There are many local varieties of sweet potatoes which are cultivated and consumed in Indonesia. The food industry which uses sweet potato as the main raw material has been developed in West Java. Demand for orange-fleshed sweet potato is high, but the supply of demand has not been fulfilled. This is because the varieties that are widely cultivated do not meet consumer standards and preferences, so new superior genotypes are needed following demand. Currently, selection of stable and high-yielding genotypes and accordance with consumer and industry preferences is one of the focuses of sweet potato research. Orange-fleshed sweet potato multi locations testing in accordance with consumer and industry preferences, can be used as a basis for consideration in the development program. The purpose of this study were to identify genotype by environment interactions (GEIs) and t select superior genotypes and to estimate yield stability across three locations in West Java, Indonesia. Combined analysis of variance (ANOVA) was used to determine significant differences between each genotype tested in term of yield and to estimated genotype by environment interactions (GEIs). Additive Main Effects and Multiplicative Interaction (AMMI), Genotype Plus Genotype by Environment Interactions (GGE) biplots, and Parametric and non-parametric stability measurements were used to determine yield stability from genotypes tested in all locations (Sumedang Regency, Bandung Regency, Karawang Regency). Data in this article showed that the genotypes, environments, and GEIs had an effect on sweet potato yields, with influences of 35.03%, 18.87%, and 46.01%, respectively. The results in this data also indicate that some new sweet potato genotypes have stable and high yields in three environments in West Java, Indonesia. So they were can be used for development in sweet potato breeding programs.

Hybrids that are stable or adaptable in a specific location for the western region of Indonesia are required to increase production of maize in Indonesia. The objectives of the study were (i) to select maize hybrids which are stable or adaptable in the western region of Indonesia and (ii) to determine the discriminant location for evaluating superior hybrids in the western region. Therefore, twelve maize hybrids were planted in different locations and seasons in the western region. Hybrids were selected based on GGE biplot analysis. The results showed that G9 and G10 were stable maize hybrids. G6 was the selected hybrid for the first megaenvironment; whereas, G3 was selected as the hybrid for the second megaenvironment. The L8 and L17 were the discriminant environment for evaluating hybrids in the western region of Indonesia. The high-yielding hybrids selected in this study should be broadly evaluated on-farm in order to disseminate for small holder farmers in Sumatera and Java islands.

Selection of high yielding and stable maize hybrid requires effective method of evaluation. Multienvironment evaluation is a critical step in plant breeding programs that is aimed at selecting the ideal genotype in a wide range of environments. A method of evaluation that combines a variety parameter of stability could provide more accurate information to select the ideal genotype. The aims of the study were (i) to identify the effect of genotype, environment, and genotype × environment interactions (GEIs) on maize hybrid yields and (ii) to select and to compare maize hybrids that have high and stable yields in diverse environments in Sumatra Island based on combined analysis, selection index, and GGE biplot. The study was conducted in five different environments in Sumatra Island, Indonesia, using a randomized complete block design repeated three times. Data were estimated using combined variance analysis, parametric and nonparametric stability, sustainability index, and GGE biplot. The results showed that the genotype had a significant effect on maize hybrid yields with a contribution of 41.797%. The environment contributed to 24.314%, and GEIs contributed 33.889% of the total variation. E1 (Karo, South Sumatra; dry season) and E3 (Tanjung Bintang, Lampung; dry season) were identified as the most ideal environments (representative) for testing the hybrids for wider adaptability. The maize hybrid with high and stable yields can be selected based on combined stability analysis and sustainability index as well as GGE biplot. These three methods are effectively selected high yielding and stable genotypes when they are used together. The three maize hybrids, namely, MH2, MH8, and MH9, are recommended as high yielding and stable genotype candidates.

Determination of grain yields of stable and high-yielding maize hybrids in a wide environment requires high accuracy. Many stability measurement methods have been used in multi-environment experiments. However, the relationships among the different methods are still difficult to understand. The objectives of this study were to 1. Identify the effect of growing season and location (Environments = E), hybrids (Genotypes = G), and their interactions (GEIs) on grain yields; 2. Select high-yielding and stable maize hybrids in a wide range of environments; 3. Determine the relationship between each stability estimation; and 4. Determine the mega-environment of maize hybrid and identify the best locations for testing. Field experiments were conducted at ten locations in Java Island, Indonesia, for two growing seasons using a randomized completed block design with three replications. The experimental results showed that the main effects of the growing season, location, hybrid, and GEIs, significantly affected maize hybrid yields. Stability estimations of TOP, S(3), S(6), NP(2), NP(3), KR, NP(4), CVi, and bi, belong to the concept of dynamic stability that can be used to select maize hybrids in favorable environments, while other estimations were classified as in the static stability. Three maize hybrids were successfully selected, with high and stable yields based on numerical and visual stability estimations, namely SC2, SC7, and SC9. The three hybrids can be used as candidates for sustainable maize development programs. The dry season, the rainy season, and the combination of two growing seasons produced three mega-environments. GJRS and KARS were the most discriminative environments. Both environments can be used as favorable environments for selecting the ideal maize hybrid.

Abstract. Amien S, Maulana H, Ruswandi D, Nurjanah S. 2021. Genetic gain and relationship of yield and yield attributes of mutant and cross-bred stevia (Stevia rebaudiana) genotypes. Biodiversitas 22: 3119-3126. Plant breeding programs involved many traits and genetic parameters in the selection process. The information on genetic parameters on yield and other related traits provided an overview for breeders and farmers in selecting new superior genotypes. The purpose of this study was to estimate genetic parameters including heritability and genetic gains in yield and other traits, to determine the relationship between various traits, and to select superior stevia (Stevia rebaudiana Bertoni) genotypes for each trait. Field experiments were carried out in two planting environments, namely, the highlands and the medium plains employing a randomized completed block design and each genotype was three replicates. The results showed that the yield had high heritability and genetic gains  ??in mutant populations, whereas cross-bred populations had moderate heritability and low genetic gains. Stem weight (SW) and number of leaves (NoL) traits were identified as having high heritability and genetic gains in both populations. The GT biplot measurement showed that the yield was identified to have a significant and positive correlation with SW (p<0.05). H4 was correlated with Number of branches (NoB), Yield, SW, and chlorophyll content (Chl) traits in the cross-bred populations. H9 excelled on and was correlated with NoL and plant height (PH). M11 was identified to be highly correlated with NoL, PH, NoB, and Chl traits in the mutant populations, while M15 excelled on and was correlated with yield and SW. The results of this study revealed that there was a potential for improvement in the traits tested of stevia through cross-bred and mutant populations in different environmental conditions. The selected genotypes can be developed in a suitable environment and used for further stevia plant breeding programs.

<div class="page" title="Page 1"><div class="layoutArea"><div class="column"><p><span>Keragaman genetik ubi jalar dapat dinilai berdasarkan analisis terhadap karakter-karakter tertentu. Tujuan penelitian ini adalah untuk melakukan pendugaan keragaman klon ubi jalar ungu berdasarkan karakter agronomi dan morfologi tanaman. Percobaan dilaksanakan selama musim hujan di Kebun Percobaan Ciparanje, Fakultas Pertanian Universitas Padjadjaran, Sumedang, Jawa Barat mulai November 2018 sampai April 2019. Perlakuan adalah 11 klon ubi jalar ungu yang berasal dari Indonesia, Peru, dan Jepang. Pengamatan terdiri atas karakter agronomi dan morfologi, serta komponen hasil. Pendugaan keragaman genetik menggunakan analisis klaster, analisis komponen utama, uji mantel, dan perhitungan ragam genotipik dan fenotipik. Hasil penelitian menunjukkan terdapat perbedaan keragaman genetik berdasarkan karakter agronomi dan karakter morfologi. Jarak genetik berdasarkan analisis klaster dan analisis komponen utama pada karakter agronomi dan morfologi masing- masing adalah 0,31–5,18 Euclidean dan 1,73–4,55 Euclidean. Korelasi keragaman agronomi dengan keragaman morfologi sangat lemah (r=0,096). Perhitungan ragam genotipik dan fenotipik juga menunjukkan bahwa keragaman karakter agronomi cenderung luas. </span></p></div></div></div>

Optimizing the performance of a company is inseparable from the work achievement of the employees in carrying out all their duties. Religious factors become one of the factors driving the optimization of performance achievement wich must be maximized. This study aims to determine how the influencer of religiosity on the performance of muslim employees in the Regional Water Company (PDAM) Pamekasan. This research is quantitative study with a population of 48 employees in the Pamekasan Regency PDAM office, all of wich were used as reseach samples. Questionnaire is used as a data collection method using a likert scale as a measurement tool. Data analysis using simple linear regression analysis, partial test (T) and the coefficient of determination (R²) test using SPSS version 23. The result of simple linear regression analysis showed the regression coefficient was a 1 then employee performance has increased by 0,028. T test results are at a significance value of 0,828 > 0,05, wich means that the variable of religiosity does not affect employee performance. While the R² test result are at the value of 0,001, wich means that there are ither variables outside the study that affect the performance of PDAM Pamekasan employees.

Turmeric ( Curcuma longa L.) is widely used as traditional medicine, kitchen spice, and natural dyes in Indonesia. The demand and popularity of this plant is increasing; however, the national supply is still low. Turmeric breeding and crop improvement in Indonesia are needed to boost the national turmeric production. Exploration of turmeric from various areas in Indonesia is a prior step of turmeric breeding. Phenotypic diversity and relationship analysis of an early population can be used as a basis for consideration in plant development and breeding programs. The purpose of this study was to estimate phenotypic diversity and relationship of local turmeric accessions from Indonesia. Raw data analysis was conducted after standardization using Principal Component Analysis (PCA) and Hierarchical Clustering Analysis (HCA) to determine phenotypic diversity and relationship among the newly collected genetic resources. The data in this article showed broad phenotypic diversity with plant height, number of shoots, number of leaves on main shoot, petiole length, lamina length, lamina width, number of mother rhizome, total rhizome weight, weight per shoot, pseudostem habit, leaf margin, and rhizome habit as distinguishing traits among the collection. PCA also resulted cumulative variation percentage of 70.73%. In addition, HCA resulted two main groups with the Euclidean range of 0.31—2.97.