Autochthonous genotypes of fruit species are very important source of genetic
variability and valuable material for breeding work. Fruit Research
Institute-Cacak has a long tradition of studying autochthonous genotypes of
temperate fruits sporadically spread and preserved in some localities in
Serbia. Over 2005-2006, the following properties of nine autochthonous sour
cherry genotypes grown in Feketic region were investigated: flowering and
ripening time, pomological properties, biochemical composition of fruits and
field resistance to causal agents of cherry diseases - cherry leaf spot
(Blumeriella jaapii (Rehm.) v. Arx.), shot-hole (Clasterosporium carpophilum
(L?v.) Aderh.) and brown rot (Monilinia laxa /Ader et Ruhl./ Honey ex
Whetz.). The genotypes were tested for the presence of Prune dwarf virus and
Prunus necrotic ring spot virus. In majority of genotypes fruits were large,
with exceptional organoleptical properties, whereas ripening time was in the
first ten or twenty days of June. The highest fruit weight was observed in
F-1 genotype (8.1 g). The highest soluble solids and total sugars content
were found in F- 4 genotype (17.60% and 14.25%, respectively). As for field
resistance to causal agents of diseases and good pomo-technological
properties, F-1, F-2, F-3, F-7 and F-8 genotypes were singled out. [Projekat
Ministarstva nauke Republike Srbije, br. TR31064]
Professional and scientific networks built around the production of sweet cherry (Prunus avium L.) led to the collection of phenology data for a wide range of cultivars grown in experimental sites characterized by highly contrasted climatic conditions. We present a dataset of flowering and maturity dates, recorded each year for one tree when available, or the average of several trees for each cultivar, over a period of 37 years (1978–2015). Such a dataset is extremely valuable for characterizing the phenological response to climate change, and the plasticity of the different cultivars’ behaviour under different environmental conditions. In addition, this dataset will support the development of predictive models for sweet cherry phenology exploitable at the continental scale, and will help anticipate breeding strategies in order to maintain and improve sweet cherry production in Europe.
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