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Spring frosts are usual in many of Spain's fruit-growing areas, so it is common to insure crops against frost damage. After a frost, crop loss must be evaluated, by comparing what crop is left with the amount that would have been obtained under normal conditions. Potential crop must be evaluated quickly through the use of measurements obtainable at the beginning of the tree's growth cycle. During 1996 and 1997 and in 95 commercial plots of `Blanquilla' and `Conference' pear (Pyrus communis L.), the following measurements were obtained: trunk cross-sectional area (TCA, cm²), space allocated per tree (ST, m²), trunk cross-sectional area per hectare (TCA/ha), flower density (FD, number of flower buds/cm² TCA), flower density per land area (FA, number of flower buds/m² land area), cluster set (CS, number of fruit clusters/number of flower clusters, %), crop density (CD, number of fruit/cm² TCA), fruit clusters per trunk cross-sectional area (FCT, number of fruit clusters/cm² TCA), fruit clusters per land area (FCA, number of fruit clusters/m² land area), fruit number per cluster (FNC), average fruit weight (FW, g), average yield per fruit cluster (CY, g), yield efficiency (YE, fruit g·cm^-2 TCA), and tree yield (Y, fruit kg/tree). CS and average CY were related to the rest of the variables through the use of multiple regression models. The models that provided the best fit were CS = TCA/ha - FA and CY = -FA - FCT. These models were significant, consistent, and appropriate for both years. Predicted yield per land area was obtained by multiplying FA × CS × CY. The models' predictive ability was evaluated for 46 different plots in 2001 and 2002. Statistical analysis showed the models to be valid for the forecast of orchards' potential yield efficiency, so that they represent a useful tool for early crop prediction and evaluation of losses due to late frosts.

Spring frosts are usual in many of Spain's fruit-growing areas, so it is common to insure crops against frost damage. After a frost, crop loss must be evaluated, by comparing what crop is left with the amount that would have been obtained under normal conditions. Potential crop must be evaluated quickly through the use of measurements obtainable at the beginning of the tree's growth cycle. During the years 1998 and 1999 and in 62 commercial plots of `Golden Delicious' and `Royal Gala' apple (Malus ×domestica Borkh.), the following measurements were obtained: trunk cross-sectional area (TCA, cm²), space allocated per tree (ST, m²) trunk cross-sectional area per hectare (TCA/ha), flower density (FD, number of flower buds/cm² TCA), flower density per land area (FA, number of flower buds/m² land area), cluster set (CS, number of fruit clusters/number of flower clusters, percent), crop density (CD, number of fruit/cm² TCA), fruit clusters per trunk cross-sectional area (FCT, number of fruit clusters/cm² TCA), fruit clusters per land area (FCA, number of fruit clusters/m² land area), fruit number per cluster (FNC), average fruit weight (FW, g), average yield per fruit cluster (CY, g), yield efficiency (YE, fruit g·cm^-2 TCA), and tree yield (Y, fruit kg/tree). FCT and average CY were related to the rest of the variables through the use of multiple regression models. The models which provided the best fit were FCT = FD - TCA/ha - FD and CY= -FCA - FCT. These models were significant, consistent, and appropriate for both years. Predicted yield per land area was obtained by multiplying TCA/ha × FCT × CY. The models' predictive ability was evaluated for 64 different plots in 2001 and 2002. Statistical analysis showed the models to be valid for the forecast of potential yields in apple, so that they represent a useful tool for early crop prediction and evaluation of losses due to late frosts.

Peach [Prunus persica (L.) Batsch, Peach Group] tree productivity is improved if trees are thinned early, either in full bloom or when the fruit is recently set. Chemical thinning reduces the high cost of manual thinning and distributes the fruit irregularly on the shoots. The effect is similar to a late spring frost that mostly affects early flower buds on the tip of the shoot. To simulate frost damage (or chemical thinning) and evaluate the effect of fruit distribution on production, fruit growth of several peach cultivars—'Catherine', `Baby Gold 6', `Baby Gold 7', `O'Henry', `Sudanell' and `Miraflores'—and the nectarine [Prunus persica (L.) Batsch, Nectarine Group] `Queen Giant' was studied in the central Ebro Valley (Spain) in 1999 and 2000. The factors investigated were the intensity of thinning and fruit distribution on the shoot (concentrated in the basal area or uniformly placed). The treatments were performed at 30 days after full bloom in 1999 and at bloom in 2000. For `Baby Gold 6' and `Miraflores' and when fruit load was high after thinning (over four fruit per shoot), a high concentration of fruit on the basal portion of the shoot had a negative influence on final yield and fruit size. The intensity of thinning (or simulated frost) greatly affected fruit diameter but was also strongly related to cultivar, tree size, and length of shoots. Thus, relationships between thinning intensity and fruit diameter varied, even among trees of the same cultivar.

Spring frosts are usual in many of Spain's fruit-growing areas, so it is common to insure crops against frost damage. After a frost, crop loss must be evaluated, by comparing what crop is left with the amount that would have been obtained under normal conditions. Potential crop must be evaluated quickly through the use of measurements obtainable at the beginning of the tree's growth cycle. During the years 1997 through 1999 and in 86 commercial plots of peach and nectarine [Prunus persica (L.) Batsch], the following measurements were obtained: trunk cross-sectional area (TCA, cm²), trunk cross sectional area per hectare (TCA/ha), estimated total shoot length per trunk cross-sectional area (SLT, shoot m/cm² TCA), crop density (CD, amount of fruit/cm² TCA), fruit weight (FW, g), yield efficiency (YE, kg of fruit/cm² TCA), yield per tree (Y, kg fruit/tree) and days between full bloom and harvest (BHP, days). CD and average FW were related to the rest of the variables through the use of multiple regression models. The models which provided the best fit were CD = SLT - TCA/ha and FW = SLT + BHP - CD. These models were significant, consistent, and appropriate for all three years. The models' predictive ability was evaluated for 32 different plots in 2001 and 2002. Statistical analysis showed the models to be valid for the forecast of orchards' potential yield efficiency, so that they represent a useful tool for early crop prediction and evaluation of losses due to late frosts.

The lowest flower in the pear (Pyrus communis L.) cluster usually develops and blooms first and also has a greater sink potential. For this reason, resources are preferentially utilized by the lowest fruit, and this is also one of the reasons why most thinning practices tend to favor their set. However, it is not always possible to perform selective thinning. This study was undertaken to determine if hindering pollination in the most developed flowers in the cluster influences yield or quality compared to that obtained in a whole open-pollinated cluster. The treatments were made in `Blanquilla' (Spadona, Agua de Aranjuez) and `Conference' pear within a wide range of flower densities for each cultivar. Pollination was hindered by cutting off the flower styles. The factor tested was style removal intensity (SRI). Treatments consisted in removing the styles of two, four(always the most developed), or all flowers in each cluster. Flower density was used as a covariate in an analysis of covariance to account for differences in flower densities in response to SRI treatments. In all experiments the covariate was not significant; therefore, SRI effect was not affected by flower density. `Blanquilla' and `Conference' had similar responses to treatments, so that when at least three flowers are susceptible to be openly pollinated, fruit set, seed content, and cluster yield were similar to control clusters, therefore the growth potential of fruit from partially damaged clusters in their most developed flowers is similar to undamaged open pollinated clusters. The reduced set of parthenocarpic clusters implies yield reductions ranging between 40% and 60% in `Conference', and up to about 60% in `Blanquilla'.

The apical or king (K) flower in the apple (Malus ×domestica L. Borkh.) cluster usually develops and blooms first and also has a greater sink potential. For this reason, resources are primarily used by the K fruit, and this is also one of the reasons why most thinning practices tend to favor K fruit set. However, it is not always possible to retain the K flower and remove the lateral ones. This study was undertaken to determine if the removal of the most developed flowers in the cluster influences yield or quality compared to that obtained in a whole cluster. The treatments were made in `Golden Delicious' and `Royal Gala' apple cultivars, within a wide range of flower densities for each cultivar. The factor tested was the intensity of flower removal (FRI); the treatments consisted in removing one, two, or three flowers in each cluster. Flower density was used as a covariate in an analysis of covariance to account for differences in flower densities in response to FRI treatments. In all experiments the covariate was not significant; therefore FRI effect was not affected by flower density. `Golden Delicious' and `Royal Gala' had similar responses to flower removal, so that when at least three flowers in a cluster remained, fruit set and cluster yield were similar to whole clusters. Only when two or fewer poorly developed flowers remained after FRI treatments, yield was reduced by as much as 25%. Fruit from FRI clusters were even heavier than those from whole clusters, due to reduced competition among the fruit, so that the growth potential of fruit from the first and second lateral flowers was similar to clusters with K fruit, in clusters where the K flower had been removed.

The influence of the species in spring frost sensibility was determined for the Prunus species peach (P. persica (L.) Batsch), sweet cherry (P. avium L.), almond (P. dulcis (Mill.) Webb/P. amygdalus Batsch), japanese plum (P. salicina Lindl.), and blackthorn (P. spinosa L.). The confidence intervals for lethal temperatures of 10% (LT₁₀) and 90% (LT₉₀) bud injury were also determined. In 2000 and 2001, seven frost treatments were made for each one of the phenological stages comprised between B (first swell) and I (jacket split) in two cultivars per each species. The relationships between frost temperature and the proportion of frost damaged buds for each cultivar, year, and phenological stage were adjusted to linear regression models. The 95% confidence intervals were also calculated. The spring frost hardiness order of the species, from the least to most hardy, was as follows: sweet cherry, almond, peach, japanese plum, and blackthorn. Despite the highly homogeneous nature of the frost and bud characteristics, the temperature range for a given injury degree was quite broad, since the confidence interval's breadth for LT₁₀ was as high as about 3 °C and as high as about 6 °C for LT₉₀. Consequently, when critical temperatures are used in making decisions as to when to begin active frost protection, a prudent measure would be to take the temperature references from the upper limits in the confidence intervals.

A collection of 141 old and local Spanish accessions of pear (Pyrus communis) from the Escuela Técnica Superior de Ingeniería Agraria-Universidad de Lleida (ETSIA-UdL) Pear Germplasm Bank in Lleida, Spain, were studied using a set of eight microsatellite markers to estimate the genetic diversity of the collection, to identify the genetic structure and relationships among its accessions, and to establish a representative core collection. An additional set of 13 well-known pear cultivars, currently grown in Spain and which represent a wide genetic diversity, were added as reference. The eight simple sequence repeat (SSR) loci amplified 97 alleles, with nine to 15 alleles per locus, and with the expected heterozygosity ranging from 0.65 to 0.89. All of the accessions except for 16 had at least one of the 48 rare alleles (frequency < 0.05) identified, and seven unique alleles were found in six accessions. Fifteen accessions were identified as synonyms and were excluded from the analysis. Genetic analyses performed by hierarchical clustering, Bayesian model-based clustering, and factorial correspondence analysis supported the existence of three groups among the accessions with moderate [fixation index (F_ST) = 0.074], but significant, differentiation. As a whole, most of the germplasm (about 75%) curated at the collection showed its genetic distinctness with respect to the main pear cultivars used in European orchards. In fact, most reference cultivars were included in one single cluster that, moreover, had the lowest genetic diversity and allelic richness, in spite of having been chosen as heterogeneous material from different origins. The obtained results were also used to create a core collection with 35 accessions constituting an efficient and accessible entry point in the ETSIA-UdL pear collection for breeding and research communities.