Genotype × Environment Interaction in the Andean Grain Crop Quinoa (Chenopodium quinoa) in Temperate Environments

Ten varieties of quinoa with origins ranging from latitude 39° S to 12° S and from sea level to an altitude of 3,800 m were grown on two soil types in two years in Cambridgeshire, England, in order to assess the extent and nature of genotype × environment (G × E) interactions and identify genotypes suited for cultivation at temperate latitudes. There was evidence that varieties differed in their susceptibility to water logging during germination. Plant height was strongly influenced by competition with weeds, and varieties differed in their susceptibility to this. The number of days to anthesis and to maturity were strongly dependent on the variety, but these periods were generally longer following an earlier sowing. The grain yield was also strongly dependent on the variety, but weed competition, a micronutrient deficiency and bird damage affected the varieties differently. Varieties originating at high latitudes gave the highest yields, about 5,000 kg/ha. Earliness and yield were strongly associated at the level of variety means, but the pattern of G × E interaction differed among the variables measured.     

高粱主要品质性状的基因型与环境及互作效应分析

摘要： 选取10个高梁品种分别播种于山西榆次、辽宁沈阳、甘肃平凉、贵州贵阳和湖南长沙5个地区,淀粉、蛋白质、单宁和脂肪4项品质分析结果表明,不同品种、不同地点间4个品质性状均表现出较大的不同。不同区域试验结果表明,在各试点籽粒淀粉含量变异系数均为最小,平均值为2.59%,单宁最大,变异系数平均值为21.57%,蛋白质和脂肪的变异系数分别为11.13%和18.63%,远远高于淀粉和低于单宁,说明不同品种淀粉含量变化相对较小, 而单宁含量则有很大的变异,有较大的选择余地和改进潜力。分析影响品质性状的主次因素,结果表明,淀粉含量以基因型×环境效应为主,基因效应也较大。单宁含量以基因效应为主要因素,蛋白质含量以基因型×环境互作效应为主, 脂肪含量的环境、基因型、基因型×环境效应三者所占总平方和的百分比比较接近,几乎是基因型、环境和交互作用平均作用的结果。在今后品种的引进和选育方面应考虑这些性状的基因型、环境和互作效应,以提高品种的选育效果和生产水平。     

Inheritance of Resistance to Striga in Sorghum Genotype SRN39

Striga hermonthica (Del.) Benth., a parasitic weed of grasses, causes major yield reductions in the principal cereal crops of semi-arid Africa. Cultivar resistance is the most economic control measure, since adapted, resistant cultivars can be grown without additional input from the subsistence farmer. Information on the genetics of resistance to S. hermonthica is scant. This is partially attributable to the rarity of germplasms which exhibit stable resistance across geographical regions. The objective of this study was to determine if the stable resistance observed in sorghum [Sorghum bicolor (L.) Moench] cultivar SRN39 is heritable. Crosses were made between SRN39 and a susceptible parent, P954063. Parental, F₁, F₂ and backcross generations were grown in infested pots and development of both host and parasite was monitored. Significant variation among genotypes was observed for both host traits and effects on parasite populations. The F₁ did not differ significantly in Striga resistance from the susceptible parent, suggesting recessive inheritance. However, hybrid vigor was exhibited by the F₁ which yielded and developed as well as the resistant parent. Broad sense heritability ranged from 0.23 to 0.55 for host traits and from 0.10 to 0.43 for effect of genotypes on the Striga population. Joint scaling tests showed that observed variation in each host or parasite trait consisted of additive and dominance components, suggesting possible progress could be made with appropriate selection schemes.     

Genotype × Environment Interaction for Nitrate Concentration in Lettuce

High nitrate concentration is a problem when lettuce (Lactuca sativa L.) is grown under low light intensities. Genotypes with low nitrate concentrations have been identified and are being used in breeding programmes. Previous results indicated the occurrence of genotype × environment (GE) interactions. Because of the important influence of light intensity on nitrate accumulation, two types of interactions may be expected: interactions related to daily variation, and those related to annual variation. In the present investigation both types were investigated using eight butterhead genotypes of lettuce which were repeatedly harvested. No daily variation in nitrate concentration and no corresponding GE-interactions were found, irrespective of the level of global radiation. In contrast, a large annual variation and important corresponding GE-interactions were found. Joint regression analysis on environmental means and on physical factors related to light intensity showed a differential response of genotypes to changing environmental conditions. Multiple joint regression on daylength and change in daylength accounted for two-thirds of the interaction variance. However, deviations from regression were still significant indicating non-linearity of the relationship, or, the existence of other environmental factors contributing to GE-interaction.     

Interaction of Salinity and Temperature on the Germination of Sorghum

Laboratory studies were conducted to investigate the effect of salinity × temperature interactions on the germination of sorghum. Sorghum bicolor (L.) Moench. Sorghum seeds were sown in petri dishes with saline solutions of varying concentrations (electrical conductivities of 0.01, 6.4, 12.2, 17.4, 22.6, 27.2, 32.1, and 37.2 dSm^-1) prepared with NaCl. The germination responses of the seeds were determined over a wide range of temperatures (15, 20, 25, 30, 35 and 40 °C) for a period of 8 days. Salinity × temperature interactions were highly significant at each counting date. Although, increased salinity resulted in decreased germination percentages, the detrimental effect of salinity was generally less severe at higher temperatures. Germination rate index, computed from germination counts taken every 2 days, was influenced by salinity and temperature in a similar pattern as final germination. Seed germination was more tolerant to salinity at germination temperatures of 30–40 °C than at 15–25 °C.     

Effects of Genotype and Environment on the Main Components in Cottonseed of Upland Cotton

[Objective] The aim of this study is to investigate the effect of cotton genotypes, growth environment, and their interaction on major components in cottonseeds. [Method] Eleven upland cotton cultivars were planted in 10 different locations in the middle and lower reaches of Yangtze River region as research materials. Cottonseeds were collected to determine the contents of six main components including protein content (PC), oil content (OC), gossypol, phytic acid (PA), α-tocopherol and γ-tocopherol, then the genotypes, environment, and their interaction effects were analyzed accordingly. [Result] The results showed that the genotypes, environment, and their interaction had extremely significant effect on the protein and oil content in cottonseeds. The environment had extremely significant effect on the gossypol and phytic acid content in cottonseed. The genotypes had extremely significant effect on the gossypol content and had significant effect on the phytic acid content in cottonseed, but their interaction was insignificant. The genotype effects of α-tocopherol and γ-tocopherol were not significant, but the environmental effects were significant. The differences of tocopherols between different regions reached the extremely significant level. In addition, protein content and oil content were significantly negatively correlated and the sum of the protein and oil contents remained stably at 75%. [Conclusion] In cotton seed quality breeding, not only the differences in varieties, but also the environment and the interaction between varieties and environment should be considered. The expression of the main components of cottonseed is the result of a combination of genotype and ecological environment.     

浙江省早籼稻蒸煮品质的品种、地点、品种×地点互作效应研究

以浙江省1995年早籼稻品种区域试验6个试点参试品种蒸煮品质测定结果为材料,用多元分析法探讨了糊化温度、胶稠度、直链淀粉含量3个蒸煮品质的品种（基因型）效应、地点效应、品种×地点互作和蒸煮品质间的相关关系,剖析了各效应的相对重要性。分析结果表明,蒸煮品质的3个性状均以品种效应为主,而且依次以直链淀粉含量的品种间变异最大,胶稠度次之,糊化温度最小;环境对糊化温度有较大影响。相关分析显示,蒸煮品质间有相关关系,且完全来自遗传（品种）效应。     

GGE叠图法—分析品种×环境互作模式的理想方法

本文介绍一种分析作物区域试验结果的方法—GGE叠图法。首先,将原始产量数据减去各地点的平均产量,由此形成的数据集只含品种主效应G和品种-环境互作效应GE,合称为GGE。对GGE作单值分解,并以第一和第二主成分近似之。按照第一和第二主成分值将各品种和各地点放到一个平面图上即形成GGE叠图。借助于辅助线,可以直观回答以     

高粱光敏色素A基因的克隆、蛋白结构与长短日照诱导表达模式

光敏色素是一类红光/远红光受体,对植物光形态建成、外部形态和生理功能等方面起着重要的调节作用。为明晰光敏色素A在调控高粱光形态建成发育过程中的作用,本研究比较分析光温敏感程度不同的高粱品种Btx623、Rio、Tx430和LH645的PhyA基因序列和PHYA蛋白的保守结构域,利用qRT-PCR明确长短日照条件处理下PhyA基因的表达模式。结果表明,Btx623、Rio和Tx430之间PhyA基因序列存在非同义突变,LH645在PhyA基因的第7个外显子上插入了5 bp碱基序列;高粱PhyA蛋白中含有1个PAS-2结构域、1个GAF结构域、1个Phytochrome结构域、2个PAS结构域、1个组氨酸激酶A结构域和1个类似组氨酸激酶的ATP激酶结构;遗传进化树分析表明,单子叶和双子叶植物PhyA蛋白明显聚为2大类,高粱PhyA、谷子PhyA和玉米PhyA1、PhyA2聚为一个亚类,相互间亲缘关系较近,与水稻PhyA同源性相对较远;在短日照(SD)条件下各时期PhyA基因转录水平变化显著,Rio PhyA基因转录水平较Btx623和Tx430变化明显,LH645 PhyA基因转录变化不显著,在长日照(LD)条件下Rio PhyA基因转录水平低于Btx623和Tx430,LH645 PhyA基因转录水平变化不显著。以上结果表明,PhyA受光周期诱导,推测其在高粱光形态建成中起重要调控作用。本研究为进一步解析PhyA基因功能及其在调控高粱光形态建成发育过程中的作用提供理论基础。     

GGE叠图法─分析品种×环境互作模式的理想方法

本文介绍一种分析作物区域试验结果的方法－ＧＧＥ叠图法。首先，将原始产量数据减去各地 点的平均产量，由此形成的数据集只含品种主效应Ｇ和品种－环境互作效应ＧＥ，合称为ＧＧＥ。对ＧＧＥ 作单值分解，并以第一和第二主成分近似之。按照第一和第二主成分值将各品种和各地点放到一个平 面图上即形成ＧＧＥ叠图。借助于辅助线，可以直观回答以下问题：（１）什么是某一特定环境下最好的 品种；（２）什么是某一特定品种最适合的环境；（３）任意两品种在各环境下的表现如何；（４）试验中品 种×环境互作的总体模式是怎样的；（５）什么是高产、稳产品种；（６）什么是有利于筛选高产、稳产品 种的环境。     

Genotype × Environment Interacion in multi-environment Trials using shrinkage factors for ammi models

Shrinkage factors applied to the additive main effects and multiplicative interaction (AMMI) models improve prediction of cultivar responses in multi-environment trials (MET). Estimates of shrinkage factors based on the eigenvalue partition (EVP) method may get a further improvement in the predictions of cell means. Objectives of this work were: (1) to compare the EVP-based shrinkage method with unshrunken AMMI, best linear unbiased predictor (BLUP) and other shrunken method (herein named CCC), when they were applied to five maize MET and simulation data; (2) to assess by cross validation the equation which estimates the standard error of predicted means (SEPM) based on the EVP theory; (3) to estimate the genotype × environment interaction (GEI) variance components after applying the EVP shrinkage method to the five maize MET. Empirical data of five maize MET and simulation data were used for cross validation of the methods using the root mean square predictive difference (RMSPD) criterion. The RMSPD of the shrunken EVP predicted cell means was generally smaller than those of the other methods, suggesting that the EVP method was generally better predictor than the other methods. The truncated AMMI was the worst among the four methods studied. The EVP-based equation, which predicts the SEPM, was a good predictor as determined by the RMSPD cross validation criterion, with the advantage that it does not need one replication for validation. Estimates of mean squares, and GEI and error variances associated with the GEI effects were smaller for the shrunken EVP predicted effects than for the original data. This revised version was published online in July 2006 with corrections to the Cover Date.     

甜高粱叶绿素荧光特性对生物有机液体混合肥的响应

为揭示生物有机液体混合肥对陕北农牧交错区青贮饲草作物光合作用的影响,以甜高粱(Sorghum bicolor L.)为研究对象,通过盆栽控制试验,设置4种浓度的生物活性水(BMW)(B1、B2、B3和B4,分别为稀释600、400、200和100倍的BMW溶液)和3种浓度的Aidoora溶液(A1、A2和A3,分别为稀释1000、500和300倍的Aidoora溶液)的生物有机液体肥处理,测定比较了不同生物有机液体混合肥下甜高粱叶片叶绿素荧光特性。结果表明:在大多数单一液体肥和混合液体肥下,适宜浓度水平的BMW和Aidoora溶液均能显著提高甜高粱幼苗叶片的PSⅡ最大光量子效率(F_v/F_m)、PSⅡ实际光化学量子效率(ΦPSⅡ)、光化学淬灭系数(qP)和表观光合电子传递速率(ETR),并降低了其非光化学淬灭系数(NPQ),且以有机液体混合肥的促进作用更显著,这说明施加生物有机液体肥后均能提高其叶片PSⅡ光化学效率和光合电子传递速率,而降低了非辐射性热能量耗散。综上分析表明,B2A2相对于其他BMW和Aidoora混合液体肥有利于促进甜高粱幼苗叶片PSⅡ光化学活性。     

Barley varieties in semi‐controlled and natural conditions—Response to water shortage and changing environment

The yield potential of 60 spring barley varieties was examined under controlled drought and natural conditions in the years 2011–2013. The studied varieties were genotyped with the 1536‐SNP barley oligonucleotide assay. In experiments with controlled drought conditions, the grain yield, 1,000‐grain weight, number of productive tillers and length of the main stem were measured. Physicochemical properties such as the specific surface area, water adsorption energy, fractal dimension and nanopore radius of the plant leaves were determined and correlated with yield‐forming traits. Field trials were conducted over 3 years at 14 locations, where along with the yield‐related traits, monthly rainfall and average temperature were monitored. Five varieties of high yield and five varieties relatively stable under both semi‐controlled and natural conditions were distinguished. The yield‐related traits observed in various locations were related to environmental variables relevant to water availability. The sum of the rainfall in April and May was negatively correlated with the 1,000‐grain weight and positively with the plant height. Positive relationships were found between plant height and temperatures in June and July. Five markers detected earlier as linked to the quantitative trait loci in the mapping populations were identified to have a coherent effect among varieties of various pedigree.     

Stability Analysis of Yield in Maize,Wheat and Sorghum and its Implications in Breeding Programs*

Six stability statistics: (b_i, s²_di, , , and ) were estimated for maize, wheat and sorghum in different environments by using three statistical models. The significant linear portion of genotype × environment interaction for maize indicates different hybrids responded differently to environments, whereas the non-significant genotype × environment interaction (linear) were found for wheat and sorghum suggest that all genotypes responded similarly as the environments change. However, the highly significant pooled deviations (deviation from regression) for all three crops make yield predictions from the model less reliable. When regression coefficients (b_i) were non-significant, s²_di, became an important statistic in estimating stability. It appears that the regression coefficient, b_i, was best used to estimate genotypic adaptability, whereas s²_di, for stability. Maize and sorghum had negative correlations between the mean yield and stability statistics, s²_di, , and , suggesting that high yield and stability are not mutually exclusive in the range of environments used in this study; however, such correlations did not occur in wheat. Thus, maize and sorghum hybrids with high yield potential and high stability could be identified and selected. Correlations between mean yield and b_i, or , were positive and significant for maize and sorghum but were non-significant for wheat, indicating that such relationships may be species specific. Under a given set of testing environments, the stability ranking associated with each maize hybrid is correlated to and depends on other hybrids included in the analysis.     

Genotype by environment interaction of tomato blossom-end scar size

Summary Large blossom-end scar is a disorder in tomato fruit which reduces its marketability. The disorder is affected by genotype and by several environmental factors and therefore the genotype by environment interaction was studied by stability analysis. Blossom-end scar size was recorded for 4 tomato cultivars grown in 6 fields. The blossom-end scar size (BSC) was affected by the genotype, the field and their interaction. Stability analysis revealed that most of the interaction resulted from different stability of the cultivars. Heterogeneity of the slopes was significant (P<0.0013). The stability slopes were 0.29, 0.74, 1.11 and 1.85 for BR-214, FA-38, Hayslip and Suncoast, respectively. The stability slopes seemed to associate with the means of the cultivars over all environments, which were 1.57, 2.92, 3.84 and 5.43, respectively. Analysis of a blossom-end scar index (BSI), which also takes fruit size into account, revealed stability similar to BSC. It was concluded, that selection for small BSC under most conditions would yield cultivars with small and stable BSC under most growing environments, however differences between genotypes in non-inducing environments are expected to be small.     

籼粳交稻米蛋白质含量的基因型与环境互作效应的分析

用包括基因型×环境互作效应的种子性状遗传模型,对籼粳交组合的蛋白质含量进行了遗传研究,结果表明：在籼粳交组合中,蛋白质含量的遗传表达主要受直接加性和母体加性效应控制,以母体加性效应为主。直接显性、母体显性和细胞质效应方差分量也达到显著或极显著水平。基因型×环境互作主要表现为直接加性×环境、母体加性×     

Variation of the genomic proportion of the recurrent parent in BC1 and its relation to yield performance in sorghum (Sorghum bicolor) breeding for low-input conditions

In order to define the variation of the genomic proportion of the recurrent parent [G(RP)] and its relation to yield, G(RP) of individual BC₁ plants of two sorghum populations composed of a high‐yielding cultivar as recurrent parent (RP) and a donor with superior drought resistance or grain quality, respectively, was estimated using AFLPs and SSRs. G(RP) in BC₁ ranged from 0.53 to 0.95 and averaged to 0.76 in the population (NP4453 × ‘SV‐2’) × ‘SV‐2’. G(RP) varied between 0.60 and 0.86 and averaged to 0.74 in the BC₁ of (ICV‐219 × ‘SV‐2’) × ‘SV‐2’. Results show that plants with a G(RP) equivalent to BC₂ (0.875) or BC₃ (0.938), respectively, can be selected from BC₁. Yield performance of BC₁S₁ families was tested in field trials carried out in South Africa. The correlation between yield and G(RP) in BC₁ was low. Selection according to G(RP) did not result in an effective preselection for yield.     

高粱A3类型后代花粉碘染色率与田间自交结实率的关系

以高粱A3雄性不育系A3299,A32457,A3JW;相应的保持系B3299,B32457,B3JW;恢复系1174及用恢复系1174与3个A3不育系组配成3个杂交种的F1,F2群体为材料,分析高粱A3类型后代花粉碘染色率与田间自交结实率之间的关系。结果表明:田间3个F1组合的套袋结实率为10%~70%,平均约为50%,与花粉染色率相当。3个组合F2可育与不育单株比约为1∶1,育性分离不同于配子体模式,也不符合孟德尔分离规律。RT与R0.75和R1.0存在极显著的回归关系,与R0.25存在显著的回归关系,回归方程为RT=0.188 R0.25 0.832 R0.75 0.933 R1.0,品种间存在差异。     

Contributions to the Analysis of Genotype × Environment Interactions: Experimental Results of the Application and Comparison of Clustering Techniques for the Stratification of Field Test Sites

The results from multienvironment field performance trials of cultivars are usually analysed as two‐way classification data with rows=genotypes/cultivars and columns=environments (locations and/or years). To reduce the impact of genotype × environment interaction effects, one commonly stratifies genotypes/cultivars or environments by cluster analysis techniques into homogeneous groups so that interactions within groups are minimized. By such a stratification, for example of test sites, with regard to similarity of genotype × environment interactions and the selection of only one representative test site from each group, the overall number of necessary test sites for yield trials can be reduced. In the literature, many clustering techniques have been proposed. Systematic comparisons between different cluster methods, however, are rather rare. A single cluster method is characterized by `measure of distance', `stopping criterion', `algorithm' and `level of significance'. In this paper, 11 clustering techniques were applied to extensive yield data sets of several agricultural crops (faba bean, fodder beet, oat, winter oilseed rape and sugar beet) from the official registration trials of the German `Bundessortenamt'. The results were compared with each other using two proposed parameters: measure of resemblance (for two classifications) and cluster size (for one classification). Neither the level of significance nor the algorithm has a substantial impact on the resulting clusters. The final results of clustering are therefore mainly determined by the stopping criterion with its associated measure of distance. If one uses tests for crossover interactions as stopping criteria, the resulting clusters are larger than the resulting clusters for the F‐test of conventional interactions in an analysis of variance. The cluster size decreases with increasing sensitivity of the tests that are used as stopping criteria. Finally, recommendations for the choice and handling of clustering techniques for practical applications are given.     

The Influence of Genotype–Environment Interaction on the Grain Yields of 10 Pigeonpea Cultivars Grown in Kenya

To study the importance of the effects of genotype–environment interactions on the yield of pigeonpea ( Cajanus cajan L. Millsp.), 10 early-maturing genotypes were grown in a randomized complete block design with three replications in a total of seven environments spread over five regions of Kenya between 1987 and 1988. Results indicated the presence of a substantial genotype–environment interaction effect on grain yield. The observed significant genotype–environment interaction effect is discussed in relation to its importance in pigeonpea grain yield evaluation studies. It is noted that the best genotype in one environment is not always so in other environments. Results from regression analysis indicated that this method of analysis is appropriate for describing the response of pigeonpea genotypes grown in a number of locations. Analysis of variance showed significant additive and multiplicative genotype–environment interaction effects. Only the first interaction principal component axis (IPCA) was found to be important in describing the multiplicative interaction effects. The additive main effects and multiplicative effects (AMMI) model allowed the partitioning of interaction variance into agronomically important sources (genotype groups), and the specific genotype × environment patterns that are the basis of these sources of variance were examined.