Effective Screening of Tropical Wheat Mutant Lines under Hydroponically Induced Drought Stress Using Multivariate Analysis Approach

Farīd, Muḥammad; Nasaruddin, Nasaruddin; Musa, Yunus; Ridwan, Ifayanti; Ansho, Muhammad Fuad

doi:10.3923/ajps.2021.172.182

Cited by 18 publications

(25 citation statements)

References 21 publications

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“…Based on the selection index, productivity does not dominate index variance but is the main character, as a result, the index requires adjustment. This has been reported by Anshori et al (2019) on rice under salinity stress and Farid et al (2021) on wheat under drought stress. Therefore, the adjusted selection index was formulated in this study.…”

Section: Resultssupporting

confidence: 69%

Drought-adapted maize line based on morphophysiological selection index

et al. 2021

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Abstract. Padjung R, Farid M, Musa Y, Anshori MF, Nur A, Masnenong A. 2021. Drought-adapted maize line based on morphophysiological selection index. Biodiversitas 22: 4028-4035. Synthetic line formation is an effort to increase maize productivity in drought-stressed areas. This process requires systematic selection in determining adaptability levels involving important secondary characters formulated in the selection index. Furthermore, the principal component index had been widely reported, both in normal and stressed conditions. The selection index development on morpho-physiological characters based on multivariate analysis was expected to increase drought stress tolerance and maize lines selection precision. Therefore, the purpose of this research was to form a selection index based on morpho-physiological characters and selecting synthetic lines adaptive under drought stress. This research was designed using a split-plot with 3 replications, where the main plot consisted of normal and stressed irrigation, while the subplot was genotype consisting of 6 lines and 3 check varieties namely Bisma, Lamuru, and Sukamarga. Observations were performed on 18 morphological and 4 physiological characters, and the results showed that the selection index was formed based on multivariate analysis from 9 characters. Through index selection, Syn_2-2 (0.79), Syn_2-15 (0.85) and Syn_2-16 (0.97) were considered as drought stress adaptive lines. Therefore, the 3 lines can be recommended in the synthetic variety release process.

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Section: Resultssupporting

confidence: 69%

Drought-adapted maize line based on morphophysiological selection index

et al. 2021

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“…This step will minimize bias in predicting or projecting supporting characters that directly affect the yield (Alsabah et al, 2019;Akbar et al, 2021;Karima et al, 2021). The same concept was also reported by Farid et al (2020Farid et al ( , 2021a in wheat, Anshori et al (2019Anshori et al ( , 2021 in rice, Fadhli et al (2020), and Padjung et al (2021) in maize crop. Based on the correlation analysis, plant height, cob weight, percentage of net yield, and 1000-seed weight were found significantly correlated with yield.…”

Section: Discussionmentioning

confidence: 82%

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

Farid¹,

DJUFRY²,

Yassi³

et al. 2022

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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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“…The use of correlation analysis and cross-print analysis in determining the character of selection has also been performed by many researchers including Milligan SB, Gravois KA, Bischoff KP, Martin FA. (1990), Akhmadi (2016), Anshori et al, (2019), Fadhli et al,(2020 and Farid et al, (2021). The cross-print of IST of the production per clump character shows a representative result on the determinant coefficient value of 0.80 (Table 4).…”

Section: Resultsmentioning

confidence: 89%

“…and Anshori et al (2018) who did it on soil media. Hydroponics method is the most widely performed due to possibility for more controllable selection and the absence of cofactors that affect salinity levels in the testing media (Faiyue, 2012;Safitri, 2016;Anshori et al 2020;Farid M, Nasaruddin, Musa Y, Ridwan I, Anshori MF. (2021).…”

Section: A Introductionmentioning

confidence: 99%

Hydroponic Salinity Screening by Deep Flow Technique on All Paddy Growing Phases

Nasaruddin

Anshori

Bdr

et al. 2022

ATJ

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Salinity screening under hydroponic Deep Flow Technique (DFT) has not been widely studied, especially on the nature of rice tolerance to salinity stress. According to previous screening studies, this method was effective in distinguishing the nature of rice tolerance to salinity stress. However, they were tested only at generative phase. Therefore, evaluation on screening method with hydroponic DFT at all phases of paddy growth is essential. The objective of this study is to evaluate the filtering under hydroponic DFT at all paddy phase and to determine secondary character that support productivity which can be utilized as selection character in this screening process. The experiment was arranged with a complete nested group design with nested replication is the NaCl stress. There were 5 (Five) tested rice varieties and the stress environment consisted of three levels: 0, 60, and 120 mM of NaCl, all with 3 (three) replications. The nutrient culture screening was adapted to the modified Egdane method. The results showed that screening under hydroponic DFT was effective at the concentration of 60 nM of NaCl. The best selection character was yields per clump, number of productive tillers and total chlorophyll. The variety of Jeliteng, Ciherang and Inpari 34 of Salin Agritan, were classified as tolerant group. This hydroponic DFT Filtering method could be recommended as one salinity screening method for all paddy growing phases

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Effective Screening of Tropical Wheat Mutant Lines under Hydroponically Induced Drought Stress Using Multivariate Analysis Approach

Cited by 18 publications

References 21 publications

Drought-adapted maize line based on morphophysiological selection index

Drought-adapted maize line based on morphophysiological selection index

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

Hydroponic Salinity Screening by Deep Flow Technique on All Paddy Growing Phases

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