The experiments were conducted for three consecutive years across 14 locations using 9 non-waxy proso millet genotypes and 16 locations using 7 waxy proso millet genotypes in China. The objectives of this study were t...The experiments were conducted for three consecutive years across 14 locations using 9 non-waxy proso millet genotypes and 16 locations using 7 waxy proso millet genotypes in China. The objectives of this study were to analyze yield stability and adaptability of proso millets and to evaluate the discrimination and representativeness of locations by analysis of vari- ance (ANOVA) and genotype and genotype by environment interaction (GGE) biplot methods. Grain yields of proso millet genotypes were significantly influenced by environment (E), genotype (G) and their interaction (GxE) (P〈0.1%). GxE inter- action effect was six times higher than G effect in non-waxy group and seven times in waxy group. N04-339 in non-waxy and Neimi 6 (NM6) in waxy showed higher grain yields and stability compared with other genotypes. Also, Neimi 9 (NM9, a non-waxy cultivar) and 90322-2-33 (a waxy cultivar) showed higher adaptability in 7 and in 11 locations, respectively. For non-waxy, Dalat, Inner Mongolia (E2) and Wuzhai, Shanxi (E5) were the best sites among all the locations for maximizing the variance among candidate cultivars, and Yanchi, Ningxia (El0) had the best representativeness. Wuzhai, Shanxi (e9) and Yanchi, Ningxia (e14) were the best representative locations, and Baicheng, Jilin (e2) was better discriminating location than others for waxy genotypes. Based on our results, El0 and e14 have enhanced efficiency and accuracy for non-waxy genotypes and waxy genotypes selection, respectively in national regional test of proso millet varieties.展开更多
In this work, the yield stress evaluation as a function of water content for slip-prone clayey soils is studied in order to understand how yield stress decreases as water content increases, and their relation with the...In this work, the yield stress evaluation as a function of water content for slip-prone clayey soils is studied in order to understand how yield stress decreases as water content increases, and their relation with the chemical properties. The clayey soil samples were taken from the region of Teziutlán-Puebla-Mexico. Yield stress was calculated using the slump test in cylindrical geometry. Results show three zones. The first one shows an exponential decrement on yield stress due to lower water content in accord with clayey soils with high content of illita, followed by a second region where yield stress decreases dramatically at a certain critical water concentration, and the third one where yield stress dependence is not well-defined since the clayey soil flow is seen. Finally, it is discussed how yield stress variation due to the water increment influences the landslide risk increment.展开更多
(Co) variance components and genetic parameters were estimated for milk yield of Iranian Holstein cows. A total number of 68,945 milk test-day records of first, second and third lactations of 8515 animals from 100 sir...(Co) variance components and genetic parameters were estimated for milk yield of Iranian Holstein cows. A total number of 68,945 milk test-day records of first, second and third lactations of 8515 animals from 100 sires and 7743 dams originated from 34 herds collected during 2007 to 2009 by Iranian animal breeding center were used. The ASReml computer program was used to analyze the milk test-day records using the random regression procedure. Herd test date (HTD), milking times per day (milking frequency), number of lactations, year of birth, year of calving, age of animal at calving and days in milk (DIM) considered as fixed effects and additive genetic effects and animal permanent environmental effects were considered as the random effects. Additive genetic variance, animal permanent environment variance, residual variance, phenotypic variance, heritability and repeatability were estimated during different months of lactation between 5.7 - 19.6, 15.3 - 27.1, 31.4 - 17.2, 45.8 - 64.83, 0.1 - 0.32 and 0.4 - 0.6, respectively. Genetic correlation and phenotypic correlation were also estimated between months of lactation in range of -0.35 - 0.98 and 0.03 - 0.67, respectively. Genetic correlation and phenotypic correlation both showed the same changing pattern and they decreased as the interval between months of lactation increased.展开更多
基金funded by the National Key Technologies R&D Program of China during the 12th Five-Year Plan period (2014BAD07B03)the National Natural Science Foundation of China (31371529)+2 种基金the Postdoctoral Science Foundation of Heilongjiang Province, China (LBH-Z14177)the project of Education Department in Heilongjiang Province, China (12541599)the China Agricultural Research System (CARS07-13.5-A9)
文摘The experiments were conducted for three consecutive years across 14 locations using 9 non-waxy proso millet genotypes and 16 locations using 7 waxy proso millet genotypes in China. The objectives of this study were to analyze yield stability and adaptability of proso millets and to evaluate the discrimination and representativeness of locations by analysis of vari- ance (ANOVA) and genotype and genotype by environment interaction (GGE) biplot methods. Grain yields of proso millet genotypes were significantly influenced by environment (E), genotype (G) and their interaction (GxE) (P〈0.1%). GxE inter- action effect was six times higher than G effect in non-waxy group and seven times in waxy group. N04-339 in non-waxy and Neimi 6 (NM6) in waxy showed higher grain yields and stability compared with other genotypes. Also, Neimi 9 (NM9, a non-waxy cultivar) and 90322-2-33 (a waxy cultivar) showed higher adaptability in 7 and in 11 locations, respectively. For non-waxy, Dalat, Inner Mongolia (E2) and Wuzhai, Shanxi (E5) were the best sites among all the locations for maximizing the variance among candidate cultivars, and Yanchi, Ningxia (El0) had the best representativeness. Wuzhai, Shanxi (e9) and Yanchi, Ningxia (e14) were the best representative locations, and Baicheng, Jilin (e2) was better discriminating location than others for waxy genotypes. Based on our results, El0 and e14 have enhanced efficiency and accuracy for non-waxy genotypes and waxy genotypes selection, respectively in national regional test of proso millet varieties.
文摘In this work, the yield stress evaluation as a function of water content for slip-prone clayey soils is studied in order to understand how yield stress decreases as water content increases, and their relation with the chemical properties. The clayey soil samples were taken from the region of Teziutlán-Puebla-Mexico. Yield stress was calculated using the slump test in cylindrical geometry. Results show three zones. The first one shows an exponential decrement on yield stress due to lower water content in accord with clayey soils with high content of illita, followed by a second region where yield stress decreases dramatically at a certain critical water concentration, and the third one where yield stress dependence is not well-defined since the clayey soil flow is seen. Finally, it is discussed how yield stress variation due to the water increment influences the landslide risk increment.
文摘(Co) variance components and genetic parameters were estimated for milk yield of Iranian Holstein cows. A total number of 68,945 milk test-day records of first, second and third lactations of 8515 animals from 100 sires and 7743 dams originated from 34 herds collected during 2007 to 2009 by Iranian animal breeding center were used. The ASReml computer program was used to analyze the milk test-day records using the random regression procedure. Herd test date (HTD), milking times per day (milking frequency), number of lactations, year of birth, year of calving, age of animal at calving and days in milk (DIM) considered as fixed effects and additive genetic effects and animal permanent environmental effects were considered as the random effects. Additive genetic variance, animal permanent environment variance, residual variance, phenotypic variance, heritability and repeatability were estimated during different months of lactation between 5.7 - 19.6, 15.3 - 27.1, 31.4 - 17.2, 45.8 - 64.83, 0.1 - 0.32 and 0.4 - 0.6, respectively. Genetic correlation and phenotypic correlation were also estimated between months of lactation in range of -0.35 - 0.98 and 0.03 - 0.67, respectively. Genetic correlation and phenotypic correlation both showed the same changing pattern and they decreased as the interval between months of lactation increased.