The changing climate is altering timing of key fruit ripening processes and increasing the occurrence of fruit defects. To improve our understanding of the genetic control of raspberry fruit development an enhanced genetic linkage map was developed and used to examine ripening phenotypic data. In this study we developed an enhanced genetic linkage map for the raspberry cvs. Glen Moy x Latham reference mapping population using genotyping by sequencing (GbS). Alignment to a newly sequenced draft reference genome of red raspberry, cultivar (cv.) Glen Moy, identified 8019 single nucleotide polymorphisms (SNPs). After stringent filtering to take account of read coverage over all the progeny individuals, association with a single chromosome, heterozygosity and marker regression mapping, 2348 high confidence SNPs were retained and integrated with an existing raspberry genetic map. The linkage map contained many more SNPs segregating in Latham than in Glen Moy. This caused difficulties in quantitative trait loci (QTL) mapping with standard software and a novel analysis based on a hidden Markov model was used to improve the mapping. QTL mapping using the newly generated dense genetic map not only corroborated previously identified genetic locations but also provided additional genetic elements controlling fruit ripening in raspberry. The high-density GbS map located the QTL peaks more precisely than in earlier studies, aligned the QTLs with Glen Moy genome scaffolds, narrowed the range of potential candidate genes to these regions that can be utilised in other populations or in gene expression studies to confirm their role and increased the repertoire of markers available to understand the genetic control of fruit ripening traits.

Hyperspectral imaging is a technology that can be used to monitor plant responses to stress. Hyperspectral images have a full spectrum for each pixel in the image, 400–2500 nm in this case, giving detailed information about the spectral reflectance of the plant. Although this technology has been used in laboratory-based controlled lighting conditions for early detection of plant disease, the transfer of such technology to imaging plants in field conditions presents a number of challenges. These include problems caused by varying light levels and difficulties of separating the target plant from its background. Here we present an automated method that has been developed to segment raspberry plants from the background using a selected spectral ratio combined with edge detection. Graph theory was used to minimise a cost function to detect the continuous boundary between uninteresting plants and the area of interest. The method includes automatic detection of a known reflectance tile which was kept constantly within the field of view for all image scans. A method to split images containing rows of multiple raspberry plants into individual plants was also developed. Validation was carried out by comparison of plant height and density measurements with manually scored values. A reasonable correlation was found between these manual scores and measurements taken from the images (r2 = 0.75 for plant height). These preliminary steps are an essential requirement before detailed spectral analysis of the plants can be achieved.

The genetic disorder known as ‘crumbly’ fruit is becoming a serious problem in the European raspberry industry. The study set out to examine the crumbly phenotype in a red raspberry mapping population under two environments (field and polytunnel) across six seasons in an effort to understand variability of the syndrome and to examine whether genetic factors were important and if so, whether QTL associated with the phenotype could be identified. This highlighted that seasonal, environmental (field or polytunnel) and genetic factors all influence the condition. Two QTL that are important for the genetic control of the condition have been located on linkage groups one and three, and an association with ripening time has been identified.

Red raspberry, commercially the most important of the Rubus species, has proven extremely recalcitrant in tissue culture. This has led to problems in the micropropagation of new and existing varieties for release to industry, and has greatly hampered the application of technologies such as genetic modification to raspberry improvement. The activity of N- (2-chloro-4-pyridyl)-N-phenylurea (CPPU), a synthetic compound with cytokinin-like activity, was investigated for use in improving the micropropagation of whole shoots and on its ability to induce organogenesis in raspberry. Significantly improved micropropagation rates and whole-plant regeneration through organogenesis were achieved by the use of medium containing low concentrations of CPPU for recalcitrant red raspberry cultivars, typical of the available germplasm. The effect of CPPU on a blackberry and a red raspberry 2 blackberry hybrid, both of which can efficiently be induced to undergo micropropagation and organogenesis was also examined, although the results were less successful than those achieved in previous work. A pilot transformation experiment was set up to ensure that the ability of CPPU to induce organogenesis was not eliminated when combined with Agrobacterium infection and with antibiotics in the regeneration/selection medium.