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Thirty-two lactating Karagouniko ewes were allocated at random to four groups for 6 weeks, to examine the effect of four diets: C (control treatment, ration without algae); LA (ration with low level of algae); MA (ration with medium level of algae) and HA (ration with high level of algae); containing 0, 23·5, 47 and 94 g algae, respectively, on the enrichment of milk and dairy products. Addition of algae reduced (P<0·001) DM intake for treatments MA and HA. Milk yield did not differ between treatments but milk composition was significantly affected by dietary inclusion of algae. Milk fat content was significantly increased (P<0·001) for treatment HA whereas milk protein content was significantly increased (P<0·001) for all treatments containing algae. Milk from treatments LA, MA and HA was significantly enriched in the following PUFA: C20[ratio ]5 (n-3) (0·4–2·1%), C22[ratio ]5 (n-6) (0·8–4·1%), C22[ratio ]6 (n-3) (4·3–12·4%) (P<0·001) and C22[ratio ]5 (n-3) (2·1–3·1%) (P<0·05), which were not detected in control milk. Feta cheese and yogurts produced from the enriched milk had identical composition with the milk, and would be characterized as healthy foods. The ratio of n-6 to n-3 fatty acids was 2·5–4·5.

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An important task of multienvironment trials (MET) analysis is evaluation of testing sites for megaenvironment diff erentiation and selection of "ideal" candidate location to improve the effi ciency of cultivar selection and recommendation. Th e objectives of this research work were (i) to divide the Spanish cotton (Gossypium hirsutum L.) testing locations into megaenvironments and (ii) to separate the testing locations based on their distance to the "ideal" location, discriminating ability, representativeness, and uniqueness. GGE biplot was employed to analyze eight 1-yr and two multiyear (3-yr, 4-yr) balanced datasets from 1999 to 2006 cotton trials of Delta & Pine Land Co. in Spain for yield, fi ber quality traits, a selection index (SI) based on yield and quality, and Verticillium wilt (Verticillium dahliae Kleb.) disease infestation level. Yearly GGE biplots revealed crossover genotype × location interactions, but not large enough to divide the area into diff erent megaenvironments. Th erefore, the Spanish cotton region may be considered as a complex megaenvironment and cultivar recommendation may be based on both mean performance and stability. Las Cabezas location was the closest to an ideal based on both yield and the SI regardless of the change from plastic to nonplastic mulching cultural practice. Aznalcazar did not provide unique information and could be dropped as a test site. Th e separation of test locations for their discriminating ability and representativeness provided useful information on the eff ectiveness of each testing location for developing and/or recommending cultivars with specifi c or broad adaptation. In this sense, Lebrija could be considered as trait-specifi c selection environment for early screening of verticillium tolerant genotypes.Abbreviations: AMMI, additive main eff ects and multiplicative interaction; GEI, genotype × environment interaction; GGE, genotype main eff ect plus genotype × environment interaction; MET, multienvironment trials; PC, principal component; SI, selection index.

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Multi-environment trial data are required, to obtain variety stability performance parameters as selection tools for effective cultivar evaluation. The interrelationship among seven stability parameters and their association with mean yield, along with the repeatability of these parameters across consecutive years was the objective of this study. Cottonseed yield data of 31 cotton cultivars, proprietary of Delta and Pine Land Co and other companies, evaluated in 20 locations over the [1999][2000][2001][2002][2003][2004][2005] year period in Greece, Spain and Turkey were used for combined analysis of variance in four datasets. Across locations in a single evaluation year (dataset A), across locations in each of two single consecutive evaluation year (dataset B), across locations and two consecutive years (dataset C) and across locations and three consecutive years (dataset D). For each dataset, cultivar phenotypic variance ðr 2 p Þ was appropriately partitioned in its components and the h 2 and r 2 ge component estimated. Furthermore, following the appropriate stability analysis b i ; sd 2 i , r 2 i ; YS i and AMMI1 along with the GGE Biplot distance (GGED) and instability (GGEIN) parameters were obtained. The interrelationship among the parameters and their association with mean yield based on Spearman rank correlation was studied in each of the seven single evaluation years (dataset A). Rank correlation coefficients were also used as estimates of the repeatability of these stability parameters across consecutive year combinations (dataset B, C and D). The parameters GGED and YS i were consistently highly correlated with each other and mean yield in five out of seven single evaluation years. The data provided evidence that single year evaluation across locations might be sufficient to reliably rank cotton cultivars, based on mean yield along with GGED and YS i . Combined analysis across two consecutive years (dataset C) was more effective as compared to single year evaluation. GGED was relatively more repeatable than YS i and mean yield in single (dataset B) and 2-year comparisons (dataset C). Although GGED is an index depended and proportional to yield, provides a superior way to integrate mean performance and stability into a single measure, which can be assessed visually on biplots. Regarding the other stability parameters, the results were contradicting and of low repeatability across single years and two

The genetic diversity among the main local landraces and commercial cultivars of P. vulgaris L. cultivated in Greece, was estimated by studying the morphological, agronomical and physicochemical traits along with molecular data analysis using random amplified polymorphic DNA (RAPD markers). Cluster analysis was conducted on similarity estimates using the UPGMA algorithm. Application of cluster analysis resulted in a dendrogram representing the genetic relationship among landraces and main bean cultivars grown in Greece. A wide genetic variation was observed among collected local bean landraces in morphological characteristics such as seed color, seed size and growth habit. According to agronomic performance, significant differences were found in number and weight of pods per plant. Variation in protein and fat content among landraces and commercial cultivars was also detected. Moreover, in some landraces like Kastoria and Byzitsa M/M extremely high values for protein content (28.6% and 27.0% respectively) were recorded. Such values were greater than the average protein content previously recorded for other cultivars of this species. Genetic similarity estimated from molecular analysis with RAPDs, seemed not to be related with the seed morphological characteristics and agronomic performance. Only qualitative parameters like growth habit and occasionally geographical origin of landraces were positively correlated with the molecular classification. Local bean landraces were classified in three subgroups whereas the commercial cultivars formed another separate group underlining the narrow genetic base of cultivars.