Genetic Parameters and Multivariate Analysis to Determine Secondary Traits in Selecting Wheat Mutant Adaptive on Tropical Lowlands

Farid, Muh.; Nasaruddin, Nasaruddin; Musa, Yunus; Anshori, Muhammad Fuad; Ridwan, Ifayanti; Hendra, Jekvy; Subroto, Gatot

doi:10.9787/pbb.2020.8.4.368

Cited by 20 publications

(15 citation statements)

References 29 publications

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“…Therefore, 3D plot grouping can be a solution for mapping the three indices. This was also reported by Farid et al (2020) through the mapping of character selection results from PCA.…”

Section: Discussionsupporting

confidence: 71%

“…ANOVA in screening tolerance is the initial basis for determining the character of selection in tolerance screening (Anshori et al, 2018;Farid et al, 2020). In addition, this analysis is applicable as a benchmark for the suitability of a method or selection environment (Al-Naggar et al, 2015;Safitri et al, 2016).…”

Section: Discussionmentioning

confidence: 99%

“…Therefore, characters that have significant interactions can be indicated as selection character (Ali et al, 2014;Safitri et al, 2016;Fadhli et al, 2020). The application of this concept has been reported by Anshori et al (2019) on double haploid rice against salinity stress, Fadhli et al (2020) on maize against drought stress, and Farid et al (2020) on wheat against temperature stress. Based on this, fresh weight of sprouts, length of plumules, percentage of sprouts, height of shoots, number of tillers, root length, shoot fresh weight, root fresh weight, total biomass fresh weight, chlorophyll a, scope and reflection can be taken as candidates for selection characters in the salinity screening which correspond to the character group.…”

Section: Discussionmentioning

confidence: 99%

“…Principal component analysis (PCA) is a multivariate analysis that can condense big data dimensions into simpler ones while maintaining diversity in the original data (Mattjik et al, 2011;Farid et al, 2020). This analysis is widely used in various scientific disciplines, including plant breeding (Acquaah, 2012).…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Interaction of rice salinity screening in germination and seedling phase through selection index based on principal components

Farid

Anshori

Musa

et al. 2021

Chil. j. agric. res.

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Salinity stress can reduce rice (Oryza sativa L.) productivity and cause crop failure. This problem needs a solution by development of tolerant varieties, and this development closely relates to the effectiveness of its screening. Screening at the phase of germination and seedling are the most common ones. However, the interactions between screenings based on the growth character selection index have not been widely reported, particularly with the principal component analysis (PCA). Therefore, the aim of this study was to determine the interaction between phases of rice salinity screening through a selection index based on PCA. This study consisted of two phases of salinity screening, namely growth phase of germination and seedlings. Both screenings were designed with a nested randomized complete block design, where replicates were nested in a selection environment. The selection environment consisted of two levels, normal (0 mM NaCl) and saline (120 mM NaCl). The genotypes consisted of eight varieties and was repeated three times. Observations were based on morphological and physiological characters, especially in seedling phase screening. Results showed that morphological character approach of the seedlings had a large distribution of salinity tolerances. The use of stress tolerance index and PCA were considered effective in the formation of the selection index on salinity screening. As for, the morphology index was formulated as 0.32 shoot height + 0.33 root fresh weight + 0.33 shoot fresh weight + 0.26 root length + 0.01 number of tillers, length + 0.34 total biomass fresh weight. Therefore, the use of this analytical concept is recommended in screening the tolerance of rice lines to salinity stress.

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“…Therefore, 3D plot grouping can be a solution for mapping the three indices. This was also reported by Farid et al (2020) through the mapping of character selection results from PCA.…”

Section: Discussionsupporting

confidence: 71%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Interaction of rice salinity screening in germination and seedling phase through selection index based on principal components

Farid

Anshori

Musa

et al. 2021

Chil. j. agric. res.

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“…The morpho-physiological data were systematically analyzed through analysis of variance (ANOVA), factor analysis, and path analysis (Farid et al, 2020). The results of the paths become the basis for the formation of a morpho-physiological index.…”

Section: Discussionmentioning

confidence: 99%

Integrated Corn Cultivation Technology Based on Morphology, Drone Imaging, and Participatory Plant Breeding

Farid¹,

DJUFRY²,

Yassi³

et al. 2022

SABRAOJBG

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The evaluation of a cultivation technology would be more efficient when the technology assessment is based on various approaches like conventional morphological approaches, the use of drone’s normalized difference vegetation index (NDVI) imaging, and participatory plant breeding (PPB). The recent study aimed to assess the effectiveness of the combination of morphological approaches, drone imaging, and participatory plant breeding in selecting the best corn cultivation technology package. This research conducted in a randomized complete block design (RCBD) with one factor from March to December 2021 at the Village Taroang, Takalar Regency, South Sulawesi, Indonesia. The factor is 40 cultivation technology packages. The treatments were replicated three times, thus having 120 experimental units. For plant participation, the investigations were conducted with 56 farmers on their corn fields through quantitative surveys in the targeted area. For NDVI, the observation was recorded 70 days after planting using a DJI Inspire two unmanned aerial vehicles equipped with a multi-spectral camera. Based on the results of the study, the combined strategy of different approaches like morpho-physiological, drone’s NDVI, and participatory plant breeding is found effective in evaluating the corn production technology. The yield, plant height, percentage of net yield, and cob weight were good selection criteria for the morphology approach in evaluating corn cultivation. The NDVI could be recommended in helping the morphology evaluation and PPB, especially in a large-scale evaluation. Based on a combined assessment of the different approaches, the maize cultivar Pioneer-27 combined with ‘Legowo’ spacing technology, NPK fertilizer ratio of 200:100:50, KNO3 at the rate of 25 kg, and application of biofertilizer 'Eco farming' @ 5 cc L-1, was recommended as the best corn production technology package in the Village Taroang, Takalar Regency, South Sulawesi, Indonesia.

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Effect of salinity on seed germination and seedling growth of bullet cultivar of chilli (Capsicum annuum L.)

Sarkar

Oraon²,

Mondal³

et al. 2023

Braz. J. Bot

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Genetic Parameters and Multivariate Analysis to Determine Secondary Traits in Selecting Wheat Mutant Adaptive on Tropical Lowlands

Cited by 20 publications

References 29 publications

Interaction of rice salinity screening in germination and seedling phase through selection index based on principal components

Interaction of rice salinity screening in germination and seedling phase through selection index based on principal components

Integrated Corn Cultivation Technology Based on Morphology, Drone Imaging, and Participatory Plant Breeding

Effect of salinity on seed germination and seedling growth of bullet cultivar of chilli (Capsicum annuum L.)

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