flower and fruit number, fruit clustering, fruit diameter and peel colour can be estimated. Light detection and ranging (LiDAR) technology mounted on the same platform scans the canopy and is processed to provide estimates of the foliage density and the canopy dimensions (tree height and cross-sectional area). Calibration, validation and evaluation of this technology was undertaken during PIPS3.  

The maps produced by Green Atlas can be used by growers to make management decisions, such as targeting ‘hot spots’. For example, an orchard block may need to have follow-up hand thinning to reduce the number of fruit or to break up clusters. Areas to focus autumn pruning, leaf blowing or laying reflective mulch to increase colour can be identified. In addition, the data provides pre-harvest estimates of yield and fruit size distribution. 

Figure 1: Cartographer operating in a commercial apple block in the Goulburn Valley. The map to the right shows the variation in fruit colour across a block of Ruby Matilda at Plunkett Orchards in Ardmona just prior to harvest. The block had been leaf blown several weeks prior to being scanned, apart from one row which is visible on the map by the greater amount of green dots.

Plant signals related to flowering 

Plant hormones – naturally occurring chemical signals – associated with high bloom in the subsequent season were identified in apple buds. These included cytokinin precursors like inosine, a ‘close relative’ of abscisic acid, flavanols and several phenylpropanoids and their derivatives.  

Identifying these signals was not a menial task. Firstly, an experiment was established to vary floral induction by crop load. Buds were then sampled during spring and early summer from the various crop load treatments. Then the buds were dissected so that the growing tip could be chemically analysed using a process often referred to as metabolomics. This method identified every known chemical in the growing tip. The final step was to crunch the data and highlight the chemicals where their concentration was related to crop load.  

The next phase of PIPS 4 Profit research will apply some of these chemicals to apple trees and observe the floral induction and flowering response. The effects of netting systems and various industry PGRs on floral induction will also be investigated. 

Figure 2: The chemical structure of inosine, one of the plant signals found in apple buds that was related to high flower numbers in the subsequent season.

Sun exposure, fruit colour and fruit damage 

Studies in the Sundial Orchard at the Tatura SmartFarm using the cultivar ANABP 01 (marketed as Bravo®) showed that fruit exposed to direct sunlight had increased dark red colour coverage; however, sudden exposure of fruit to sunlight during summer should be avoided to prevent sunburn damage. Light ‘quality’ may also be critical in colour development as was evident when blocking ultraviolet (UV) light caused yellowing. Furthermore, row orientation impacted fruit exposure to direct sunlight; fruit in east–west oriented rows are likely to have less colour coverage and fruit in north–south rows are more susceptible to sunburn. 

Figure 3: Sudden exposure of ANABP 01 fruit to direct sunlight resulted in sunburn damage (left). An ultraviolet filter above ANABP 01 fruit resulted in distinct yellowing (right).

Crop load 

Results from field experiments in commercial orchards showed that increasing crop load increased yield to a biological plateau, but at the same time delayed maturity and reduced fruit size, red colour, soluble solids concentration (i.e. sweetness), tree growth and return bloom. In addition, the results showed that a high crop load reduced the number of fruit that set in the subsequent season and may have impacted on fruit size – most likely due to the lack of stored carbohydrate in the woody tissue of the tree.  

The experiment in the Goulburn Valley on 2-leader Ruby Matilda trees was set up to study how localised these crop load effects were within a tree. One leader was set to either a low or a high crop load, whereas the second had a range of crop loads from low to high. Return bloom impacts from a high crop load were localised. In other words, a high crop load on one leader resulted in a decrease in return bloom on that leader irrespective of the crop load on the second leader.  

The next phase PIPS 4 Profit project will continue to explore the opportunity to use mobile sensing to set orchard-specific crop load targets. Here, the data collected from a platform like Cartographer will be used to establish relationships between yield parameters, for example, the relationship of crop load (i.e. fruit number adjusted for canopy cross-sectional leaf area) to fruit diameter. A thinning map for an orchard block can then be generated based on the target fruit size for that cultivar. Furthermore, PIPS 4 Profit will determine the financial benefits and costs of undertaking such spatial management based on orchard scanning using a mobile sensing platform. 

Further information 

Visit the PIPS3 Program’s Advancing sustainable and technology driven apple orchard production systems (AP19003) project webpage: 


Peavey M (2022) “Rootstocks, canopy architecture and fruit quality of ‘ANABP 01’ apples”, Australian Fruitgrower 16(1):38–39. 

Peavey M (2023) “Understanding apple sunburn damage in response to sunlight”, Australian Fruitgrower 17(2):48–51. 

Plozza T and Frisina C (2021) “Effects of crop load on fruit quality in ‘Rosy Glow’ apples”, Australian Fruitgrower 15(4):44–45. 

Reddy P, Plozza T, Rochford S and Goodwin I (2022) “Turning off biennial bearing”, Australian Fruitgrower 16(3):48–49. 

Scalisi A (2022) “Unveiling apple block variability using Green Atlas Cartographer”, Australian Fruitgrower 16(2):51–52. 


“Tech-driven fruit diameter and colour measurement”,

“Sensing technologies to improve predictions and management of crop load”,

“Crop load management: Signalling compounds that induce flowering”, 

“Managing orchard data with smartphone technology”, 


The PIPS3 Program’s Advancing sustainable and technology driven apple orchard production systems (AP19003) project and upcoming PIPS4 Profit Program’s Apple production systems (AP22002) project are funded by Hort Innovation, using the apple and pear research and development levy, contributions from the Australian Government and co-investment from Agriculture Victoria (PIPS3 and PIPS4) and the Tasmanian Institute of Agriculture (PIPS4). Hort Innovation is the grower-owned, not-for-profit research and development corporation for Australian horticulture. 

This article was first published in the Spring 2023 edition of AFG.

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