Image Based Phenotyping of Shell Thickness Revealed Strong Association with Kernel Recovery in Macadamia

Phenotyping in macadamia breeding programs is usually laborious, time-coming, and costly. The development of rapid and cost-effective phenotyping technologies can reduce costs and increase breeding efficiency. As macadamia kernel is the only edible part of the nut, a key indicator of farm profitability is kernel recovery (KR), which is the amount of total kernel in a nut in shell (NIS). There was a general consensus, without scientific records, that a thicker nutshell results in a smaller kernel, thus lower kernel recovery. This project aims to assess the relationships between nutshell thickness and KR by using a rapid and cost-effective method. Nut samples were collected from second-generation macadamia breeding progenies grown in Bundaberg station of the Department of Agriculture and Fisheries, Queensland, Australia. A digital slide caliper and an analytical balance were used to measure manually phenotypic traits of each nut, including nutshell thickness. Pictures of samples were captured with a digital camera and processed with Image J to extract phenotypic information. Negative correlations between shell thicknesses with kernel recovery were recorded in both manual and image-based approaches. Particularly, manual measurements of nutshell thickness had correlation coefficients ranged from -0.54 to -0.59 with KR while image-based measurements of average shell thickness had a correlation coefficient of -0.87 with KR. The outcomes indicated that shell thicknesses can be used as a predictor for KR in macadamia breeding programs and more importantly, image-based measurements offered higher prediction accuracy of KR than manual measurements.