Centre for Plant & Water Science - Central Queensland University

Centre for Plant & Water Science 2008 Annual Report
NEAR INFRARED SPECTROSCOPY FOR PREDICTING B74
MANGO MATURITY AND EATING QUALITY
SUMMARY
This projects represents the second year of a three year funded activity within a larger DPI
led, HAL-Harvest Company funded project “Development of Best Practice Pre- and Post-
Harvest Protocols for Production of B74 Mango, Phase II”. In a previous season, we have
demonstrated that handheld unit can be used to predict DM and internal flesh colour in
intact and just-harvested fruit, ºBrix in ripe fruit, and ºBrix of ripened fruit from spectra
collected at the just-harvested stage. In the current project, we aim to extend this work done
in previous years on Calypso mango, to confirm the robustness of the handheld unit in field
conditions, advancement of handheld technology, and develop agronomic protocols for
uniform and better mango maturity prediction.
The previous season’s work was done testing both a portable laboratory-based NIRS unit
connected to a laptop computer (the Shoebox system) and a portable handgun. During this
season a portable handgun was utilised throughout the season and in some instances an online
Insight unit was trialed along with the handheld unit. Trials were conducted near
Darwin, Katherine, Mareeba and Bundaberg.
Key findings
Accuracy of the handheld NIR (iQ unit) under field conditions
Based on two seasons results, the unit can be used with fruit over a range of temperature and
ambient light conditions, however the instrument should be kept as cool as possible (e.g.
storage in shade rather than in sun). Use of the instrument on exceptionally hot days (> 40º
C) is not recommended.
Predicting flesh colour and % DM
Results indicate that models could be used across varieties through the growing season and
between growing seasons if the model calibration population adequately represented the
variation present in the new populations.
A quality control procedure is recommended for the next few seasons at least. This would
involve confirming the accuracy of the unit’s estimates of % DM and flesh colour by
scanning about 20 fruit then measuring actual flesh colour and % DM for each fruit and
averaging the results from the unit estimates and actual measurements. This should be done
several times during the season and for each region.
Prediction of flesh colour was not as robust, with large bias values skewing RMSEP (Root
Mean Square Error of Prediction) values. It is recommended that a single model cannot be
used across all growing districts, and that a model updating or bias adjustment procedure is
required. Model performance should be checked on each farm, as outlined above.
Predicting ripe fruit ºBrix
As expected, the on-line InSight unit performed slightly better than the handheld iQ unit.
However, DM content was well predicted by the iQ unit in fruit at the hard green stage, and
the ripe stage TSS is well correlated to % DM at the hard green stage. Therefore NIRS
should be able to predict ripe fruit ºBrix by scanning fruit at harvest.
It is recommended that this issue be re-considered using a model developed using a wider
range of DM and thus ripe fruit ºBrix values. Alternatively, as the link between DM and
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