Joe Panozzo
University of Melbourne
122 Papers
901 Citations
Joe Panozzo is an academic researcher from University of Melbourne. The author has contributed to research in topics: Biology & Population. The author has an hindex of 33, co-authored 107 publications. Previous affiliations of Joe Panozzo include Commonwealth Scientific and Industrial Research Organisation & Government of Victoria.
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Papers
Discriminant Analysis of Defective and Non-Defective Field Pea (Pisum sativum L.) into Broad Market Grades Based on Digital Image Features.
TL;DR: An objective Linear Discriminant Analysis (LDA) model was developed to classify market grades of field peas based on seed colour, shape and size traits extracted from digital images which correctly classified over 97% of all validation samples as defective or non-defective.
Accelerating wheat breeding for end-use quality with multi-trait genomic predictions incorporating near infrared and nuclear magnetic resonance-derived phenotypes
Ben J. Hayes,Joe Panozzo,C.K. Walker,A. L. Choy,Surya Kant,Debbie Wong,Josquin Tibbits,Hans D. Daetwyler,Simone Rochfort,Matthew J. Hayden,German Spangenberg +10 more
TL;DR: Using NIR and NMR predictions of quality traits overcomes a major barrier for the application of genomic selection to accelerate improvement in grain end-use quality traits of wheat.
A Simple High-Throughput Method for the Analysis of Vicine and Convicine in Faba Bean
TL;DR: A rapid high-throughput LC-MS method for the analysis of v-c in faba beans is developed and fully validated, which uses 10-times less starting material; removes the use of buffers, acids and organic chemicals; and improves precision and accuracy when compared to current methods.
Effects of gamma irradiation on physical and chemical properties of chickpeas (Cicer arietinum)
TL;DR: In this paper, the physical and chemical properties of chickpeas gamma irradiated with 60Co at doses of 0-50kGy were investigated, and the results showed an improvement in cooking quality with increased irradiation.
Molecular basis of barley quality
TL;DR: Genomic techniques allowing more detailed analysis of variations in the barley genome in relation to quality promise to extend significantly the value of molecular genetic approaches to barley quality improvement.