Analysis of multienvironment trials (METs) of crops for cultivar evaluation and recommendation is an important issue in plant breeding research. Evaluating both stability of performance and high yield is essential in MET analyses. The objective of this investigation was to compare 10 nonparametric stability methods and apply nonparametric tests (which do not require distributional assumptions) for genotypeby-environment (G 3 E) interaction to 11 lentil (Lens culinaris Medik) genotypes. Nine improved lentil genotypes and two local cultivars were grown in 20 semiarid environments in Iran from 2002 to 2004. Results of nonparametric tests of G 3 E interaction and a combined ANOVA across environments showed there were both crossover and noncrossover G 3 E interactions and genotypes varied significantly for yield. In this study, high values of TOP (proportion of environments in which a genotype ranked in the top third) and low values of rank-sum (sum of ranks of mean yield and Shukla's stability variance) were associated with high mean yield, but the other nonparametric methods were not positively correlated with mean yield and instead characterized a static concept of stability. The results of principal component (PC) analysis and correlation analysis of nonparametric stability statistics and yield indicated that only ranksum and TOP methods would be useful for simultaneously selecting for high yield and stability. These methods recommended FLIP 92-12L as stable and FLIP96-6L as unstable genotypes. A biplot of the first two PCs also revealed that the nonparametric methods grouped as three distinct classes that corresponded to different agronomic and biological concepts of stability.

SU MMARYGenotype by environment (GrE) interaction effects are of special interest for breeding programmes to identify adaptation targets and test locations. Their assessment by additive main effect and multiplicative interaction (AMMI) model analysis is currently defined for this situation. A combined analysis of two former parametric measures and seven AMMI stability statistics was undertaken to assess GrE interactions and stability analysis to identify stable genotypes of 11 lentil genotypes across 20 environments. GrE interaction introduces inconsistency in the relative rating of genotypes across environments and plays a key role in formulating strategies for crop improvement. The combined analysis of variance for environments (E), genotypes (G) and GrE interaction was highly significant (P<0 . 01), suggesting differential responses of the genotypes and the need for stability analysis. The parametric stability measures of environmental variance showed that genotype ILL 6037 was the most stable genotype, whereas the priority index measure indicated genotype FLIP 82-1L to be the most stable genotype. The first seven principal component (PC) axes (PC1-PC7) were significant (P<0 . 01), but the first two PC axes cumulatively accounted for 71 % of the total GrE interaction. In contrast, the AMMI stability statistics suggested different genotypes to be the most stable. Most of the AMMI stability statistics showed biological stability, but the SIPCF statistics of AMMI model had agronomical concept stability. The AMMI stability value (ASV) identified genotype FLIP 92-12L as a more stable genotype, which also had high mean performance. Such an outcome could be regularly employed in the future to delineate predictive, more rigorous recommendation strategies as well as to help define stability concepts for recommendations for lentil and other crops in the Middle East and other areas of the world.

Selection of lentil (Lens culinaris Medik) cultivars with wide adaptability across diverse farming environments is important, before recommending them to achieve a high rate of cultivar adoption. Seed yield of 11 lentil genotypes, tested in a randomized complete-block design with four replicates across 20 environments in Iran, was analyzed using site regression (SREG) stability model. Th e biplot technique facilitates a visual evaluation of superior genotypes, which is useful for cultivar recommendation and megaenvironment identifi cation. A substantial amount of genotype × environment (GE) interaction for lentil grain yield was detected. Location (L) and genotype × location (GL) variabilities were the predominant components of total yield variation. Th e fi rst two principal components (PC1 and PC2) of the SREG model accounted for 76% of the total GE interaction. Th ere were four winning genotypes and three megaenvironments according to the SREG model. Th e best genotype in one location was not always so in other test locations. According to the ideal-genotype biplot, genotype G5 was better than all other genotypes; G5 exhibited both high mean yield and high stability of performance across environments. According to G + GE sources of variations, the genotypes (G4, G7, G9, and G10) were the most suitable varieties for the lentil-producing regions in Iran.

Interest in growing winter rapeseed (Brassica napus L.) in Iran is increasing due to its potential returns relative to other oilseed crops. Th e objectives of this study were (i) to investigate the interrelationships among diff erent traits of winter rapeseed and (ii) to determine the eff ects of sowing date and variety on the seed yield and other traits of winter rapeseed with application of the biplot methodology in visualizing agronomic research data. Four winter rapeseed varieties were grown on three sowing dates during 2 yr. Th e results showed that variety 1 (SLM046) produced maximum seed yield and oil content in the second (21 September) and the third sowing dates (1 October). Th ousand seed weight was positively and signifi cantly associated with seed yield and the number of pods per plant, but oil content was not correlated with yield or the other traits. Th e study revealed that treatment by trait (TT) biplot can graphically display the interrelationships among traits and facilitate visual comparison of treatments.

Nano-fertilizers are new generation of the synthetic<em> </em>fertilizers which contain readily available nutrients in nano scale range. Nano fertilizers are preferred largely due to their efficiency and environment friendly nature compared to conventional<em> </em>chemical<em> </em>fertilizers. To evaluate the effects of foliar spray<em> </em>of micronutrient nano-fertilizer (iron and zinc) and nano-titanium dioxide (nTiO₂) solution on grain yield and its components in barley under supplemental<em> </em>irrigation conditions, a field experiment was carried out in the semi-arid highland region of Maragheh, Iran. Barley plants were separately treated with of chelated nano-scale zinc oxide (ZnO) and ferric oxide (Fe₂O₃) suspensions during tillering stage, booting and milky stages. Results revealed that days to<em> </em>anthesis and maturity significantly increased after application of both nano-fertilizers. Furthermore<em>,</em> a considerable improvement was observed in grain mass, spike length, number of the grains per spike, chlorophyll content, grain yield and harvest index by application of nano-fertilizer. However the impact of nano zinc fertilizer was more prominent than iron. Foliar application of nTiO₂ positively affected some morphophysiological characteristics like as days to<em> </em>anthesis, chlorophyll content and straw yield. The results suggest that the delivery of Zn into barley seedling through spray of nano-fertilizer can be an efficient nutrient management strategy in semi-arid regions. Overall, our result indicated that the integration of nanotechnology in fertilizer products can improve fertilizer use efficiency and significantly increase of barley yield. However, plant response to nanoparticles significantly depend on concentration and time of application as well as size, shape, and surface functionalization of the particles.

Silicon nanoparticles have distinctive physicochemical characteristics and are able to enter into plants and impact the metabolism of plants as well as improve plant growth and yield under unfavourable environmental conditions. Besides, low soil organic matter content, imbalanced nutrient and inadequate water supply may adversely affect crop productivity in semiarid areas. To understand the effects of foliar spray of silicon dioxide nanoparticles (nSiO2) with application of farmyard manure (FYM) or inorganic fertilizer on morpho-physiological traits and yield of safflower, a field experiment was carried out in a highland semiarid region of Maragheh, northwest Iran. The experiment consisted of two levels of nSiO2(0 and 20 mM) and four fertilizer regimes (control, 15 t ha−1FYM, 30 t ha−1FYM, 90 kg ha−1N-P-K chemical fertilizer). Safflower plants were treated with nSiO2suspension at leaf development, branching and capitulum emergence stages. Although the nSiO2significantly improved some growth parameters such as canopy spread, stem diameter, plant height, ground cover and the number of achenes in capitulum, it did not affect achene yield and harvest index. However, fertilizer treatments considerably affected most of morpho-physiological traits, achene yield and yield components. The result showed that the best growth and the highest achene yield were achieved by application of 30 t ha−1FYM before sowing. Application of high FYM increased the achene yield by 48% compared to the control, however, application of N-P-K chemical fertilizer or of 15 t ha−1FYM improved achene yield only up to 17% over the no fertilizer condition. Moreover, this work revealed some positive effects of exogenous application of nSiO2on safflower growth. This finding suggests that application of organic fertilizers with foliar spray of nSiO2can improve safflower production and is an advisable agronomic option.

Development of new canola (Brassica napus L.) cultivars requires efficient tools to monitor trait association in a breeding program. The efficiency of a breeding program depends mainly on the direction of the correlation between yield and its components and the relative importance of each component involved in contributing to seed yield. This research uses sequential path analysis to determine the interrelationships among seed yield and 20 related traits. Forty nine canola genotypes were grown in two environments (non-stressed and water-stressed conditions) to determine the important components of seed yield. Observations were recorded on 20 other canola traits. Correlation coefficient analysis revealed seed yield was positively correlated with all the traits except stem diameter and days to flowering in the non-stressed environment. Seed yield was significantly positively correlated with all measured traits except first pod height, first lateral branch height, number of lateral branches pod -1 , number of pods plant -1 and stem diameter in the water-stressed environment. Sequential path analysis identified the 1,000-seed weight (TSW) and main stem length as important first order traits that influenced seed yield in the non-stressed environment. Plant height and the TSW were important first order traits that influenced seed yield in the water-stressed environment. All direct effects were significant, as indicated by bootstrap analysis. The results suggest that TSW could be used as a selection criterion in selecting for increased seed yield in canola in both non-stressed and water-stressed conditions. Additional key words: bootstrap analysis, conventional path analysis, drought tolerance. Resumen Interrelación entre el rendimiento de las semillas y veinte caracteres asociados de 49 cultivares de colza (Brassica napus L.) en entornos sin estrés y con estrés hídricoEn los programas de mejora, el desarrollo de nuevos cultivares de colza (Brassica napus L.) requiere herramientas eficaces para analizar la correlación entre el rendimiento de las semillas y sus componentes genéticos. La presente investigación utiliza un análisis secuencial para determinar las interrelaciones entre el rendimiento de las semillas y 20 caracteres relacionados. Se cultivaron 49 genotipos de colza en dos ambientes (sin estrés y con estrés hídrico) para determinar los componentes más importantes del rendimiento de las semillas y se realizaron observaciones sobre otros 20 caracteres. El análisis del coeficiente de correlación reveló que el rendimiento de las semillas está positivamente correlacionado con todos estos caracteres, excepto con el diámetro del tallo y días hasta la floración en condiciones sin estrés, y con la altura de la primera vaina, altura de la primera rama lateral, número de ramas laterales por vaina, número de vainas por planta y diámetro del tallo, en condiciones de estrés hídrico. Del análisis secuencial se dedujo que el peso de 1.000 semillas (TSW) y la longitud de tallo principal son los caracteres que más influ...

Lentil (Lens culinaris Medik.) is traditionally grown as a rain fed crop, particularly in the Middle East; its seed is a rich source of protein for human consumption in developing countries such as Iran and others. The stability of 11 different lentil genotypes was investigated using 19 univariate stability parameters. Field experiments were conducted in 20 rain-fed environments in Iran's lentil producing areas to characterize genotype by environment (GE) interactions on seed yield of 11 lentil genotypes. Combined analysis of variance across environments indicated that both environment and GE interactions significantly influenced genotype yield. Several statistical methods and techniques were used to describe the GE interaction and to define stable genotypes in relation to their yield. The results of these different stability methods were variable. However, most showed genotype FLIP 92-12L was stable and genotype Gachsaran was unstable. Genotypes identified as superior differed significantly from local cultivars and can be recommended for use by farmers in semi-arid areas of Iran. Principal component analysis was used to obtain an understanding of relationships among stability techniques. It showed the parameters studied could be grouped in five distinct classes. Clustering of the genotypes indicated that there were two genotypic groups in this group of genotypes.Additional key words: adaptation, multi-environmental trials, regression analysis, variance component. ResumenInteracción genotipo × × ambiente de la producción de grano de genotipos de lenteja y su relación con técnicas estadísticas de estabilidad univariadas La lenteja (Lens culinaris Medik.) se cultiva tradicionalmente en regadío, particularmente en el Oriente Medio, y su semilla es una fuente rica de proteínas para consumo humano en países en desarrollo como Irán y otros muchos. Se investigó la estabilidad de 11 diferentes genotipos de lenteja utilizando 19 parámetros univariados. Para caracterizar la interacción genotipo × ambiente (GE) de la producción de grano de 11 genotipos de lenteja, se realizaron experimentos de campo en 20 ambientes de regadío de las áreas productoras de Irán. Análisis combinados de varianza entre ambientes indicaron que tanto los ambientes como las interacciones GE influyeron significativamente en la producción de los genotipos. Se utilizaron varios métodos estadísticos para describir la interacción GE y definir los genotipos estables respecto a la producción. Los resultados de los diferentes métodos fueron variables, pero la mayoría mostraron que el genotipo FLIP 92-12L es estable y que Gachsaran es inestable. Los genotipos calificados como superiores difirieron significativamente de los cultivares locales y pueden ser recomendados para ser utilizados por los agricultores de las zonas semi-áridas de Irán. Se utilizó un análisis de componentes principales para analizar las relaciones entre las técnicas de estabilidad. El análisis mostró que los parámetros estudiados pueden ser agrupados en cinco clases, y los genot...