Storage root yield and sweetness level selection for new honey sweet potato (<i>Ipomoea batatas</i> [L.] Lam)

Karuniawan, Agung; Anindita, Putri Ardya; Yoel, Andrew; Ustari, Debby; Suganda, Tarkus; Concibido, Vergel

doi:10.1515/opag-2021-0219

Cited by 9 publications

(12 citation statements)

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“…have the same power in estimating genotype stability; therefore, the three stability parameters were suggested to select stable genotypes [9,18]. Based on the average ranks (AR), the maize hybrid of MH2 followed by MH8, MH9, and MH5 had a small AR value; therefore, these maize hybrids can be proposed as the most stable genotype.…”

Section: Evaluation Of High Yielding Maize Hybrids Usingmentioning

confidence: 99%

“…In some cases, maize yields are strongly influenced by GEIs due to environmental changes [5][6][7][8]. Studies also reported that GEIs complicate the selection process for crops like sweet potato in Indonesia [9], durum wheat in Turkey [10], yellow passion fruit in Brazil [11], and cotton in China [12]. Therefore, GEI analysis is important in evaluating superior genotypes.…”

Section: Introductionmentioning

confidence: 99%

“…Selection of stable and high-yielding genotypes can combine parametric and nonparametric stability models. This method has been applied in selecting high yielding and stable genotypes of many crops including in chickpeas [ 14 ], grass bean [ 15 ], wheat [ 16 ], barley [ 17 , 18 ], sweet potato [ 9 ], and peanut [ 19 ]. The use of combined analysis of the various stability parameters together with the multivariate GGE biplot for selecting stable and high yielding genotypes in multienvironment evaluation is recommended.…”

Section: Introductionmentioning

confidence: 99%

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Evaluation of High Yielding Maize Hybrids Based on Combined Stability Analysis, Sustainability Index, and GGE Biplot

Ruswandi

Syafi’i

Wicaksana

et al. 2022

BioMed Research International

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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.

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Section: Evaluation Of High Yielding Maize Hybrids Usingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Evaluation of High Yielding Maize Hybrids Based on Combined Stability Analysis, Sustainability Index, and GGE Biplot

Ruswandi

Syafi’i

Wicaksana

et al. 2022

BioMed Research International

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“…Selection is an important stage in plant breeding programs in determining superior genotypes. Several researchers have selected several characters including Yan and Frégeau-reid (2018) on oat yield, agronomic and quality traits, and Karuniawan et al (2021) on the yield and sweetness traits of sweet potatoes. Selection on multiple traits allows researchers and farmers to select genotypes that excel at multiple traits.…”

Section: Introductionmentioning

confidence: 99%

Genetic gain and relationship of yield and yield attributes of mutant and cross-bred stevia (Stevia rebaudiana) genotypes

et al. 2021

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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.

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“…Sweet potato farming, cassava, corn, and various bean types are the livelihoods of strategic residents in Madagascar, and most of the island's population consists of smallholders and herders, ranchers and farmers [2]. Tuber plants that play an important role in Indonesia include sweet potatoes [3]. One of the root crops in many countries is sweet potatoes [4].…”

Section: Introductionmentioning

confidence: 99%

Determination of Effectiveness and Efficiency of Production Factors in Sweet Potato Farming in Lamongan, Indonesia

Hamidah¹,

Rahayu²,

Sutrisno³

et al. 2021

International Journal on Advanced Science, Engineering and Information Technology

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Food crops have a strategic role in agricultural development, covering food security growth, opening up employment opportunities, and income sources in regional and national economies. This research aims to determine the relationship patterns of sweet potato farming production factors. This research utilized a quantitative approach with the survey method. The data were obtained through questionnaires, and the sampling method used a census of 348 respondent farmers in six sweet potato center villages. The Maximum Probability Estimation frontier 4.1 method was employed to calculate the technical efficiency of sweet potato farming. The results showed that the production factors significant at the trust level of 99 percent, 90 percent, and positive value for sweet potato production in Lamongan Regency, Indonesia, were land area production, Urea fertilizer, Phonska fertilizer, ZA fertilizer, and SP36 fertilizer. The technical efficiency attainment level of sweet potato farming was very high, indicating that sweet potato farming in the research was efficient, with an average technical efficiency of 0.90 percent. The achievement level of allocative efficiency on sweet potato farming was relatively low, implying that sweet potato farming was inefficient, with an average localized efficiency of 0.50 percent. The economic efficiency of sweet potato farming was very low, depicting inefficient sweet potato farming, with an average economic efficiency of 0.48 percent. Therefore, sweet potato farmers must optimize land use, ZA, Urea, SP36, and Phonska to produce sweet potatoes optimally to support food security.

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Storage root yield and sweetness level selection for new honey sweet potato (Ipomoea batatas [L.] Lam)

Cited by 9 publications

References 38 publications

Evaluation of High Yielding Maize Hybrids Based on Combined Stability Analysis, Sustainability Index, and GGE Biplot

Evaluation of High Yielding Maize Hybrids Based on Combined Stability Analysis, Sustainability Index, and GGE Biplot

Genetic gain and relationship of yield and yield attributes of mutant and cross-bred stevia (Stevia rebaudiana) genotypes

Determination of Effectiveness and Efficiency of Production Factors in Sweet Potato Farming in Lamongan, Indonesia

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