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Mousavi SMN, Illés A, Bojtor C, Demeter C, Zsuzsanna B, Vad A, Abakeer RA, Sidahmed HMI, Nagy J. Quantitative and qualitative yield in sweet maize hybrids. BRAZ J BIOL 2024; 84:e265735. [DOI: 10.1590/1519-6984.265735] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2022] [Accepted: 07/27/2022] [Indexed: 11/21/2022] Open
Abstract
Abstract Today, sweet corn is considered an important vegetable due to its high sugar content and low starch content. Cluster analysis and variance analysis showed that hybrids had variations in yield indices. GB, DE and GS hybrids had similar performance on indices. SE hybrid that has significant performance on zeaxanthin. Biplot showed that fructose, glucose, sucrose and potassium had stability value on hybrids. All the hybrids had the best performance on fructose, glucose, sucrose and potassium factors. Factor biplot positively correlated with yield indices, including calcium, iron, zinc, magnesium, α-Carotene, 9Z-β-Carotene, phosphorus, and β-carotene. On the other hand, there is a positive correlation with fructose, glucose, potassium, lutein, sucrose, β-Cryptoxanthin, and zeaxanthin. So, to evaluate or increase lutein and zeaxanthin, the other parameters like sugar content (fructose, glucose, and sucrose) are important factors and have an effect together. Factor analysis and biplot showed that ME hybrid had a maximum performance on the first factor of yield indices. Also, the second factor of yield indices had a maxi-mum effect on NO hybrids. SE hybrids had maximum performance in zeaxanthin and GS hybrid had maximum performance in zinc, phosphorus, and iron. The dry matter had stability on DB hybrid.
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Affiliation(s)
| | | | | | | | | | - A. Vad
- University of Debrecen, Hungary
| | | | - H. M. I. Sidahmed
- University of Debrecen, Hungary; National Center for Research, Sudan
| | - J. Nagy
- University of Debrecen, Hungary
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Semeskandi MN, Mazloom P, Arabzadeh B, Moghadam MN, Ahmadi T. Evaluation of seedling cultivation and irrigation regimes on yield and yield components in rice plant. BRAZ J BIOL 2024; 84:e266261. [DOI: 10.1590/1519-6984.266261] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2022] [Accepted: 09/13/2022] [Indexed: 12/23/2022] Open
Abstract
Abstract A split-plot experiment was conducted in a randomized complete block design with three replications in two cropping years at Mazandaran Rice Research Institute to study cultivation and irrigation regimes. The main factor is three-level irrigation regimes, permanent irrigation throughout the day (T1), irrigation two days after water disappears from the soil (T2) and permanent soil saturation (T3) the second factor is three-level cultivation methods., Plowless cultivation (W1), stack 60 cm (W2), and stack 80 cm (W3). Based on the results obtained from the combined analysis, the effect of the year was significant in terms of rainfall, productivity 2, number of tillers, number of empty grains, 1000-grain weight, percentage of the crushed grain, and white rice yield. The effect of the main factor was significant for all traits except productivity 1 and plant height. Based on the results of comparing the mean effect of year × treatment, four treatments, without plowing with permanent irrigation throughout the day in the first and second year of the experiment, cultivation without plowing with irrigation two days after water disappears from the soil in the second year of experiment and cultivation without Plowing with permanent saturated irrigation in the first and second years of the experiment was identified in terms of grain yield as suitable planting methods with appropriate irrigation regimes. Based on the results obtained from the polygon view in different years of the experiment, T3W1, T3W2, and T1W1 treatments can be suggested as desirable treatments in terms of irrigation regimes and cultivation methods in this rice cultivar. According to the ranking diagram of treatments based on traits in the years of experimentation, T1W1, T2W2 and T1W3 were introduced as the most desirable treatments for cultivating this rice cultivar.
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Affiliation(s)
| | | | - B. Arabzadeh
- Rice Research Institute of Iran Deputy of Mazandaran, Iran
| | | | - T. Ahmadi
- Rice Research Institute of Iran Deputy of Mazandaran, Iran
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Shojaei SH, Mostafavi K, Bihamta M, Omrani A, Bojtor C, Illes A, Szabo A, Vad A, Nagy J, Harsányi E, Mousavi SMN. Selection of maize hybrids based on genotype × yield × trait (GYT) in different environments. BRAZ J BIOL 2023; 84:e272093. [PMID: 37283408 DOI: 10.1590/1519-6984.272093] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2023] [Accepted: 03/16/2023] [Indexed: 06/08/2023] Open
Abstract
This study aimed to identify the best genotypes using the genotype × yield × trait (GYT) method. To investigate the relationships was performed between yield × traits in four regions of Karaj, Birjand, Shiraz and Arak in two cropping years in a randomized complete block design (RCBD) with three replications. The average grain yield in four regions and two years of the experiment was calculated as 5966 kg/ha, and GYT was obtained based on the multiplication of grain yield with different traits. Comparing the average effect of genotype × year in different environments showed that KSC703 and KSC707 hybrids are among the most productive hybrids among the studied genotypes in grain yield. By examining the correlation coefficients between yield × traits in the tested areas, Y × TWG with Y × GW, Y × NRE, Y × NGR and Y × EL, Y × ED with Y × NGR, Y × NRE with Y × GW and the combination of Y × GW with Y × GL had a positive and significant correlation in all regions. The correlation diagrams were drawn on the evaluated areas' data and showed the correlation of most compounds except Y × GT with each other. Based on the analysis of the main components, the first three components explained the greatest diversity in the population. They were named the component ear grain profile, grain thickness component and plant height profile component.
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Affiliation(s)
- S H Shojaei
- Islamic Azad University, Science and Research Branch, Department of Biotechnology and Plant Breeding, Tehran, Iran
| | - K Mostafavi
- Islamic Azad University, Department of Agronomy and Plant Breeding, Karaj, Iran
| | - M Bihamta
- University of Tehran, College of Agriculture & Natural Resources - UCAN, Karaj, Iran
| | - A Omrani
- Ardabil Agricultural and Natural Resources Research and Education Center - AREEO, Crop and Horticultural Science Research Department, Moghan, Iran
| | - C Bojtor
- University of Debrecen, Institute of Land Use, Engineering and Precision Farming Technology, Debrecen, Hungary
| | - A Illes
- University of Debrecen, Institute of Land Use, Engineering and Precision Farming Technology, Debrecen, Hungary
| | - A Szabo
- University of Debrecen, Institute of Land Use, Engineering and Precision Farming Technology, Debrecen, Hungary
| | - A Vad
- University of Debrecen, Institutes for Agricultural Research and Educational Farm - IAREF, Farm and Regional Research Institutes of Debrecen - RID, Experimental Station of Látókép, Debrecen, Hungary
| | - J Nagy
- University of Debrecen, Institute of Land Use, Engineering and Precision Farming Technology, Debrecen, Hungary
| | - E Harsányi
- University of Debrecen, Institute of Land Use, Engineering and Precision Farming Technology, Debrecen, Hungary
| | - S M N Mousavi
- University of Debrecen, Institute of Land Use, Engineering and Precision Farming Technology, Debrecen, Hungary
- Dalhousie University, Faculty of Agriculture, Department of Plant, Food, Environmental Sciences, Truro, Nova Scotia, Canada
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Bojtor C, Mousavi SMN, Illés Á, Golzardi F, Széles A, Szabó A, Nagy J, Marton CL. Nutrient Composition Analysis of Maize Hybrids Affected by Different Nitrogen Fertilisation Systems. PLANTS 2022; 11:plants11121593. [PMID: 35736744 PMCID: PMC9228499 DOI: 10.3390/plants11121593] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/13/2022] [Revised: 06/14/2022] [Accepted: 06/14/2022] [Indexed: 11/16/2022]
Abstract
Maize is one of the most widely used plants in the agricultural industry, and the fields of application of this plant are broad. The experiment was conducted at the Látókép Crop Production Experimental Station of the University of Debrecen, Hungary. Three mid-ripening maize hybrids with different FAO numbers were used in the present study. The effects of different nitrogen supplies were examined as a variable rate of abiotic stress and the interrelationship among the essential nutrients through the nutrient acquisition and partitioning of the different vegetative and generative plant parts. The results showed that NPK application compared to the control treatment (no fertilizer application) increased DM in all tissues of maize, while increasing nitrogen application from 120 to 300 kg ha−1 had no significant effect on this trait. The highest protein content was obtained with the nitrogen application of 120 kg ha−1, and the higher nitrogen fertilizer application had no significant effect on this trait. Seeds and leaves had a maximum zinc and manganese value in terms of nitrogen content (protein). Dry matter was positively correlated with nitrogen, potassium, and manganese content, while the dry matter had a negative correlation with nickel content. In general, to achieve a maximum quantitative and qualitative yield, it is recommended to use NPK fertilizer with a rate of 120 kg ha−1 N for maize cultivation.
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Affiliation(s)
- Csaba Bojtor
- Institute of Land Use, Engineering and Precision Farming Technology, Faculty of Agricultural and Food Sciences and Environmental Management, University of Debrecen, 138 Böszörményi St., H-4032 Debrecen, Hungary; (S.M.N.M.); (Á.I.); (A.S.); (A.S.); (J.N.); (C.L.M.)
- Correspondence:
| | - Seyed Mohammad Nasir Mousavi
- Institute of Land Use, Engineering and Precision Farming Technology, Faculty of Agricultural and Food Sciences and Environmental Management, University of Debrecen, 138 Böszörményi St., H-4032 Debrecen, Hungary; (S.M.N.M.); (Á.I.); (A.S.); (A.S.); (J.N.); (C.L.M.)
| | - Árpád Illés
- Institute of Land Use, Engineering and Precision Farming Technology, Faculty of Agricultural and Food Sciences and Environmental Management, University of Debrecen, 138 Böszörményi St., H-4032 Debrecen, Hungary; (S.M.N.M.); (Á.I.); (A.S.); (A.S.); (J.N.); (C.L.M.)
| | - Farid Golzardi
- Seed and Plant Improvement Institute, Agricultural Research, Education and Extension Organization (AREEO), Karaj P.O. Box 31585-4119, Iran;
| | - Adrienn Széles
- Institute of Land Use, Engineering and Precision Farming Technology, Faculty of Agricultural and Food Sciences and Environmental Management, University of Debrecen, 138 Böszörményi St., H-4032 Debrecen, Hungary; (S.M.N.M.); (Á.I.); (A.S.); (A.S.); (J.N.); (C.L.M.)
| | - Atala Szabó
- Institute of Land Use, Engineering and Precision Farming Technology, Faculty of Agricultural and Food Sciences and Environmental Management, University of Debrecen, 138 Böszörményi St., H-4032 Debrecen, Hungary; (S.M.N.M.); (Á.I.); (A.S.); (A.S.); (J.N.); (C.L.M.)
| | - János Nagy
- Institute of Land Use, Engineering and Precision Farming Technology, Faculty of Agricultural and Food Sciences and Environmental Management, University of Debrecen, 138 Böszörményi St., H-4032 Debrecen, Hungary; (S.M.N.M.); (Á.I.); (A.S.); (A.S.); (J.N.); (C.L.M.)
| | - Csaba L. Marton
- Institute of Land Use, Engineering and Precision Farming Technology, Faculty of Agricultural and Food Sciences and Environmental Management, University of Debrecen, 138 Böszörményi St., H-4032 Debrecen, Hungary; (S.M.N.M.); (Á.I.); (A.S.); (A.S.); (J.N.); (C.L.M.)
- Eötvös Loránd Research Network, Centre for Agricultural Research, Agricultural Institute, 2 Brunszvik St., H-2462 Martonvásár, Hungary
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Szabó A, Mousavi SMN, Bojtor C, Ragán P, Nagy J, Vad A, Illés Á. Analysis of Nutrient-Specific Response of Maize Hybrids in Relation to Leaf Area Index (LAI) and Remote Sensing. PLANTS (BASEL, SWITZERLAND) 2022; 11:1197. [PMID: 35567198 PMCID: PMC9102345 DOI: 10.3390/plants11091197] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 04/13/2022] [Revised: 04/23/2022] [Accepted: 04/26/2022] [Indexed: 06/15/2023]
Abstract
Leaf area index (LAI) indicates the leaf area per ground surface area occupied by a crop. Various methods are used to measure LAI, which is unitless and varies according to species and environmental conditions. This experiment was carried out in three different nitrogen ranges (control, 120 kg N ha-1, and 300 kg N ha-1) + PK nutrient levels, with five replications used for leaf area measurement on seven different maize hybrids. Hybrids had different moisture, protein, oil, and starch contents. N (1, 2) + PK treatments had a desirable effect on protein, starch, and yield. P0217 LAI had a minimal response at these fertiliser levels. LAI for Sushi peaked at different dates between control and fertiliser treatments. This result showed that Sushi has an excellent capacity for LAI. LAI values on 15 June 2020 showed minimum average values for all hybrids, and it had a maximum average values on 23 July 2020. LAI had maximum performance between the average values treatments in Sushi, Armagnac, Loupiac, and DKC4792 on 15 June 2020. This study also provides insights for examining variably applied N doses using crop sensors and UAV remote-sensing platforms.
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Affiliation(s)
- Atala Szabó
- Faculty of Agricultural and Food Sciences and Environmental Management, Institute of Land Use, Engineering and Precision Farming Technology, University of Debrecen, 138 Böszörményi St., H-4032 Debrecen, Hungary; (A.S.); (S.M.N.M.); (P.R.); (J.N.); (Á.I.)
| | - Seyed Mohammad Nasir Mousavi
- Faculty of Agricultural and Food Sciences and Environmental Management, Institute of Land Use, Engineering and Precision Farming Technology, University of Debrecen, 138 Böszörményi St., H-4032 Debrecen, Hungary; (A.S.); (S.M.N.M.); (P.R.); (J.N.); (Á.I.)
| | - Csaba Bojtor
- Faculty of Agricultural and Food Sciences and Environmental Management, Institute of Land Use, Engineering and Precision Farming Technology, University of Debrecen, 138 Böszörményi St., H-4032 Debrecen, Hungary; (A.S.); (S.M.N.M.); (P.R.); (J.N.); (Á.I.)
| | - Péter Ragán
- Faculty of Agricultural and Food Sciences and Environmental Management, Institute of Land Use, Engineering and Precision Farming Technology, University of Debrecen, 138 Böszörményi St., H-4032 Debrecen, Hungary; (A.S.); (S.M.N.M.); (P.R.); (J.N.); (Á.I.)
| | - János Nagy
- Faculty of Agricultural and Food Sciences and Environmental Management, Institute of Land Use, Engineering and Precision Farming Technology, University of Debrecen, 138 Böszörményi St., H-4032 Debrecen, Hungary; (A.S.); (S.M.N.M.); (P.R.); (J.N.); (Á.I.)
| | - Attila Vad
- Institutes for Agricultural Research and Educational Farm (IAREF), Farm and Regional Research Institutes of Debrecen (RID), Experimental Station of Látókép, University of Debrecen, H-4032 Debrecen, Hungary;
| | - Árpád Illés
- Faculty of Agricultural and Food Sciences and Environmental Management, Institute of Land Use, Engineering and Precision Farming Technology, University of Debrecen, 138 Böszörményi St., H-4032 Debrecen, Hungary; (A.S.); (S.M.N.M.); (P.R.); (J.N.); (Á.I.)
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Shojaei SH, Mostafavi K, Omrani A, Illés Á, Bojtor C, Omrani S, Mousavi SMN, Nagy J. Comparison of Maize Genotypes Using Drought-Tolerance Indices and Graphical Analysis under Normal and Humidity Stress Conditions. PLANTS (BASEL, SWITZERLAND) 2022; 11:942. [PMID: 35406921 PMCID: PMC9002667 DOI: 10.3390/plants11070942] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/02/2022] [Revised: 03/21/2022] [Accepted: 03/29/2022] [Indexed: 06/14/2023]
Abstract
This study aimed to identify drought-tolerant genotypes and to evaluate and compare the response of genotypes under normal conditions and humidity stress. The experiment was conducted in a Randomized Complete Block Design (RCBD) on 12 commercial single cross hybrids of maize (Zea mays L.) with three replications in two separate experiments under normal and stress conditions. GT biplot was used to compare genotypes under normal conditions and humidity stress. Based on the polygon diagrams' graphical analysis, KSC206, KSC704, KSC705 and KSC706 genotypes were identified as desirable hybrids. The ranking diagram of genotypes based on ideal genotype also showed that the KSC704 genotype had high desirability in all evaluated traits in normal and stress conditions. TOL, MP, HARM, GMP, SSI and STI indices were used to identify drought-tolerant genotypes, and the genotypes were ranked based on this index. Based on this, KSC260, SC302 and KSC400 hybrids were selected as resistant hybrids. Based on the correlation analysis between drought-tolerance indices, a positive correlation was observed between MP, GMP, HARM and STI indices. Based on the analysis of the PCA on the indices, the first and second principal components were given the titles of grain yield tolerance component under humidity stress conditions and grain yield stability component under normal humidity conditions, respectively. KSC704 was superior to other hybrids in terms of grain yield under normal conditions and stress, and the KSC260 hybrid was identified as a tolerant hybrid in terms of all studied traits under drought stress.
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Affiliation(s)
- Seyed Habib Shojaei
- Department of Biotechnology and Plant Breeding, Science and Research Branch, Islamic Azad University, Tehran 1477893855, Iran;
| | - Khodadad Mostafavi
- Department of Agronomy and Plant Breeding, Karaj Branch, Islamic Azad University, Karaj 3149968111, Iran;
| | - Ali Omrani
- Crop and Horticultural Science Research Department, Ardabil Agricultural and Natural Resources Research and Education Center, AREEO, Moghan 193951113, Iran;
| | - Árpád Illés
- Institute of Land Use, Engineering and Precision Farming Technology, Faculty of Agricultural and Food Sciences and Environmental Management, University of Debrecen, 138 Böszörményi St., 4032 Debrecen, Hungary; (Á.I.); (C.B.); (J.N.)
| | - Csaba Bojtor
- Institute of Land Use, Engineering and Precision Farming Technology, Faculty of Agricultural and Food Sciences and Environmental Management, University of Debrecen, 138 Böszörményi St., 4032 Debrecen, Hungary; (Á.I.); (C.B.); (J.N.)
| | - Saeed Omrani
- Plant Breeding and Genetics, Department of Agronomy and Plant Breeding, Isfahan University of Technology, Isfahan 84156-83111, Iran;
| | - Seyed Mohammad Nasir Mousavi
- Institute of Land Use, Engineering and Precision Farming Technology, Faculty of Agricultural and Food Sciences and Environmental Management, University of Debrecen, 138 Böszörményi St., 4032 Debrecen, Hungary; (Á.I.); (C.B.); (J.N.)
| | - János Nagy
- Institute of Land Use, Engineering and Precision Farming Technology, Faculty of Agricultural and Food Sciences and Environmental Management, University of Debrecen, 138 Böszörményi St., 4032 Debrecen, Hungary; (Á.I.); (C.B.); (J.N.)
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Abstract
This study was conducted to investigate the response of maize hybrids to drought stress and to select the most drought-tolerant cultivar compared to other hybrids. The experiment was performed on six maize hybrids in a randomized complete block design (RCBD) with three replications under regular irrigation and limited irrigation in the vegetative and reproductive stages in Iran. Drought tolerance indices (TOL, MP, GMP, STI, SSI, and HAR) for the grain yield of genotypes were calculated, and principal component analysis was based on them. The results obtained from estimating the indices showed that the SC647 and KSC704 hybrids, while having good performance in both conditions, also have drought tolerance. Examining the correlation between drought tolerance indices and yield in both conditions, among the indices used to detect drought tolerance, STI, MP, and GMP indices can be considered suitable for selecting high-yielding hybrids in these conditions. The principal components analysis on the stress-tolerance index showed that MP and GMP indices could be used as the best indices with high coefficients to select stress-tolerance hybrids. SC647 and KSC704 hybrids were identified and selected as hybrids with high tolerance to moisture stress. The results of drought tolerance indices in the emergence stage of the crest showed that the KSC260 hybrid has the lowest level of stress sensitivity. SC647 hybrids showed the lowest susceptibility to drought stress in the ear emergence stage.
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