Multi environment and spatial analysis of early maturing sorghum [Sorghum bicolor (L.) Moench] genotypes in dry lowland areas of Ethiopia Amare Seyoum1, Amare Nega1, Kedanemaryam Wagaw1, Taye Tadesse2, Diriba Tadesse2, Alemu Tirfessa1, Habte Nida3, Adane Gebereyhones1, Sewmehone Siraw1, Tsegaye Gebremariam4, Chalachew Endalamaw1, Hailemariam Solomon1, Tamirat Bejiga1, Tokuma Legesse1, David Jordan5, Emma Mace5, Daniel Nadew1, Ligaba Ayele1 and Meron Bogale1 1Ethiopian Institute of Agricultural Research (EIAR), Melkassa Agriculture Research Center, P. O. Box 436, Adama, Ethiopia. 2Ethiopian Institute of Agricultural Research (EIAR), Head Quarter, P. O. Box 2003 Addis Ababa, Ethiopia. 3Purdue University, 610 Purdue Mall, West Lafayette, IN 47907, United States. 4Tigray Agricultural Research Institute (TARI), P. O. Box 492, Mekelle, Ethiopia. 5Queensland Alliance for Agriculture and Food Innovation, Hermitage Research Facility 604 Yangan Rd Warwick QLD 4370, Australia. Received 28 September, 2019; Accepted 31 January, 2020 In Ethiopia, drought usually occur due to delay in onset, dry spell after sowing, drought during critical crop stage (flowering and grain filling stage) and too early cessation of rainfall. These situations can be addressed by developing improved sorghum varieties which are resistance to drought. Developments of sorghum varieties resistant to drought and producing better grain yield while addressing the plant biomass requirement is one of the strategies in the sorghum breeding program in dry lowland environment. A total of 90 early maturing sorghum genotypes were evaluated along with two standard check varieties to estimate the grain yield, plant height, days to flowering, days to maturity and overall agronomic aspects and stability of performance across the test environments. The trial was conducted using Randomized Complete Block Design (RCBD) in row and column arrangement. Linear mixed model has been used to predict and identify stable and superior varieties across the test environment. Correlations of the trials range from positive +1 to -1 where positive correlation is an indication of similarity among the testing environments while negative correlation is an indication of non-similarity among testing environments. Moreover, using the biplot it was observed that the stability and correlation among testing site where the angle between the two lines measure the strength of correlation. Improvement in heritability has been obtained due to spatial variation using advanced statistical analysis methods without any additional cost. Three genotypes exhibited better yield advantage, higher plant biomass and overall plant aspect including drought tolerance. In addition, these genotypes were preferred by farmers in their overall agronomic desirability (drought tolerance, earliness, head exertion and compactness, grain size and shape and threshability. Also, the national variety releasing committed has evaluated the variety verification trial both on station and farmers’ field condition in 2018/2019 and they decided the release of the candidate variety 14MWLSDT7114 (2005MI5060/E-36-1) for commercial production in dry lowland environment. Key words: Genotype, heritability, mixed model, Spatial analysis, GEI, correlated environment.

Recent global climatic changes have highlighted viticulture in arid/semiarid regions as an increasingly relevant study model. Grapes in arid regions face excessive solar irradiance, leading to more than 50 °C berry surface temperatures in exposed berries. The resultant oxidative stress, sunburn necrosis, and browning consistently reduce berry quality. Adapting an adequate training system to the climate and cultivar is a simple and inexpensive method to control the radiation regime. This study compares the berry and wine characteristics and compositional components of desert-grown Vitis vinifera L. cv. Gewürztraminer, trained on either a Vertical Shoot Positioning (VSP) system or a Y-shaped training system (SAYM, Sistema di Allevamendo ad Ypsilon Integralmente Meccanizzabile), a method with a higher canopy light interception. The SAYM training reduced direct radiation and concomitant heat in the cluster zone and significantly alleviated oxidative stress in berries in the 2016/17 season. In addition, SAYM-grown berries were preferable in terms of quality and productivity. Correspondingly, a sensorial analysis rated SAYM wines higher than VSP wines in all categories. Photosynthetic pigment content in the berries' skin showed similarities between VSP and SAYM, and a volatile compound analysis of the wines by GC-MS revealed a higher ester content in the wines derived from SAYM vines, along with a higher content of compounds linked to Gewürztraminer wine typicity (varietal characteristics such as esters, terpenoids, and alcohols).

For sorghum hybrid development, assessment of parental lines is a pre-requisite. However, information on heterotic performance and combing ability of Ethiopian elite sorghum lines is inadequate. ANOVA revealed mean squares had signifying substantial amount of variability amongst genotypes for most traits. Males 72, 81 and 99 were the best performing parents for yield and related traits. Hybrids, 106 x 94, 106 x 90, 106 x 102, 107 x 99 and 107 x 105 were found maximum heterotic hybrids for yield as compare to check. The estimates of variance of combining ability revealed that σ2gca was found inferior to σ2sca for all traits except plant height and number of heads. The σ2gca/σ2sca ratio revealed preponderance of supremacy gene action for most traits. The degree of dominance was found greater than unity for entire traits except plant height. The estimations of parental GCA effects showed that female 106 and males 79, 96, 94 and 81 were good general combiners for yield and related traits. Based on perse performance, heterotic response, combining ability and nature of gene action for yield and related traits, female parent 106 and male parents 94, 102 and 90 were found most performed. Those parental lines were grouped into dualistic heterotic groups based on their SCA and GCA results. Key words: Combining ability, elite line, general combining ability (GCA) and specific combining ability (SCA), heterosis, heterotic group, hybrid, sorghum.