Combining ability and gene action studies for drought tolerance in tomato
Subject Areas : Stress Physiology
Maryam Noori
1
,
Alireza Motallebi Azar
2
,
Mehdi Saidi
3
,
Ali Akbar Asadi
4
,
Jaber Panahandeh
5
,
Davoud ZareHaghi
6
,
Shahnaz Fathi
7
1 -
2 -
3 -
4 -
5 -
6 -
7 -
Keywords: combing ability, drought stress, gen action, line × tester, peroxidase ,
Abstract :
Physiological traits of tomato including its resistance to stresses are a main breeding goal in producing new cultivars. This study reports on a combining ability analysis investigating the variance of general and specified combing abilities for some important physiological characteristics as a whole as well as their effects for individual parents and hybrids of 19 tomato genotypes of tomato under drought stress. Three commercial innate lines and four analyzers were used in a line-to-tester crossing plan at Ilam University, Iran. There was a significant difference between genotypes (parents and crosses) in all characteristics at three levels of stress. Evaluating the impacts of common combining capacity analyzers and lines showed that neither a single line nor an analyzer was a commendable common combiner for all of the characteristics examined at all three push levels. Estimation of the effects of specific combining ability indicated that for each specific physiological trait, a specific hybrid showed the highest effect at all three stress levels. In all of the traits under study, specific combining ability variance had a higher estimation than general combining ability variance, and the genetic variance ratio of additive variance to non-additive variance was smaller than one, indicating that non-additive gene action predominated in the inheritance of all of the characteristics in the three levels of stress. The degree of dominance under three levels of stress was higher than one for all attributes except total soluble solids, and it seems that dominance in the genetic locations controlling these traits is superseded.
Abbasi, Z., A. Arzani., M.M. Majidi., A. Rajabi., and A. Jalali. 2019. 'Genetic analysis of sugar yield and physiological traits in sugar beet under salinity stress conditions'. Euphytica, 215: 1-12.
Aghighi Shahverdi, M., H. Omidi., and S.J. Tabatabaei. 2017. 'Effect of nutri-priming on germination indices and physiological characteristics of stevia seedling under salinity stress'. Journal of Seed Science, 39: 353-362.
Aghighi Shahverdi, M., H. Omidi., and S.J. Tabatabaei. 2018. 'Plant growth and steviol glycosides as affected by foliar application of selenium, boron, and iron under NaCl stress in Stevia rebaudiana Bertoni'. Industrial Crops and Products, 125: 408-415.
Alijani, A.M., J. Daneshian., S. Sayfzadeh., H. Madani., and A.H. Shirani Rad. 2022. 'Effect of microelements on some physiological traits and yield of soybean (Glycine max L.) under water deficit stress conditions'. Iranian Journal of Plant Physiology, 12: 4089-4098.
Anoshee, M., and M. Farzami Sepehr. 2016. 'The effect of salinity pretreatment of Glomus mosseae on induction of salinity tolerance in Lycopersicum esculentum L'. Iranian Journal of Plant Physiology, 6: 1815-1824.
Azarnia, M., A. Biabani., E.G. Alamdari., and H. Eisvand. 2020. 'Effects of seed priming with gibberellic, salicylic acids and mycorrhizal inoculation on lentil (Lens culinaris L.) yield and its components'. Legume Research-An International Journal, 43: 518-523.
Asadi, N.N., P. Hassibi., H. Roshanfekr., and M. Meskarbashi. 2013. 'Study some physiological and morphological responses of three sugar beet (Beta vulgaris L.) cultivars to salinity stress'. Journal of Crops Improvement, 15: 79-94.
Bates, L.S., R.P. Waldren., and I. Teare. 1973. 'Rapid determination of free proline for water-stress studies'. Plant and Soil, 39: 205-207.
Bouras, H., A. Bouaziz., B. Bouazzama., A. Hirich., and R. Choukr-Allah. 2021. 'How phosphorus fertilization alleviates the effect of salinity on sugar beet (Beta vulgaris L.) productivity and quality'. Agronomy, 11: 1491.
Choudhary, S., K.I. Wani., M. Naeem., M. Khan., and T. Aftab. 2022. 'Cellular Responses, Osmotic adjustments, and role of osmolytes in providing salt stress resilience in higher plants: polyamines and nitric oxide crosstalk'. Journal of Plant Growth Regulation: 1-15.
Efisue, A.A., and C.C. Dike. 2020. 'Screening Rice (Oryza sativa L.) for salinity tolerance for yield and yield components in saline stressed environment'. American Journal of Agriculture and Forestry, 8: 15-21.
FAO. 2019. Statistical yearbook. https://www.fao.org
Farooq, M., Atique-ur-Rehman., T. Aziz., and M. Habib. 2011. 'Boron nutripriming improves the germination and early seedling growth of rice (Oryza sativa L.)'. Journal of Plant Nutrition, 34: 1507-1515.
Farzami Sepehr, M., S. Salehi., and M. Kaveh. 2022. 'Effect of blue and white lights on physiological characteristics of two wheat cultivars under salinity stress'. Iranian Journal of Plant Physiology, 12: 4195-4204.
Gholamzadeh Alam, A., S. Mousavi-Fard., and A. Rezaei Nejad. 2022. 'Morphological and physiological characteristics for evaluation of salicylic acid effects on Celosia argentea L. under salinity stress'. Iranian Journal of Plant Physiology, 12: 4027-4037.
Gohari, G., S. Panahirad., M. Sadeghi, A. Akbari., E. Zareei., S.M. Zahedi, M.K. Bahrami., and V. Fotopoulos. 2021. 'Putrescine-functionalized carbon quantum dot (put-CQD) nanoparticles effectively prime grapevine (Vitis vinifera cv.‘Sultana’) against salt stress'. BMC Plant Biology, 21: 1-15
Heath, R.L., and L. Packer. 1968. 'Photoperoxidation in isolated chloroplasts: I. Kinetics and stoichiometry of fatty acid peroxidation'. Archives of Biochemistry and Biophysics, 125: 189-198.
Huang, Y., Z. Bie., Z. Liu., A. Zhen., and W. Wang. 2009. 'Protective role of proline against salt stress is partially related to the improvement of water status and peroxidase enzyme activity in cucumber'. Soil Science and Plant Nutrition, 55: 698-704.
Kandil, E.E., N.R. Abdelsalam., A.A.A. EL Aziz., H.M. Ali., and M.H. Siddiqui. 2020. 'Efficacy of nanofertilizer, fulvic acid and boron fertilizer on sugar beet (Beta vulgaris L.) yield and quality'. Sugar Tech, 22: 782-791
Katerji, N., J. Van Hoorn., A. Hamdy., M. Mastrorilli., and E.M. Karzel. 1997. 'Osmotic adjustment of sugar beets in response to salty soil and its influence on stomatal conductance, growth and yield'. Agricultural Water Management, 34: 57-69.
Khorshid, A., A. Rajabi., I. Bernousi., and A. Fayaz Moghadam. 2020. 'Evaluation of salinity tolerance of sugar beet breeding populations and hybrids under greenhouse and field conditions'. Journal of Sugar beet, 35: 141-156.
Khorshid, A., F. Moghadam., I. Bernousi., S. Khayamim., and A. Rajabi. 2018. 'Comparison of some physiological responces to salinity and normal conditions in Sugar Beet'. Indian Journal of Agricultural Research, 52:15-22.
Lichtenthaler, H.K., and C. Buschmann. 2001. 'Chlorophylls and carotenoids: Measurement and characterization by UV‐VIS spectroscopy'. Current Protocols in Food Analytical Chemistry, 1: F4. 3.1-F4. 3.8.
Lv, X., S. Chen., and Y. Wang. 2019. 'Advances in understanding the physiological and molecular responses of sugar beet to salt stress'. Frontiers in Plant Science, 10: 1431.
Mahmood, A., H. Kanwal., A. Kausar., A. Ilyas., N. Akhter., M. Ilyas., Z. Nisa., and H. Khalid. 2019. 'Seed priming with zinc modulate growth, pigments and yield of chickpea (Cicer arietinum L.) under water deficit conditions'. Applied Ecology and Environmental Research, 17: 147-160.
Mirshekari, B. 2012. 'Seed priming with iron and boron enhances germination and yield of dill (Anethum graveolens)'. Turkish Journal of Agriculture and Forestry, 36: 27-33.
Mohamed, N.A., M.F. Saad., M. Shukry., A.M. El-Keredy., O. Nasif., H. Van Doan., and M.A. Dawood. 2021. 'Physiological and ion changes of Nile tilapia (Oreochromis niloticus) under the effect of salinity stress'. Aquaculture Reports, 19: 100567.
Moreno, C., C. Seal., and J. Papenbrock. 2018. 'Seed priming improves germination in saline conditions for Chenopodium quinoa and Amaranthus caudatus'. Journal of Agronomy and Crop Science, 204: 40-48.
Nejati, M., A. Alipour., M. Yousefirad., Y. Sharghi., and H. Zahedi. 2020. 'Effects of seed germination with gibberellin on safflower germination under salinity stress'. Iranian Journal of Plant Physiology, 11: 3443-3448.
Pakbaz, N., H. Omidi., H. Naghdi Badi., and A. Bostani. 2022. 'Foliar application of iron and zinc on quinoa under drought stress affects its seeds germination and biochemical properties'. Iranian Journal of Plant Physiology, 12: 4153-4168.
Pakniyat, H., and M. Armion. 2007. 'Sodium and proline accumulation as osmoregulators in tolerance of sugar beet cultivars to salinity'. Pakestan Journal of Biological Science, 10: 4081-4086.
Pavia, I., J. Roque., L. Rocha., H. Ferreira., C. Castro., A. Carvalho., E. Silva., C. Brito., A. Gonçalves., and J. Lima-Brito. 2019. 'Zinc priming and foliar application enhances photoprotection mechanisms in drought-stressed wheat plants during anthesis'. Plant Physiology and Biochemistry, 140: 27-42.
Peykani, L.S., and M.F. Sepehr. 2018. 'Effect of chitosan on antioxidant enzyme activity, proline, and malondialdehyde content in Triticum aestivum L. and Zea maize L. under salt stress condition'. Iranian Journal of Plant Physiology, 9: 2661-2670.
Poudineh, Z., Z.G. Moghadam., and S. Mirshekari. 2015. Effects of humic acid and folic acid on sunflower under drought stress. In Biological Forum, 451. Research Trend.
Rehman, A., M. Farooq., M. Naveed., A. Nawaz., and B. Shahzad. 2018. 'Seed priming of Zn with endophytic bacteria improves the productivity and grain biofortification of bread wheat'. European Journal of Agronomy, 94: 98-107.
Shahid, M.A., A. Sarkhosh., N. Khan., R.M. Balal., S. Ali., L. Rossi., C. Gómez., N. Mattson., W. Nasim., and F. Garcia-Sanchez. 2020. 'Insights into the physiological and biochemical impacts of salt stress on plant growth and development'. Agronomy, 10: 938.
Shahverdi, M.A., H. Omidi., and C.A. Damalas. 2020. 'Foliar fertilization with micronutrients improves Stevia rebaudiana tolerance to salinity stress by improving root characteristics'. Brazilian Journal of Botany, 43: 55-65.
Shahverdi, M.A., H. Omidi., and S.J. Tabatabaei. 2019. 'Stevia (Stevia rebaudiana Bertoni) responses to NaCl stress: Growth, photosynthetic pigments, diterpene glycosides and ion content in root and shoot'. Journal of the Saudi Society of Agricultural Sciences, 18: 355-360.
Shokohian, A., and H. Omidi. 2021. 'Sugar beet (Beta vulgaris L.) germination indices and physiological properties affected by priming and genotype under salinity stress'. Notulae Botanicae Horti Agrobotanici Cluj-Napoca, 49(3): 12063
Skorupa, M., M. Gołębiewski., K. Kurnik., J. Niedojadło., J. Kęsy., K. Klamkowski., K. Wójcik., W. Treder., A. Tretyn., and J. Tyburski. 2019. 'Salt stress vs. salt shock-the case of sugar beet and its halophytic ancestor'. BMC Plant Biology, 19: 57.
Subramanyam, K., G. Du Laing., and E.J. Van Damme. 2019. 'Sodium selenate treatment using a combination of seed priming and foliar spray alleviates salinity stress in rice'. Frontiers in Plant Science, 10: 116.
Tounekti, T., M. Mahdhi., A.F. Zarraq., and H. Khemira. 2020. 'Priming improves germination and seed reserve utilization, growth, antioxidant responses and membrane stability at early seedling stage of Saudi sorghum varieties under drought stress'. Notulae Botanicae Horti Agrobotanici Cluj-Napoca, 48: 938-953.
Wu, G.Q., N. Liang., R.J. Feng., and J.J. Zhang. 2013. 'Evaluation of salinity tolerance in seedlings of sugar beet (Beta vulgaris L.) cultivars using proline, soluble sugars and cation accumulation criteria'. Acta Physiologiae Plantarum, 35: 2665-2674.
Yousif, B.S., L.Y. Liu., N.T. Nguyen., Y. Masaoka., and H. Saneoka. 2010. 'Comparative studies in salinity tolerance between New Zealand spinach (Tetragonia tetragonioides) and chard (Beta vulgaris) to salt stress'. Agricultural Journal, 5: 19-24.
Yu, D. 2019. 'Investigating membrane lipid responses of barley (Hordeum vulgare L.) roots under salt stress', The University of Melbourne.
1405
Combining ability and gene action studies for drought tolerance in tomato
1. Department of Horticulture, Faculty of Agriculture, University of Tabriz, Iran
2. Department of Horticulture, Faculty of Agriculture, University of Ilam, Iran
3. Department of Crop and Horticultural Science Research, Zanjan Agriculture and Natural Resources Research and Educational Center (AREOO), Zanjan, Iran
4. Department of Soil Science, Faculty of Agriculture, University of Tabriz, Iran
5. Shahid Bakeri High Education Center of Miandoab, Urmia University, Urmia, Iran
________________________________________________________________________________
Abstract
Physiological traits of tomato including its resistance to stresses are a main breeding goal in producing new cultivars. This study reports on a combining ability analysis investigating the variance of general and specified combing abilities for some important physiological characteristics as a whole as well as their effects for individual parents and hybrids of 19 tomato genotypes of tomato under drought stress. Three commercial innate lines and four analyzers were used in a line-to-tester crossing plan at Ilam University, Iran. There was a significant difference between genotypes (parents and crosses) in all characteristics at three levels of stress. Evaluating the impacts of common combining capacity analyzers and lines showed that neither a single line nor an analyzer was a commendable common combiner for all of the characteristics examined at all three push levels. Estimation of the effects of specific combining ability indicated that for each specific physiological trait, a specific hybrid showed the highest effect at all three stress levels. In all of the traits under study, specific combining ability variance had a higher estimation than general combining ability variance, and the genetic variance ratio of additive variance to non-additive variance was smaller than one, indicating that non-additive gene action predominated in the inheritance of all of the characteristics in the three levels of stress. The degree of dominance under three levels of stress was higher than one for all attributes except total soluble solids, and it seems that dominance in the genetic locations controlling these traits is superseded.
Keywords: combing ability, drought stress, gen action, line × tester, peroxidase
Noori, M., A. Motallebi Azar, M. Saidi, A. A. Asadi, J. Panahandeh, D. Zare Haghi and Sh. Fathi. 2024. 'Combining ability and gene action studies for drought tolerance in tomato'. Iranian Journal of Plant Physiology 14(1), 4865- 4878.
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____________________________________ * Corresponding Author E-mail Address: Sh.fathi@urmia.ac.ir Received: January, 2023 Accepted: March, 2023
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Genotypes' combining abilities indicate how well they combine with a given genotype to produce populations with potential and productivity. The idea of general (GCA) and specific combining ability (SCA) aids the breeder in selecting the parents for hybridization, isolating promising genotypes from the segregating population, and gaining knowledge of gene action, which helps to understand the principles of plant trait inheritance (Sprague and Tatum, 1942). Kempthorne's (1957) Line × Tester mating design aids breeders by providing details on the combining ability status of the genotypes (parents) used and the kind of gene action involved. The estimation of GCA and SCA variations as well as their impacts have been considerably used in this design. Moreover, it is employed to comprehend the type of gene action responsible for the expression of economically significant quantitative characters.
Owing to various benefits of hybrids over pure line varieties in response to commercial yields of fruits and their different characteristics, the commercial exploitation of hybrid vigor in tomatoes has gained more importance. For the exploitation of heterosis, the choice of parents is of paramount importance (Mukri et al., 2020). Kumar et al. (2013) investigated a line × tester analysis in tomato using 10 lines and three testers. They discovered that all fruit quality traits, for example ascorbic acid, lycopene (LYC), titrable acidity (TA), and total soluble solids (TSS) were controlled by non-additive gene action. Over-dominance was prevalent in the majority of the traits. Arora et al. (2022) reported the importance of additive and non-additive gene action in a line (8) × tester (32) analysis, with the non-additive gene action predominating for fruit weight and ascorbic acid content. Reddy et al. (2020) found that titrable acidity and ascorbic acid had predominant non-additive genetic variance. According to Mondal et al. (2009), non-additive gene action governs features of fruit quality like total soluble solids and lycopene content. Katkaret al. (2012) investigated 57 F1 hybrids and discovered that the estimated variance of GCA and SCA, as well as their ratio, indicated a predominance of non-additive gene action for total soluble solids and ascorbic acid. Mondal et al. (2009) discovered that both the additive and dominance components were highly significant, implying that both additive and dominance gene action are important for the conditioning of lycopene, total soluble solids, and β-carotene in tomato.
Material and Method
The research was carried out at Illam University's Experimental Research Farm between 2017 and 2018. A total of 19 tomato genotypes, including three inbred lines (Bitstoik, Kingston, and Peto early), given by the Seed and four testers [LA2080 (S. lycopersicum var. cerasiforme), LA2656 (S. pimpinellifolium), LA1607 (S. pimpinellifolium), and LA1579 (S. pimpinellifolium)] were used. Initially, parental seeds were planted in the chassis. Then, the seedlings with 2-4 leaves were transferred to pots (23 x 20 cm) containing a mixture of 1:1:1 garden topsoil, leaf mold, and fine sand at the stage of 2-4 leaves. At the beginning of the flowering period, the cross between the lines and desired testers was carried out, and the seeds of the F1 generation (hybrid) were obtained. In the second year, obtained F1 and parents were evaluated at three levels of drought stress. The three drought stress levels were 100 percent field capacity (FC) (S1: control), 40% FC (S2: mild stress), and 60% FC (S3: severe stress). At each stress level, a randomized complete block design with 3 replications was used. Seeds from parents and hybrids were grown in plastic pots for two months before being transplanted to the field plot at 75 × 30 cm spacing. Water stress treatments were applied after the entire plant had been deployed in the field. Irrigation treatments are carried out in accordance with field capacity. Drought relief was maintained until the harvest. The crop was grown in accordance with the area's standard cultural recommendations. Water stress treatments were applied after the complete plant deployment in the field. Irrigation treatments were carried out according to the capacity of the farm. Drought stress treatment was carried out until harvest.
Proline measurement
Proline was determined using the reaction of proline with ninhydrin, as described by Bates et al. (1973). One gram of fresh leaves was powdered in three ml of sulfosalicylic acid 3%. The homogenized components were centrifuged and the supernatant was transferred to the tube, and 2 ml of ninhydrin and 2 ml of glacial acetic acid were added to it. The supernatant was moved to a tube, and glacial acetic acid and ninhydrin were added to it. Then, the tubes were closed before being placed in a 100 ℃ hot water bath. After the contents of the tubes were cooled, 4 ml of toluene were added to each tube which were shaken for 20 seconds. Finally, the red supernatant phase containing proline in toluene was separated and measured at 520 nm in a spectrophotometer alongside standard specimens. A standard curve was used to calculate the concentration of proline in milligrams per gram fresh leaf tissue.
PH measurement
The PH of extracts was determined with a pH meter after the extraction and filtration of extracts (a mix of 3 fruit extracts for each experimental unit).
Relative water content
These measurements were taken using a method previously described by Korkmaz et al. (2010).
Measurements of Chlorophylls
The chlorophyll (Chl) content of young and fully developed leaves was determined using fresh samples (0.1 g). The samples were centrifuged with 5 milliliters of acetone (80% v/v) after being homogenized with 5 milliliters of the solvent. Absorbance was measured at wavelengths of 663 and 645 nm, and chlorophyll content was measured using the Strain and Svec (1966) equations.
Measurements of malondialdehyde (MDA)
The TBA reaction, described by Heath and Packer (1968) was used with a few modifications to determine the lipid peroxidation index as well as the content of malondialdehyde. In this approach, 0.25 g of fresh leaf was rinsed in 5 ml of trichloroacetic acid (0.1) before being centrifuged at 10,000 rpm for 5 minutes. One ml of the upper solution was combined with 4 ml of 20% trichloroacetic acid containing 0.5 g of thiobarbituric acid, then kept on ice for 30 minutes in a 95 ℃ water bath. The supernatant was then utilized to determine MDA content spectrophotometrically. The absorbance at 532 nm was calculated by subtracting it from the absorbance at 600 nm. Lastly, the quantity of malondialdehyde was estimated using the equation below.
malondialdehyde (nmol/g Fresh Weight) = [(532 nm-600 nm) / (cuvette path length × quenching factor)] × (Dilution Factor).
Measurement of catalase
To calculate catalase enzyme activity, leaf protein was first extracted. After protein extraction, 4.51 µl of 30% hydrogen peroxide and 3 mL of 50 µl enzyme crude extract buffer (pH = 7) were mixed in an ice bath. The curve absorbance at 240 nm wavelength was obtained after two minutes, and the results were displayed based on the μmol (H2O2)/mg protein (Aebi, 1984).
Peroxidase measurement
The method of measuring this enzyme is similar to that of catalase, but with the following differences. The extraction buffer for this enzyme contained 35.3 µl of guaiacol in a 50 mM phosphate buffer. Also, the spectrophotometer absorption wavelength was set to 470 nm. 3), and the time required to stabilize the enzyme reactions was 2 minutes.
Ascorbate peroxidase activity measurement
Ascorbate peroxidase activity was measured using Chance and Maehly (1995). The reaction composition included 4.51 µl H2O2 (30%), 100 µl sodium ascorbate, 50 µl crude enzyme extract, and 1050 mM phosphate buffer (pH = 7). After the addition of hydrogen peroxide, 290 nm was used as the wavelength for measuring absorbance in 1 minute, and the data was reported as μmol H2O2/mg protein.
Soluble solid concentration measurement
Soluble solids concentration (TSS) was measured using an ATC-1E refractometer at 20±1 ℃. Initially, the refractometer was calibrated using double distilled-water, and the findings were stated as %TSS.
Titrable acidity measurement
Titrable acidity was measured using the titration method where 2.5 mL of tomato juice was mixed with 47.5 mL of distilled water and just a few drops of phenolphthalein before being titrated with 0.1 N NaOH to pH 8.2. Titrable acidity was determined by the amount of citric acid (the dominant acid in tomatoes) per 100 grams of fresh weight (Ayala-Zavala et al., 2004).
Flavonoid measurements
A sample of 0.1 g of freshly harvested tomato fruit tissue was extracted in a tube with 10 ml of acidified ethanol [ethanol: glacial acetic acid (99:1 v/v)]. Before being brought up to volume, the samples were gently cooked in an 80 ℃ water bath for 10 minutes. Testing for absorbance was done using a spectrophotometer at three different wavelengths: 270, 300, and 330 nm (Krizeket et al., 1998).
Anthocyanin measurements
To evaluate the anthocyanin content, 0.1 g of fresh tomato fruit tissue was taken and placed in a tube containing 10 ml of acidified methanol (methanol HCl, 99:1, v/v) and stored overnight at 85 ℃ in the dark. The homogenate was centrifuged at 4000 g for 30 minutes and the absorbance was measured at 550 nm (Wanger, 1979).
Lycopene measurements
Lycopene content was extracted using a solvent mixture of hexane, acetone, and ethanol (2:1:1, V/V/V). Fresh tomato fruit tissue (2.5 g) was weighed, then 4 ml of distilled water was added, stirred for 60 seconds, and then it was mixed with 50 ml of the desired extraction solvent. Following that, the solution was divided into separate phases of polar and non-polar sections. A yellow-colored layer containing lycopene was removed and diluted 100 times with hexane before the sample's absorbance was measured at 502 nm (Olives Barba et al., 2006).
Ascorbic acid measurement
Titration with iodine and potassium iodide was used to measure ascorbic acid (vitamin C) (Majedi, 1994). To extract vitamin C, 10 grams of tomato pulp were homogenized for 2 minutes with a tissue homogenizer in 50 ml of the solution obtained by dissolving 30 grams of metaphosphoric acid in one liter of acetic acid. The mixture was centrifuged at 40,000 rpm at 4 ℃ for 15 minutes after the solution was filtered through organza fabric. The aqueous phase was put into a high-performance liquid chromatography system after filtering with a 22 µm membrane. With an acetonitrile-potassium phosphate mobile phase with a flow rate of 1.5 ml/min, vitamin C was separated in a water-NH2 Bondapak column. The amount of vitamin C was calculated by estimating the area under the reaction peak using a standard vitamin C solution with a known concentration. The data were reported in mg of vitamin C per 100 g fresh fruit weight (Gonzalez-Aguilar et al., 2004).
Electrolyte leakage assay
Electrolyte leakage was calculated using a method previously described by Korkmaz et al. (2010).
Data Analysis
The SAS (Version 6.12) program was used to analyze the data. Kempthrone's line × tester analysis was used to conduct combining ability studies (1957).
Results
Table 1 Mean square from the analysis of variance for flavonoid, lycopene, ascorbic acid, and relative water content in tomato under three levels of stress
S1: control (100% FC), S2: mild stress (40% of FC), and S3: severe stress (60% of FC); ** and *: significant at P≤0.01 and P≤0.05, respectively. Table 2 Mean square from the analysis of variance for soluble solids concentration %, pH, peroxidase, and electrolyte leakage % in tomato under three levels of stresses
S1: control (100% FC), S2: mild stress (40% of FC), and S3: severe stress (60% of FC); ** and *: Significant at P≤0.01 and P≤0.05, respectively. Table 3 Mean square from the analysis of variance for malondialdehyde, ascorbate peroxidase, and anthocyanin in tomato under three levels of stress
S1: control (100% FC), S2: mild stress (40% of FC), and S3: severe stress (60% of FC); ** and *: Significant at P≤0.01 and P≤0.05, respectively. |
Table 4 Mean square from the analysis of variance for proline, catalase, and titrable acidity %, in tomato under three levels of stress
Table 5 Mean square from the analysis of variance for chlorophyll t, chlorophyll a, and chlorophyll b in tomato under three levels of stress
Table 6 Estimate of general combining ability effects of parents for flavonoid, lycopene, ascorbic acid, and relative water content in tomatoes under three levels of stress
S1: control (100% FC), S2: mild stress (40% of FC), and S3: severe stress (60% of FC); ** and *: Significant at P≤0.01 and P≤0.05, respectively.
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Table 7 Estimate of general combining ability effects of parents for soluble solids concentration %, peroxidase, and electrolyte leakage % in tomatoes under three levels of stresses.
S1: control (100% FC), S2: mild stress (40% of FC), and S3: severe stress (60% of FC); ** and *: Significant at P≤0.01 and P≤0.05, respectively.
Table 8 Estimate of general combining ability effects of parents for malondialdehyde, ascorbate peroxidase, anthocyanin, and titrable acidity % in tomatoes under three levels of stress
S1: control (100% FC), S2: mild stress (40% of FC), and S3: severe stress (60% of FC); ** and *: Significant at P≤0.01 and P≤0.05, respectively.
Table 9 Estimate of general combining ability effects of parents for proline, catalase, and pH in tomatoes under three levels of stress
S1: control (100% FC), S2: mild stress (40% of FC), and S3: severe stress (60% of FC); ** and *: Significant at P≤0.01 and P≤0.05, respectively.
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Table 10 Estimate of specific combining ability (SCA) effects of hybrids for agronomic characters in tomatoes under three levels of stress
Table 11 Estimate of specific combining ability effects of hybrids for agronomic characters in tomatoes under three levels of stress
S1: control (100% FC), S2: mild stress (40% of FC), and S3: severe stress (60% of FC); ** and *: Significant at P≤0.01 and P≤0.05, respectively.
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Table 12 Estimate of specific combining ability effects of hybrids for malondialdehyde, ascorbate peroxidase, anthocyanin, and titrable acidity % in tomatoes under three levels of stress
S1: control (100% FC), S2: mild stress (40% of FC), and S3: severe stress (60% of FC); ** and *: Significant at P≤0.01 and P≤0.05, respectively.
Table 13 Estimate of specific combining ability effects of hybrids for proline, catalase, and pH in tomatoes under three levels of stress
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Table 14 Estimate of specific combining ability effects of hybrids for chlorophyl t, Chlorophyl a, and Chlorophyl b in tomatoes under three levels of stress
S1: control (100% FC), S2: mild stress (40% of FC), and S3: severe stress (60% of FC); ** and *: Significant at P≤0.01 and P≤0.05, respectively.
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The estimations of the effects of parents' general combining ability for all the studied traits are shown in Tables (6-9). No single line or tester was actually an excellent general combiner for each of the tested traits for the three stress levels, according to estimated lines and testers general combining ability effects, showing variances in genetic variability between parents for various traits (Arora et al., 2022; Nc et al., 2020).
The general combining ability rate in some traits such as the RWC varied with changes in stress conditions, which can be attributed to the effects of various levels of stress. As a result, no specific genotype for this trait can be proposed at all levels of stress.
Results revealed that for FLA LA2656 and LA2080, for LYC LA1579, Kingston, and Petoearly, for ASA LA1607, LA2080, LA1579, LA2656, and Kingston, for RWC Petoearly, for TSS LA1607, for PROX Petoearly, for EL LA2080, LA1579, and Petoearly, for MDA LA2656 and Petoearly, for TA LA1607 and LA2656, for PR LA2080 and Petoearly, for CAT LA1579, for APA LA2080, LA1579 and Petoearly, for CH a LA1607, LA2656, LA1579, and Kingston, for CH b LA1607, Kingston, and Petoearly, and finally for CH T LA1607, LA1579, and Kingston were the highest general combiner since they showed significant positive GCA effects. These genotypes' positive GCA for all studied variables demonstrated that they are useful testers and lines that have indicated the dominance of their hybrids when they were either used as both or one of the parents. Also, these genotypes showed high general combining ability at all three levels, so that they can be considered in breeding programs for these traits.
Specific combing ability
Specific combining ability effects for 17 physiological attributes in 12 hybrids are shown in Tables 10-14. Results revealed that for FLA Kingston×LA1579 and Petoearly × LA2656 hybrids, for LYC Kingston × LA1579hybrid, for ASA Petoearly × LA2656 and Kingston × LA1579 hybrids, for RWC Bitstoik × LA2656, Kingston × LA1607, Kingston × LA1579 and Petoearly × LA2656 hybrids, for TSSKingston × LA1579 hybrid, for PROX Bitstoik × LA1607 hybrid, for EL Bitstoik × LA1607, Bitstoik × LA2080, Bitstoik × LA11579, Kingston × LA2656, Petoearly × LA2656 and Petoearly × LA1579 hybrids,MDA Bitstoik × LA2080, Kingston × LA1607, Kingston × LA1579, and Petoearly × LA2656 hybrids, for ANT Bitstoik × LA2656, Kingston × LA2080, Petoearly × LA2656 and Petoearly × LA1579 hybrids, for TA Bitstoik × LA2080 and Petoearly × LA1607 hybrids, for PR Bitstoik×LA2080, Kingston ×LA1607, and Petoearly × LA1579 hybrids, for CAT Bitstoik × LA2080, Kingston × LA1607 and Petoearly × LA1579 hybrids, for APA Bitstoik × LA1607, Kingston × LA2656, Kingston × LA1579 and Petoearly × LA2656 hybrids, for CH a Bitstoik × LA2080, Kingston × LA2656 and Petoearly × LA1607 hybrids, for CH b Bitstoik × LA2080, Bitstoik × LA1579, Kingston × LA1607 and Petoearly × LA2656 hybrids, and finally for CH T Bitstoik × LA2080, Kingston × LA1607, and Petoearly × LA2656 hybrids showed positive SCA effects at three levels of stress while others showed negative SCA.
Gene action and variation
SCA variance had higher estimates than GCA variance, and the ratio of additive variance to non-incremental genetic variance was less than one, which indicated that non-incremental gene function was dominant in the inheritance of all traits at three stress levels. The estimates for SCA variance were higher than those for GCA variance, and the additive variance/non-additive genetic variance ratio was smaller than one, indicating that at three levels of stress, non-additive gene action predominated in the inheritance of all characteristics. On the other hand, in all traits except TSS, the degree of dominance was greater than one. These traits in tomatoes can be improved using hybrid products. Plants must be heterozygous because these properties are governed by non-additive gene action. As a result, modified breeding schemes like biparental mating, triple test mating, or the reselection generation method must be used in the early generations. In all traits and at each stress level, the ratio of additive variance to dominance variance was estimated to be less than one (except for TSS). Results showed that, in all studied physiological traits, dominance variance was more than additive variance, and non-additive effects played a role in controlling all studied characteristics.
Of the total variations observed, i.e., the highest percentage of the line’s participation at three levels of stress was observed in the FLA and ASA, but the highest percentage of tester's participation at three levels of stress was observed in MDA. Also, the highest percentage of line × tester's participation at three levels of stress was observed in LYC, RWC, ANT, TA, PR, CAT, APA, CH a, CH b, and CH T.
Discussion
These days, there is a solid craving for crop breeding to increase yield while also improving quality. A potential approach would be to combine conventional breeding techniques with geometric profiling and interbreeding. The desire to improve nutritional characteristics (enhance flavonoid content and lycopene), extend the shelf life of tomato fruit, and improve its quality drives the conceptual strategy to improve organoleptic characteristics, particularly in tomato breeding. Many breeders have discovered through their experience with various plants that the achievements of parents alone sometimes cannot be a real index of their ability in hybrid combos. The situation for genotypes' combining ability demonstrates well how they combine with a given genome to generate survivable and productive population numbers. The breeding program can choose parents for hybridization and isolate prospective genotypes from the separate population with the support of GCA and SCA information, which also gives data on gene action that aids in understanding the principles of character inheritance (Begna, 2021).
To identify the best hybrids, estimates of SCA effects are usually used. On the other hand, studies show that SCA effects do not significantly enhance self-pollinated plants (Enang et al., 2015). According to Beyene et al. (2017), breeding plans can make use of crossovers with desirable SCA. Such programs will be more effective if one parent is a great combiner and the other is a poor combiner. It is predicted that they will produce preferred transgressive segregants if the complementary epistatic effect and the additive genetic system in the good combiner function in the same direction to boost desirable genes of interest. The estimation of general combining ability effects aids in identifying superior parents for use in the production of superlative genotypes in separating populations through the concentration of favorable additive gene action. A strong GCA effect is also known as additive gene action or additive × additive effects, which represent the repairable genetic components of variation (Ahamed et al., 2018). Nevertheless, at three levels of stress and with tester parents, the LA1607 showed good general combining ability for five characters, viz., ASA, TA, TSS, CH a, and CH b, at three levels of stress. The next tester was LA2656, which had a significant effect on FLA, ASA, EL, TA, and CH a. In the same way, the tester LA2080 had a significant effect on FLA, ASA, PR, APA, and EL, and finally, LA1607 had a good SCA for LYC, ASA, CAT, APA, EL, and CH a. In line parents, Petoearly, at three levels of stress, had good general combining ability for eight characters, viz., LYC, RWC, MAD, PR, APA, PROX, EL, and CH b. In this study, no hybrid exhibited superior SCA for all traits. These results agree with those for TSS and vitamin C presented by Al-Shammari and Al-Obaiday (2022) and Bharathkumar et al. (2017). Specific combing ability (SCA) variance was higher than general combing ability (GCA) variance, according to NC et al. (2020), showing that non-additive gene activity predominated for plant yields. Nonetheless, the Kingston × LA1579 mating demonstrated good specific combining ability for eight traits: FLA, LYC, ASA, RWC, TSS, MAD, and APA. Petoearly × LA2656 was the other best mating, with a significant effect on FLA, ASA, RWC, EL, MAD, ANT, APA, CH b, and CH T. In the same way, the cross Bitstoik × LA1579 has a significant effect on EL, MAD, TA, PR, CAT, CH a, CH b, and CH T. Finally, the cross Kingston × LA1607 showed good SCA for RWC, MAD, PR, CAT, CH b, and CH T. The remaining hybrids showed a high specific combining ability for one or two specific characters. The results of this study are in alignment with those of previous studies (Gramaje et al., 2020; Amegbor, 2023; Krishna et al., 2021). Overall, these crosses with significant specific combining ability effects were universally related to higher characteristic performance. The larger part of crossovers having solid particular combining capacity impacts have either both guardians or fair one of them being great common combiners for the variable beneath ponder, which recommends non-additive quality activity (Begna, 2021; Abdel-Aty et al., 2023; Sharma et al., 2023). Our results agree with those of Riaz et al. (2022), Al-Shammari (2022), and Sen et al. (2022). According to Istipliler et al. (2015), if the ratio of additive/dominance variance and GCA to SCA variations is lower than one, non-additive effects are responsible for the regulation of characteristics. Differences within genetic effects (additive or non-additive) on traits in different experiments can be due to the used method, the difference in the tested substance, or the use of different indices for the estimation of the gene action. In the current research, specific combining ability variances were found to be higher than general combining ability variances for studied traits at three levels of stress, indicating the predominance of non-additive gene action. SCA is caused by epistasis and dominance, whereas GCA is caused by additive gene function. In the current research, SCA variances were found to be more than GCA variances for studied traits at three levels of stress, indicating the dominance of non-additive gene effects. As a result, hybrid breeding and rearrangement breeding with delayed choice for future generations are suitable for improving many such characteristics.
Acknowledgments
The authors would like to thank Tabriz University for providing the research facilities.
References
Abdel-Aty, M. S., Sorour, F. A., Yehia, W. M. B., Kotb, H. M. K., Abdelghany, A. M., Lamlom, S. F., ... & Abdelsalam, N. R. 2023. Estimating the combining ability and genetic parameters for growth habit, yield, and fiber quality traits in some Egyptian cotton crosses. BMC Plant Biology, 23(1): 1-21.
Aebi, H. 1984. Catalase in vitro. Methods in Enzymology, 105: 121-126.
Ahamed, H. G. M. D., A.S. Khan,M. Kashif, and S. H. Khan. 2018. Genetic analysis of yield and physical traits of spring wheat grain. Journal of the National Science Foundation of Sri Lanka 46(1):23
Al-Shammari, A. M. A., and A. R. Al-Obaiday2022. H. Study of genetic analysis of individual hybrids derived by the half-diallel cross of some Lycopersicon esculantum mill. Revis Bionat, 7 (4): 44.
Amegbor, I. K., A. Van Biljon, N. G. Shargie, A. Tarekegne, and M. T. Labuschagne. 2023. Combining ability estimates for quality and non-quality protein maize inbred lines for grain yield, agronomic, and quality traits. Frontiers in Sustainable Food Systems, 7: 1123224.
Arora, H., S. K. Jindal, and N. Chawla, 2022. Combining ability analysis for yield and quality traits in exotic lines of tomato (Solanum lycopersicum L.). Agricultural Research Journal, 59(3): 394-399.
Ayala-Zavala, J.F., S.Y. Wang, C.Y. Wang and G.A. Gonzalez-Aguilar. 2004. Effect of storage temperatures on antioxidant capacity and aroma compounds in strawberry fruit. LWT - Food Science and Technology, 37: 687-695.
Bates, L.S., R.P. Waldren and I.D. Teare. 1973. Rapid determination of free proline for water stress studies. Plant Soil, 39: 205-207.
Begna, T. 2021. Combining ability and heterosis in plant improvement. Open Journal of Political Science, 6(1): 108-117.
Bharathkumar, M.V., A. T. Sadashiva and R. Punithkumar , 2017. Combining ability, gene action and heritability analysis for early blight resistance, yield and quality traits in tomato (Solanum LycopersicumL.) Journal of Applied and Natural Science, 9(3): 1495-1500.
Bhattarai, U., P. Talukdar, A. Sharma, and R. Das, 2016. Combining ability and gene action studies for heat-tolerance physio-biochemical traits in tomato. Asian Journal of Agricultural Research, 10: 99-106.
Chance, B., and A.C. Maehly. 1955. Assay of catalases and peroxidase. Method of Enzymology, 2: 764–775.
Gonzalez-Aguilar, G.A., M.E. Tiznado-Hernandez, R. Zavaleta-Gatica and M.A. Martınez-Tellez. 2004. Methyl jasmonate treatments reduce chilling injury and activate the defense response of guava fruits. Biochemical and Biophysical Research Communications., 313: 694-701.
Gramaje, L. V., J. D. Caguiat, J. O. S. Enriquez, Q. D. dela Cruz, R. A. Millas, J. E. Carampatana, and D. A. A.Tabanao, 2020. Heterosis and combining ability analysis in CMS hybrid rice. Euphytica, 216: 1-22.
Heath, R.L. and L. Packer. 1968. Photo peroxidation in isolated chloroplasts: I. Kinetics and stoichiometry of fatty acid peroxidation. Archives of Biochemistry and Biophysics, 125: 189-198.
Istipliler, D., E. Ilker, F. A. Ykuttonk, G. Vivi, M. Tosun, 2015. Line × Tester analysis and estimating combining abilities for yield and components in bread wheat. Turkish Journal of Field Crops, 20(1): 72-77.
Katkar, G.D., O. Sridevi, P.M. Salimath, and S. P. Patil, 2012. Combining ability analysis for yield, its contributing characters and fruit quality parameters of exotic tomato (Lycopersicon esculentum Mill.) breeding lines. Electronic Journal of Plant Breeding, 3(3): 908-915.
Kempthrone, O. 1957. An Introduction to Genetic Statistics, John Wiley and Sons. Inc., New York, pp, 458-471.
Korkmaz, A.,Y. Korkmaz, and A. R. Demirkiran ,2010. Enhancing chilling stress tolerance of pepper seedling by exogenous application of 5- aminolevulinic acid. Environmental and Experimental Botany, 67: 495-501.
Krizek, D.T., S. J. Britz, and R. M. Mirecki, 1998. Inhibitory effects of ambient levels of solar UV- and UV-B radiation on growth of cv, New Red Fire Lettuce. Physiologia Plantarum. 103: 1-7.
Kumar, R., K. Srivastava, R. K. Singh and V. Kumar 2013. Heterosis for quality attributes in tomato (Lycopersicon esculentum Mill). VEGETOS, 26(1): 101-106.
Majedi, M. 1994. Chemical Test Procedures of Food Material. Jahad Daneshgahi, University of Tehran, pP: 65.
Mondal, C., S. Sarkar, P. Hazra, 2009. Line × Tester analysis of combining ability in tomato (Lycopersicon esculentum Mill.), Jou. Crop and Weed. 5: 53-57.
Mukri, G., M. S. Patil, B. N. Motagi, J.S. Bhat, C. Singh, S.P. Jeevan Kumar, , ... and J. Simal-Gandara, 2022. Genetic variability, combining ability and molecular diversity-based parental line selection for heterosis breeding in field corn (Zea mays L.). Molecular Biology Reports, 49(6): 4517-4524.
NC, G., G. U., Kulkarni, B. Datta, and R. Shyadambi, 2020. Correlation coefficient studies for fruit yield and its components in tomato (Solanum lycopersicum L.). International Journal of Chemical Studies, 8(4): 2707-2711.
Olives Barba, A.I., M. Címara Hurtado, M.C. Sanchez Mata, V. Fernandez-Ruiz, D. Lopez Saenz, and M. Tejada, 2006. Application of a UV–vis detection-HPLC method for a rapid determination of lycopene and b-carotene in vegetables. Food Chemistry, 95:328-336.
Reddy B.R.,A. K. Singh , A. K. Pal, Y. S. Reddy and G. E. Reddy , 2020. Combining ability and heterosis studies in tomato (Solanum lycopersicum L.) for quality traits and yield. International Journal of Chemical Studies, 8: 2788-2792.
Sen, E. Z. A., M. A. El-Dahan, S. A. Badawy, Y. S. Katta, B. S. Aljuaid, A. M. El-Shehawi,... and A. M. El-Tahan, 2022. Evaluation of genetic behavior of some Egyption Cotton genotypes for tolerance to water stress conditions. Saudi Journal of Biological Sciences, 29(3), 1611-1617.
Sharma, A., R. Yadav, R. Sheoran, D. Kaushik, T. K. Mohanta, K. Sharma,... and P. Kaushik, 2023. Estimation of Heterosis and the Combining Ability Effect for Yield and Its Attributes in Field Pea (Pisum sativum L.) Using PCA and GGE Biplots. Horticulturae, 9(2): 256.
Singh, A.K. and B.S. Asati. 2011. Combining ability and heterosis studies in tomato under bacterial wilt condition. Bangladesh Journal of Agriculture Resarch, 36: 313-318. http://
Strain, H.H. and W. A. Svec, H. R.1966. Extraction, separation and isolation of chlorophylls. Pp. 24- 61, In Varnon L.P., Seely G.R. (Ed.). Chlorophylls, Academic Press, New York
Tilahun, S., H. R. Choi, M. W. Baek, L. H. Cheol, K.W. Kwak , D. S. Park, ... and C. S. Jeong, 2021. Antioxidant properties, γ-aminobutyric acid (GABA) content, and physicochemical characteristics of tomato cultivars. Agronomy, 11(6): 1204.
Wanger, G.J. 1979. Content and vacuole/ extra vacuole distribution of neutral sugars, free amino acids and anthocyanins in protoplast. Plant Physiology, 64: 88-93.
