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Technologies for forecasting tree fruit load and harvest timing—from ground, sky and time

journal contribution
posted on 17.12.2021, 00:19 by Nicholas AndersonNicholas Anderson, Kerry WalshKerry Walsh, Dvoralai Wulfsohn
The management and marketing of fruit requires data on expected numbers, size, quality and timing. Current practice estimates orchard fruit load based on the qualitative assessment of fruit number per tree and historical orchard yield, or manually counting a subsample of trees. This review considers technological aids assisting these estimates, in terms of: (i) improving sampling strategies by the number of units to be counted and their selection; (ii) machine vision for the direct measurement of fruit number and size on the canopy; (iii) aerial or satellite imagery for the acquisition of information on tree structural parameters and spectral indices, with the indirect assessment of fruit load; (iv) models extrapolating historical yield data with knowledge of tree management and climate parameters, and (v) technologies relevant to the estimation of harvest timing such as heat units and the proximal sensing of fruit maturity attributes. Machine vision is currently dominating research outputs on fruit load estimation, while the improvement of sampling strategies has potential for a widespread impact. Techniques based on tree parameters and modeling offer scalability, but tree crops are complicated (perennialism). The use of machine vision for flowering estimates, fruit sizing, external quality evaluation is also considered. The potential synergies between technologies are highlighted.

History

Volume

11

Issue

7

Start Page

4

End Page

37

Number of Pages

37

eISSN

2073-4395

Publisher

MDPI AG

Additional Rights

CC BY 4.0

Language

en

Peer Reviewed

Yes

Open Access

Yes

Era Eligible

Yes

Journal

Agronomy