Development of fruit growing and fruit science in Latvia has always been closely linked to the development of the whole country. After the founding of the independent Latvia state in 1918, fruit growing developed rapidly. Although in the Soviet times the situation was not favourable for quality fruit growing, research and breeding continued with good results. After Latvia regained independence, private land property rights were restored, and interest in intensive orchard establishment and growing technologies increased rapidly, which demanded change in the research focus. At present, the Latvia State Institute of Fruit-Growing is the leading institution in this field, working in cooperation with Pūre Horticultural Research Centre, Latvian Plant Protection Research Centre, Institute of Agrobiotechology, and Faculty of Food Technology, Latvia University of Agriculture, Laboratory of Plant Mineral Nutrition, Institute of Biology, University of Latvia. Research is carried out in the following directions: breeding and cultivar evaluation; genetics and molecular biology; plant pathology and entomology; orchard management; experimental processing and storage.

With long-term changes in temperature and weather patterns, ecologically adaptable fruit varieties are becoming increasingly important in agriculture. For selection of candidate cultivars in fruit breeding or for yield predictions, fruit set characteristics at different growth stages need to be described and evaluated, which is largely done visually. This is a time-consuming and labor-intensive process that also requires sufficient expert knowledge. The annotated dataset for Japanese quince - QuinceSet - consists of images of Japanese quince (Chaenomeles japonica) fruits taken at two phenological developmental stages and annotated for detection and phenotyping. First, after flowering, when the second fruit fall is over and the fruits have reached 30-50% of their final size, and second, at the ripening stage of quince, just before the fruits are yielded. Both stages of quince images classified as unripe and ripe were annotated using ground truth ROI and presented in YOLO format. The dataset contains 1515 high-resolution RGB .jpg images with the same number of annotated .txt files. Images in the dataset were manually annotated using LabelImg software. A total of 17,171 annotations were provided by the experts. The images were acquired on site at the Institute of Horticulture in Dobele, Latvia. Homogenization of the images was performed under different weather conditions, at different times of the day, and from different capturing angles. The dataset contains both fully visible quinces and quinces partially obscured by leaves. Care was also taken to ensure that the foreground, which contains the leaves has adequate brightness with minimal shadows, while the background is darker. The presented dataset will allow to increase the efficiency of the breeding process and yield estimation, to identify and phenotype quinces more reliably, and may also be useful for breeding other crops.

The production of Ribes (Rosaceae) in temperate regions in Europe, Asia and New Zealand is severely constrained by damages of Cecidophyopsis mites (Acari: Eriophyidae) and blackcurrant reversion virus (BRV) (Nepovirus, Secoviridae). The infestation of Ribes plants with Cecidophyopsis mites and BRV infection is a complex tripartite system. This paper reviews scientific progress and knowledge gaps on the Cecidophyopsis‐BRV‐Ribes complex emphasising Cecidophyopsis mites as a pest and natural vector of BRV, BRV as a pathogen, and Ribes as a host plant with horticultural significance. Cecidophyopsis species occurring on Ribes, their host range, geographic distribution and the role in BRV transmission is reviewed. Blackcurrant reversion disease symptoms and BRV hosts are analysed. Resistance of Ribes to Cecidophyopsis and BRV, and resistance breeding aspects are discussed. Discrepancies in research data, controversies and problems are highlighted, and further research is suggested to clarify some of the controversial aspects.

ISHS XXVIII International Horticultural Congress on Science and Horticulture for People (IHC2010): International Symposium on Berries: From Genomics to Sustainable Production, Quality and Health A MULTINATIONAL APPROACH FOR CONSERVING THE EUROPEAN GENETIC RESOURCES OF CURRANTS AND GOOSEBERRY

The RaspberrySet dataset is a valuable resource for those working in the field of agriculture, particularly in the selection and breeding of ecologically adaptable berry cultivars. This is because long-term changes in temperature and weather patterns have made it increasingly important for crops to be able to adapt to their environment. To assess the suitability of different cultivars or to make yield predictions, it is necessary to describe and evaluate berries’ characteristics at various growth stages. This process is typically carried out visually, but it can be time-consuming and labor-intensive, requiring significant expert knowledge. The RaspberrySet dataset was created to assist with this process, and it includes images of raspberry berries at five different stages of development. These stages are flower buds, flowers, unripe berries, and ripe berries. All these stages of raspberry images classified buds, damaged buds, flowers, unripe berries, and ripe berries and were annotated using ground truth ROI and presented in YOLO format. The dataset includes 2039 high-resolution RGB images, with a total of 46,659 annotations provided by experts using Label Studio software (1.7.1). The images were taken in various weather conditions, at different times of the day, and from different angles, and they include fully visible buds, flowers, berries, and partially obscured buds. This dataset is intended to improve the efficiency of berry breeding and yield estimation and to identify the raspberry phenotype more accurately. It may also be useful for breeding other fruit crops, as it allows for the reliable detection and phenotyping of yield components at different stages of development. By providing a homogenized dataset of images taken on-site at the Institute of Horticulture in Dobele, Latvia, the RaspberrySet dataset offers a valuable resource for those working in horticulture.