Evaluation of avocado fruit maturity with a portable near-infrared spectrometer

Abstract There is considerable financial incentive for avocado ( Persea americana Mill.) growers in South Africa to begin harvest as soon as the minimum fruit maturity has been reached. The need to quickly process a large amount of samples for maturity determination pre- and postharvest using a user-friendly instrument provided motivation this study. ‘Fuerte’, ‘Hass’ and ‘Carmen ® -Hass’ fruit were included in the calibration of the portable near-infrared spectrometer. The calibration included fruit from three seasons and the external validation included fruit from two further seasons. With this portable NIR spectrometer, it was not possible to develop a calibration model to accurately measure the maturity of avocado fruit non-destructively (‘Fuerte’: R 2  = 0.654, RMSECV = 2.62, RPD CV  = 1.23, ‘Hass’ and ‘Carmen ® -Hass’: R 2  = 0.400, RMSECV = 2.94, RPD CV  = 0.79). A model incorporating all three cultivars, with the fruit peel removed, provided comparable results to the commercial method when using at least four fruit per sample (R 2  = 0.732, RMSEP = 1.83, RPD = 1.14). The measurement of a single fruit took 30s, and could be conducted pre- or postharvest.

[1]  Z. Schmilovitch,et al.  Determination of avocado maturity by near-infrared spectrometry , 2001 .

[2]  C. Schroeder.  Physiological Gradient in Avocado Fruit , 1985 .

[3]  B. B. Wedding,et al.  Non-destructive prediction of 'Hass' avocado dry matter via FT-NIR spectroscopy. , 2011, Journal of the science of food and agriculture.

[4]  Dolores Pérez-Marín,et al.  Miniature handheld NIR sensor for the on-site non-destructive assessment of post-harvest quality and refrigerated storage behavior in plums , 2010 .

[5]  Lembe S. Magwaza,et al.  A Review of Destructive and Non-destructive Methods for Determining Avocado Fruit Maturity , 2015, Food and Bioprocess Technology.

[6]  M. Sánchez,et al.  On-Vine Monitoring of Grape Ripening Using Near-Infrared Spectroscopy , 2012, Food Analytical Methods.

[7]  C. Greensill,et al.  Sorting of Fruit Using near Infrared Spectroscopy: Application to a Range of Fruit and Vegetables for Soluble Solids and Dry Matter Content , 2004 .

[8]  Dolores Pérez-Marín,et al.  Internal and external quality assessment of mandarins on-tree and at harvest using a portable NIR spectrophotometer , 2013 .

[9]  J. P. Bower,et al.  Influence of water and ABA supply on the ripening pattern of avocado (Persea americana Mill.) fruit and the prediction of water content using Near Infrared Spectroscopy , 2009 .

[10]  V. A. McGlone,et al.  Dry matter determination in ‘Hass’ avocado by NIR spectroscopy , 2003 .

[11]  B. B. Wedding,et al.  Effects of seasonal variability on FT-NIR prediction of dry matter content for whole Hass avocado fruit , 2013 .

[12]  Dolores Pérez-Marín,et al.  Non-destructive characterization and quality control of intact strawberries based on NIR spectral data , 2012 .

[13]  A. Kader.  FRUIT MATURITY, RIPENING, AND QUALITY RELATIONSHIPS , 1999 .

[14]  Lembe S. Magwaza,et al.  Non-destructive evaluation of avocado fruit maturity using near infrared spectroscopy and PLS regression models , 2016 .

[15]  I. Ferguson,et al.  IMPACT OF SUN EXPOSURE ON HARVEST QUALITY OF 'HASS' AVOCADO FRUIT , 1999 .

[16]  Dolores Pérez-Marín,et al.  Testing of a local approach for the prediction of quality parameters in intact nectarines using a portable NIRS instrument , 2011 .

[17]  M. Hertog,et al.  Systems to characterise internal quality of fruit and vegetables , 2006 .

[18]  Mary Lu Arpaia,et al.  Development of a New Method for Measuring Minimum Maturity of Avocados , 2001 .

[19]  Miguel Lopo,et al.  A Review on the Applications of Portable Near-Infrared Spectrometers in the Agro-Food Industry , 2013, Applied spectroscopy.