ORIGINAL_ARTICLE
Non-destructive model to estimate leaf area in Epilobium species
Leaf area (LA) is one of valuable parameters in plant physiological studies. Therefore, the use of a non-destructive, accurate and simple model to estimate LA is very important. This research aimed to develop a non-destructive model to estimate LA accurately in Epilobium species. To estimate LA, leaf length (L) and leaf width (W) of five Epilobium species were determined. Moreover, the actual leaf area, using leaf area meter was measured. Regression analysis of LA versus L, W and LW revealed several models to predict LA in Epilobium species. Out of the models, the best fitted and validated model which is recommended to estimate LA accurately in each species, was quadratic model based on two dimensions (L and W), including the E. algidum (LA = 0.1264 + 0.6562 (L×W) + 0.0366 (L×W)2), E. parviflorum (LA = – 3.144 + 1.323 (L×W) – 0.030 (L×W)2(, E. sp. (LA = 0.4236 + 0.3033 (L×W) + 0.1368 (L×W)2), E. hirsutum (LA= 2.2417 + 0.2202 (L×W) + 0.0029 (L×W)2), and E. frigidum (LA = 0.2119 + 0.4162 (L×W) + 0.1191 (L×W)2), all with R2 ≥ 0.80.
https://breeding.tabrizu.ac.ir/article_13097_c94fdb62febea7750af3029edfe452e4.pdf
2020-12-29
1
12
10.22034/jppb.2020.13097
Epilobium
Leaf Area
Leaf length
Leaf width
Non-destructive
Quadratic regression model
Shima
Abbasi-Karin
abbasi_shima73@yahoo.com
1
Department of Plant Genetics and Breeding, Faculty of Agriculture, Tarbiat Modares University, Tehran, IRAN
AUTHOR
Ghasem
Karimzadeh
karimzadeh_g@modares.ac.ir
2
Department of Plant Genetics and Breeding, Faculty of Agriculture, Tarbiat Modares University (TMU), Tehran, Iran.
LEAD_AUTHOR
Mitra
Mohammadi-Bazargani
mitra_cb@yahoo.com
3
Agriculture Institute, Iranian Research Organization for Science and Technology (IROST), Tehran, Iran.
AUTHOR
Ali
Mokhtassi-Bidgoli
mokhtassi@modares.ac.ir
4
Department of Agronomy, Faculty of Agriculture, Tarbiat Modares University (TMU), Tehran, Iran.
AUTHOR
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41
ORIGINAL_ARTICLE
Priming with L-arginine reduces oxidative damages in Carthamus tinctorius seedlings under the toxic levels of lead
Lead (Pb) stress adversely affects plant nutrient homeostasis and metabolism when present at an elevated concentrations in the surrounding media. In this research, the effects of 1mM Pb(NO3)2 on 14-day-old Carthamus tinctorius seedlings pretreated with arginine (Arg) as nitric oxide (NO) precursor, methylene blue (MB), a nitric oxide scavenger and Nω-nitro-L-Arg-methyl ester (LNAME) and a nitric oxide biosynthetic inhibitor, were investigated in the greenhouse of the Department of Biology, Shahid Bahonar University of Kerman, Iran. Pb exposure caused oxidative stress, reduced root and shoot growth and elevated malondialdehyde (MDA) content of the seedlings. Pb stress also increased the ascorbate peroxidase activity while decreasing the activity of the catalase (CAT) enzyme. Arg pretreatment decreased the harmful effects of Pb stress by increasing the root and shoot length and reducing the MDA content. Additionally, Pb-induced reduction of CAT enzyme activity in roots was reversed by the Arg pretreatment of the plants. In many characteristics which we measured, the effects of Arg pretreatment on alleviation of Pb-induced oxidative stress were reversed by LNAME and methylene blue pretreatments. Therefore, it seems that Arg induces a positive effect through NO production. Data showed that in the presence of Arg, the uptake and translocation of Pb declined and the application of Arg with LNAME or MB reversed these positive effects of Arg. It seems that Arg can alleviate lead toxicity in plants through the prevention of Pb uptake and promoting the direct scavenging of reactive oxygen species or activating antioxidant enzymes. Also, results from the use of LNAME and MB indicated that the positive effect of Arg is probably related to its role in NO production.
https://breeding.tabrizu.ac.ir/article_13098_ef5286caf3a2a126935ec15d8721b227.pdf
2020-12-29
13
26
10.22034/jppb.2020.13098
Antioxidant enzymes
Heavy metals
Methylene blue
Nitric oxide
Safflower
Translocation factor
Fatemeh
Nasibi
nasibi2002@yahoo.com
1
Department of Biology, Shahid Bahonar University of Kerman, Kerman, Iran.
AUTHOR
Mansooreh
Khodashenas
mkhodashenas4@gmail.com
2
Agricultural and Natural Resources Research and Education Center, Kerman, Iran.
LEAD_AUTHOR
Nahid
Nasibi
3
Department of Biotechnology, Institute of Environmental Sciences, Graduate University of Advanced Technology, Kerman, Iran.
AUTHOR
Arasimowicz-Jelonek M, Floryszak-Wieczorek J and Gwozdz EA, 2011. The message of nitric oxide in cadmium challenged plants. Plant Science 181: 612-620.
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54
ORIGINAL_ARTICLE
Combined hydrogen peroxide and nitric oxide priming modulate salt stress tolerance in acclimated and non-acclimated oilseed rape (Brassica napus L.) plants
We examined the combined effects of hydrogen peroxide (H2O2) and nitric oxide (NO) on the responses of oilseed rape(Brassica napus L.) plants to salt stress under acclimated and non-acclimated conditions. The results of the shoot and root dry weight traits together with the measurement of malondialdehyde (MDA) indicated that salt acclimation with a low concentration of NaCl (50 mM) could not alleviate the inhibitory effect of high salinity (200 mM NaCl). Under acclimated conditions, seed priming with H2O2 or NO resulted in effective protection against salt stress, however, maximum amelioration of salt stress was found by the combined treatments of H2O2 + NO. Interestingly, in the salt-exposed non-acclimated plants, only seed priming with H2O2 + NO was effective in improving salt tolerance. Pretreatment with H2O2 + NO tended to limit Na translocation into photosynthetic organs to prevent salt damages. Additionally, a large increase in salicylic acid contentwas correlated with phenylalanine ammonia lyase activation and flavonoid biosynthesis was observed when oilseed rape plants exposed to salinity in the presence of H2O2+NO. Interestingly, in this study, endogenous NO content of H2O2–primed plants exhibited a significant increase under non-saline conditions, indicating that H2O2 influences NO accumulation. In addition, oilseed rape plants primed with H2O2 + NO exhibited lower MDA and H2O2 content, contributing to the better induction of antioxidative enzyme activities. Higher levels of antioxidant enzyme activities maintained the integrity of cell membranes, resulting in better plant growth under salt stress. Taken together, our results revealed that oilseed rape plants pretreated with H2O2 + NO exhibited more effective tolerance to salt stress than plants that were pretreated with H2O2 or NO alone.
https://breeding.tabrizu.ac.ir/article_13099_c0dca2c9cd6c6fdc2ef2d74e228f841e.pdf
2020-12-29
27
43
10.22034/jppb.2020.13099
Combined priming
Flavonoid
Ion homeostasis
Nitric oxide
Oilseed Rape
Salicylic acid
salinity
Zahra
Karimi
zahra.karimi92@yahoo.com
1
Department of Biology, Faculty of Sciences, Urmia University, Urmia, Iran.
AUTHOR
Jalil
Khara
j.khara@urmia.ac.ir
2
Department of Biology, Faculty of Science, Urmia University, Urmia, Iran.
AUTHOR
Ghader
Habibi
gader.habibi@gmail.com
3
Department of Biology, Payame Noor University (PNU), Tehran, Iran.
LEAD_AUTHOR
Ali Q, Daud MK, Haider MZ, Ali S, Rizwan M, Aslam N, Noman A, Iqbal N, Shahzad F, Deeba F and Ali I, 2017. Seed priming by sodium nitroprusside improves salt tolerance in wheat (Triticum aestivum L.) by enhancing physiological and biochemical parameters. Plant Physiology and Biochemistry 119: 50-58.
1
Ashfaque F, Khan MIR and Khan NA, 2014. Exogenously applied H2O2 promotes proline accumulation, water relations, photosynthetic efficiency and growth of wheat (Triticum aestivum L.) under salt stress. Annual Research & Review in Biology 4(1):105-120.
2
Balotf S, Islam S, Kavoosi G, Kholdebarin B, Juhasz A and Ma W, 2018. How exogenous nitric oxide regulates nitrogen assimilation in wheat seedlings under different nitrogen sources and levels. PLoS One 13(1):e0190269. 10.1371/journal.pone.0190269.
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5
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64
ORIGINAL_ARTICLE
Antioxidant properties of two alfalfa (Medicago sativa L.) ecotypes in response to sodium chloride salinity stress
Biochemical and physiological responses of alfalfa under salinity stress were comparatively studied in a factorial experiment based on randomized complete block design by using Yazdi as the tolerant and Diabolourde as the sensitive ecotypes. Salt levels of 100, 150 and 200 mM were prepared by adding sodium chloride to the Hoagland half-strength culture medium. Total phenolics content, polyphenol oxidase (PPO), β-glucosidase and antiradical activities of leave′s extract, stomata properties and chlorophyll fluorescence parameters of the leaves including Fv/Fm and Fv/Fo were measured in response to salinity stress. Stomata characters were reduced in both ecotypes but chlorophyll fluorescence parameters only declined in Diabolourde but not in the Yazdi ecotype. The PPO and β-glucosidase activities increased in both ecotypes. The phenolics content and antiradical activities increased in the Yazdi ecotype at all salt levels but those of Diabolurde increased only at the higher salinity levels. Our observations indicated that the Yazdi ecotype manipulated biochemical and physiological responses more efficiently to alleviate the reduction of growth parameters under salinity.
https://breeding.tabrizu.ac.ir/article_13192_15ec021b2fbe203b1d920805a3b7e738.pdf
2020-12-01
45
58
10.22034/jppb.2020.13192
Alfalfa
β-glucosidase
Polyphenol oxidase
Stomata properties
Total phenolics
Seyed Afshin
Hosseini-Boldaji
afshin.h.b@gmail.com
1
Department of Biology, College of Sciences, Yadegar-e- Imam Khomeini (RAH) Shahre Rey Branch, Islamic Azad University, Tehran, Iran.
LEAD_AUTHOR
Babak
Babakhani
babakhani.biology@gmail.com
2
Department of Biology, Tonekabon Branch, Islamic Azad University, Tonekabon, Iran.
AUTHOR
Reza
Hassan-Sajedi
r_sajedi@modares.ac.ir
3
3Department of Biochemistry, Faculty of Biological Sciences, Tarbiat Modares University, Tehran, Iran.
AUTHOR
Mahdieh
Houshani
mhoshani@yahoo.com
4
Department of Biology, Tonekabon Branch, Islamic Azad University, Tonekabon, Iran.
AUTHOR
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46
ORIGINAL_ARTICLE
Evaluation of seed yield stability of barley promising genotypes using principal coordinates analysis
Analysis of the structure of genotype by environment (GE) interaction is essential in crop stability programs. To study the effects of GE interaction on the seed yield and identify stable genotypes of barley for warm and humid regions, 16 barley genotypes with two check cultivars were assayed in a randomized complete block design with four replications in Gachsaran, Moghan, Khorramabad and Gonbad regions for three years (2017-2019). Combined analysis of variance for yield data of 12 environments (year/location combined) showed significant differences among environments and genotypes and significant GE interaction. The GE interaction was examined using principal coordinates analysis (PCoA). Based on the deviation from the grand mean, 12 environments were divided into two main groups: five environments with higher mean yield and seven environments with lower mean yield. The most stable genotypes based on the minimum spanning tree and distance from the center of plots were G13 (2.43 kg/ha), G2 (2.38 kg/ha), G14 (2.29 kg/ha), which could be recommended for environments with a yield lower than the average mean of all studied environments. The results of the PCoA showed that the genotype G18 (2.32 kg/ha) was also located five times in the vertex positions of high cycles and so it can be recommended for favorable or high yielding environments.
https://breeding.tabrizu.ac.ir/article_13195_808e8cc300f863b554a239797dd06066.pdf
2020-12-29
59
68
10.22034/jppb.2020.13195
Barley promising genotypes
GE interaction
Principal coordinates analysis
Stability
Elnaz
Ramzi
e.ramzi1393@gmail.com
1
Department of Agronomy and Plant Breeding, Faculty of Agriculture and Natural Resources, University of Mohaghegh Ardabili, Ardabil, Iran.
AUTHOR
Ali
Asghari
ali_asgharii@yahoo.com
2
Department of Agronomy and Plant Breeding, Faculty of Agriculture and Natural Resources, University of Mohaghegh Ardabili, Ardabil, Iran.
LEAD_AUTHOR
Omid
Sofalian
sofalian@gmail.com
3
Department of Agronomy and Plant Breeding, Faculty of Agriculture and Natural Resources, University of Mohaghegh Ardabili, Ardabil, Iran.
AUTHOR
Asghar
Mehraban
asgharmehraban@gmail.com
4
Moghan Agricultural Research Center, Parsabad, Iran.
AUTHOR
Asghar
Ebadi
asghar_ebadi@yahoo.com
5
Department of Agronomy and Plant Breeding, Faculty of Agriculture and Natural Resources, University of Mohaghegh Ardabili, Ardabil, Iran.
AUTHOR
Ahmadi J, Vaezi B and FotokianMH, 2012. Graphical analysis of multi-environment trials for barley yield using AMMI and GGE-biplot under rain-fed onditions, Journal of Plant Physiology and Breeding, 2(1): 43-54.
1
Akcura M, Kaya Y and Taner S, 2009. Evaluation of durum wheat genotypes using parametric and nonparametric stability statistics. Turkish Journal of Field Crops 14(2): 111-122.
2
Crossa J, 1988. A comparison of results obtained with two methods for assessing yield stability. Theoretical and Applied Genetics 75: 460-467.
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Elias AA, Robbins KR, Doerge RW and Tuinstra MR, 2016. Half a century of studying genotype × environment interactions in plant breeding experiments. Crop Science 56: 2090-2105.
4
Flores F, Moreno MT, Martinez A and Cubero JI, 1996. Genotype × environment interaction in faba bean: comparison of AMMI and principal coordinate models. Field Crops Research 47: 117-127.
5
GENSTAT Committee, 2009. GENSTAT 12 release 1, Reference Manual. Clarendon Press, Oxford, UK.
6
Ibanmez MA, Direnzo MA, Samame SS, Bonamico MM and Poverene NC, 2001. Genotype × environment interaction of lovegrass forage yield in the semi-arid region of Argentina. Journal of Agricultural Science 137: 329-336.
7
Karimizadeh R, Asghari A, Chinipardaz R, Sofalian O and Ghaffari A, 2016. Determining yield stability and model selection by AMMI method in rain-fed durum wheat genotypes. Turkish Journal of Field Crops 21(2): 174-183.
8
Karimizadeh R, Asghari A, Chinipardaz R, Sofalian O, Ghaffari A, Shahbazi K, Hosseinpour T, Ghojog H and Armion M, 2019. Use of principal coordinate analysis for measuring GE interactions in rain-fed durum wheat genotypes. Agricultural Sciences 25: 38-46.
9
Karimizadeh R, Mohammadi, M and Sabbagnia, N, 2013. Site regression biplot analysis for matching new improved lentil genotypes into target environments. Journal of Plant Physiology and Breeding, 3(2): 51-65.
10
Medina JL, Moore PP, Shanks JR, Gil FF and Chandler CK, 1999. Genotype × environment interaction for resistance to spider mites in Fragaria. Journal of American Society of Horticultural Science 124: 353-357.
11
Mohebodini M, Karimizadeh R, Mohammadi M and Sabaghnia N, 2012. Principal coordinates analysis of genotype × environment interaction in grain yield of lentil genotypes. Agriculture and Forestry 57: 93-107.
12
Reynolds MP, Quilligan E, Aggarwal PK, Bansal KC, Cavalieri AJ, Chapman, SC, Chapotin SM, Datta SK, Duveiller E, Gill KS, Jagadish KSV, Joshi AK, Koehler AK, Srivalli PK, Lafitte K.R, Mahala R.S, Muthurajan R, Paterson AH, Prasanna B.M, Rakshit S, Rosegrant MW, Sharma I, Singh RP, Sivasankar S, Vadez V, Valluru R, Prasad PVV and Yadav OM, 2016. An integrated approach to maintaining cereal productivity under climate change. Global Food Security 8: 9-18
13
Sabaghnia N, Mohammadi M and Karimizadeh R, 2013. Principal coordinate analysis of genotype × environment interaction for grain yield of bread wheat in the semi-arid regions. Genetika 45: 691-701.
14
Tabachnick GB and Fidell LS, 2012. Using Multivariate Statistics. Pearson Publications, USA, 1024 pp.
15
Westcott B, 1986. Some methods of analyzing genotype-environment interaction. Heredity 56: 243-253.
16
Westcott B, 1987. A method of assessing the yield stability of crop genotypes. Journal of Agricultural Science 108: 267-274.
17
Yan W, 2012. Biplot analysis of incomplete two-way data. Crop Science, 53: 48-57.
18
Yan W, Kang MS, Ma B, Woods S and Cornelius PL, 2007. GGE biplot vs. AMMI analysis of genotype-by-environment data. Crop Science 47: 643-655.
19
Zuur AF, Leno EN and Smith GM, 2007. Statistics for Biology and Health - Analyzing Ecological Data. Springer, New York.
20
ORIGINAL_ARTICLE
Evaluation of genotype × environment interaction for grain yield of promising genotypes of rice (Oryza sativa L.) derived from mutation induction using the GGE-biplot method
The existence of genotype × environment interaction complicates the evaluation of cultivar performance and reduces gain to selection. One of the multivariate methods for interpreting genotype by environment interaction is GGE-Biplot, in which the main effect of genotype and genotype by environment interaction are investigated simultaneously. In this study, 13 mutant genotypes of rice along with three check cultivars Tarrom-Mahalli, Tarrom-Jelodar and Neda were evaluated for grain yield stability in the two locations of Sari and Tonekabon during the years 2016 and 2017 using randomized complete block design with three replications within each environment. The results of GGE-biplot analysis showed that the two first components explained 92.52% of the total yield variation. According to the polygon view, all four environments of the experiment were located in the place that the Neda cultivar was at the top. Genotypes 33, 30, 26, 31 were highly stable genotypes and genotypes 18, 16 and 25 were highly unstable. In this study, we found only one mega-environment. Also following Neda and Jelodar cultivars, genotype 31 was closest to the ideal genotype. Ton 95 was the most desirable environment.
https://breeding.tabrizu.ac.ir/article_13269_01946abcdec744011a43b7623252ea51.pdf
2020-12-29
69
76
10.22034/jppb.2020.13269
Genotype by environment interaction
GGE-biplot
Mutant rice
Stability
Gholamreza
Cheloei
rezacheloei@yahoo.com
1
Department of Plant Breeding, Faculty of Crop Sciences, Sari Agricultural Sciences and Natural Resources University, Sari, Iran.
AUTHOR
Gholam Ali
Ranjbar
ali.ranjbar@gmail.com
2
Department of Plant Breeding, Faculty of Crop Sciences, Sari Agricultural Sciences and Natural Resources University, Sari, Iran.
LEAD_AUTHOR
Nadali
Babaeian-Jelodar
nbabaeian@yahoo.com
3
Department of Plant Breeding, Faculty of Crop Sciences, Sari Agricultural Sciences and Natural Resources University, Sari, Iran.
AUTHOR
Nadali
Bagheri
n.bagheri@sanru.ac.ir
4
Department of Plant Breeding, Faculty of Crop Sciences, Sari Agricultural Sciences and Natural Resources University, Sari, Iran.
AUTHOR
Mohammadzaman
Nouri
mznouri@yahoo.com
5
Rice Research Institute of Iran, Amol, Iran.
AUTHOR
Ahmadi J, Vaezi B and Fotokian MH, 2012. Graphical analysis of multi-environment trials for barley yield using AMMI and GGE-Biplot under rain-fed conditions. Journal of Plant Physiology and Breeding 2(1): 43-54.
1
Bana RS, Singh D, Nain MS, Kumar H, Kumar V and Sepat S, 2020. Weed control and rice yield stability studies across diverse tillage and crop establishment systems under on-farm environments. Soil & Tillage Research 204: 104729.
2
Bii CL, Ngug K, Kimani JM, George N and Chemining W, 2020. Genotype by environment analysis of rice (Oryza sativa L.) populations under drought stressed and well-watered environments. Australian Journal of Crop Science 14: 259-262.
3
Chandrashekhar S, Babu R, Jeyaprakash RU, Bhuvaneshwari K and Manonmani S, 2020. Yield stability analysis in multi-environment trials of hybrid rice (Oryza sativa L.) in northern India using GGE Biplot analysis. Electronic Journal of Plant Breeding 2: 665-673.
4
Jadhav S, Balakrishnan D, Shankar G, Beerelli K, Chandu G and Neelamraju S, 2019. Genotype by environment (G×E) interaction study on yield traits in different maturity groups of rice 22: 425-449.
5
Karimizadeh R, Mohammadi M and Sabaghnia N, 2013. Site regression biplot analysis for matching new improved lentil genotypes into target environments. Journal of Plant Physiology and Breeding 3(2): 51-65.
6
Kroonenberg PM, 1995. Introduction to biplots for G × E Tables. Department of Mathematics, Res. Rep. 51. University of Queensland, Australia.
7
Li Y, Suontama M, Burdon RD and Dungey HS, 2017. Genotype by environment interactions in forest tree breeding: review of methodology and perspectives on research and application. Tree Genetics & Genomes 13: 1-18.
8
Oladosu Y, Rafli MY, Abdullah N, Magaji U, Miah G, Hussin G and Ramli A, 2017. Genotype × environment interaction and stability analyses of yield and yield components of established and mutant rice genotypes tested in multiple locations in Malaysia. Acta Agriculturae Scandinavica, Section B- Soil & Plant Science 7: 590-606.
9
R Development Core Team, 2016. R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna. Austria. URL http://www.R-project.org/.
10
Raza Khan RA, Ramzan M, Haider Z, Akter M, Riaz M, Ali SS, Awan TH and Mahmood A, 2019. Stability and adaptability analysis in advance fine grain rice (Oryza sativa L.) genotypes for yield. Journal of Agriculture and Aquaculture 2: 1-9.
11
Yan W, 2002. Singular-value partitioning in biplot analysis of multi-environment trial data. Agronomy Journal 94: 990-996.
12
Yan W, 2019. LG biplot: a graphical method for mega-environment investigation using existing crop variety trial data. Scientific Reporters 9: 7130. doi.org/10.1038/s41598-019-43683-9.
13
Yan W, Cornelius PL, Crossa J and Hunt LA, 2001. Two types of GGE biplots for analyzing multi-environment trial data. Crop Science 41: 656-663.
14
Yan W, Hunt LA, Sheng Q and Szlavnics Z, 2000. Cultivar evaluation and mega environment investigations based on the GGE biplot. Crop Science 40: 597-605.
15
Yan W and Kang MS, 2003. GGE Biplot Analysis: A Graphical Tool for Breeders, Geneticists, and Agronomists. CRC Press, Boca Raton, FL, USA, 271p.
16
Yan W and Rajcan, 2002. Biplot analysis of test sites and trait relations of soybean in onatario. Crop Science 42: 11-20.
17
Yan W and Tinker NA, 2006. Biplot analysis of multi-environment trial data: principles and applications. Canadian Journal of Plant Science 86: 623-645.
18
ORIGINAL_ARTICLE
Effect of 17β-estradiol on seedling and callus growth of German chamomile (Matricaria chamomilla L.)
To study the effect of 17β-estradiol on seedling growth, antioxidant enzyme activity and also, on callus induction from leaf explants of German Chamomile (Matricaria chamomilla L.), an experiment was conducted as a completely randomized design with three replications using MS medium containing different concentrations of 17β-estradiol (0, 0.01, 0.1, 1 and 10 mg/l) alone or in combination with 3 mg/l Benzylaminopurine (BAP) + 0 or 1.5 mg/l 1-naphthalene acetic acid (NAA). The results showed that 17β-estradiol at 0.01 and 0.1 mg/l increased root and shoot length and weight, respectively and at high concentration (10 mg/l) increased peroxidase, polyphenol oxidase and catalase activity of German chamomile seedlings. Also, the callus induction was observed after one to two weeks in all media, but the growth varied depending on the presence or absence of plant growth regulators and different concentrations of 17β-estradiol. Maximum callus weight was obtained in 0.01 mg/l of 17β-estradiol with about three-fold increase in comparison with the control (MS without17β-estradiol). This indicates that the 17-beta-estradiol at lower concentrations (0.01 mg/l) can significantly improve callus growth in the presence of plant growth regulators such as NAA and BAP. The results of this study indicate that using steroidal hormone 17β-estradiol can be used to optimize German chamomile cell growth under in vitro conditions.
https://breeding.tabrizu.ac.ir/article_13271_3977cd8416228a20178ee7e1e24c66af.pdf
2020-12-29
77
87
10.22034/jppb.2020.13271
Antioxidant enzymes
Callus induction
In vitro culture
Steroid hormone
Elnaz
Nozari
nozari_elnaz@yahoo.com
1
Former MSc student of Agricultural Biotechnology, Department of Agronomy and Plant Breeding, University of Mohaghegh Ardabili, Ardabil, Iran.
AUTHOR
Rasool
Asghari Zakaria
r-asghari@uma.ac.ir
2
Department of Agronomy and Plant Breeding, Faculty of Agriculture and Natural Resources, University of Mohaghegh Ardabili, Ardabil, Iran.
LEAD_AUTHOR
Nasser
Zare
zarenasser@yahoo.com
3
Department of Agronomy and Plant Breeding, Faculty of Agriculture and Natural Resources, University of Mohaghegh Ardabili, Ardabil, Iran.
AUTHOR
Chance B and Maehly AC, 1955. Assay of catalases and peroxidases. Methods in Enzymology 11: 764-755.
1
Dumlupinar R, Genisel M, Erdal S, Korkut T, Taspinar MS and Taskin M, 2011. Effects of progesterone, β-estradiol and androsterone on the changes of inorganic element content in barley leaves. Biological Trace Element Research 143: 1740-1745.
2
Erdal S, 2012a. Exogenous mammalian sex hormones mitigate inhibition in growth by enhancing antioxidant activity and synthesis reactions in germinating maize seeds under salt stress. Journal of Science, Food and Agriculture 92: 839-843.
3
Erdal S, 2012b. Alleviation of salt stress in wheat seedlings by mammalian sex hormones. Journal of Science, Food and Agriculture 92: 1411-1416.
4
Erdal S, 2012c. Androsterone-induced molecular and physiological changes in maize seedlings in response to chilling stress. Plant Physiology and Biochemistry 57: 1-7.
5
Erdal S and Dumlupinar R, 2011a. Mammalian sex hormones stimulate antioxidant system and enhance growth of chickpea plants. Acta Physiologiae Plantarum 33: 1011-1017.
6
Erdal S and Dumlupinar R, 2011b. Exogenously treated mammalian sex hormones affect inorganic constituents of plants. Biological Trace Element Research 143: 500-506.
7
Fathi S, Kharazmi M and Najafian S, 2019. Effects of salicylic acid foliar application on morpho-physiological traits of purslane (Portulaca olaracea L.) under salinity stress conditions. Journal of Plant Physiology and Breeding 9(2): 1-9.
8
Fazeli Behgo T and Alizadeh Ajirlo S, 2015. Callus induction and shoot regeneration using indole acetic acid and N-isopentenylamino purine combinations and two types of explant in tomato. Journal of Plant Physiology and Breeding 5(2): 41-50.
9
Genisel M, Turk H and Erdal S, 2013. Exogenous progesterone application protects chickpea seedlings against chilling-induced oxidative stress. Acta Physiologiae Plantarum 35: 241-251.
10
Geuns JMC, 1978. Steroid hormones and plant growth and development. Phytochemistry 17: 1-14.
11
Iino M, Nomura N, Tamaki Y, Yamada Y, Yoneyama K and Takeuchi Y, 2007. Progesterone: its occurrence in plants and involvement in plant growth. Phytochemistry 68: 1664-1673.
12
Janeczko A, 2012. The presence and activity of progesterone in the plant kingdom. Steroids 77: 169-173.
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Janeczko A and Skoczowski A, 2005. Mammalian sex hormones in plants. Folia Histochemistry and Cytochemistry43: 71-79.
14
Janeczko A and Szybka P, 2001. Induction and proliferation of callus of Polygonatum verticillatum L. Conference materials of the 18th Meeting of the Polish Pharmaceutical Society Pharmacy in the 21st century, 19-22 September, Poznan, Poland, p 536 (In Polish).
15
Janeczko A, Filek W and Skoczowski A, 2002. Influence of human sex hormones on the growth response of winter wheat immature embryos and callus.Zeszyty Problemowe Postepow Nauk Rolniczych 488: 667-673 (In Polish).
16
Janik JR and Adler JH, 1984. Estrogen receptors in Gladiolus ovules. Plant Physiology 75(Suppl): 135.
17
Kar M and Mishra D, 1976. Catalase, peroxidase, and polyphenol oxidase activities during rice leaf senescence. Plant Physiology 57: 315-319.
18
Khan M, Rozhon W, Unterholzner SJ, Chen T, Eremina M, Wurzinger B, Bachmair A, Teige M, Sieberer T, Isono E and Poppenberger B, 2014. Interplay between phosphorylation and SUMOylation events determines CESTA protein fate in brassinosteroid signaling. Natural Communication 5: 4687 doi:10.1038/ncomms5687.
19
Koohi L, Zare N, Asghari Zakaria R and SheikhZadeh-Mosaddegh P, 2014. Effect of plant growth regulators and different explants on tissue culture response and suspension cell cultures of German chamomilla (Matricaria chamomilla L.). Journal of Crop Ecophysiology 8: 203-214 (In Persian with English abstract)
20
Milanesi L, Monje P and Boland R, 2001. Presence of estrogens and estrogen receptor-like proteins in Solanum glaucophyllum. Biochemical and Biophysical Research Communications 289: 1175-1179.
21
Murashige T and Skoog F, 1962. A revised method for rapid growth and bioassays with tobacco tissue cultures. Physiologia Plantarum 15: 472-497.
22
Petronilho S, Maraschin M, Coimbra MA and Rocha SM, 2012. In vitro and in vivo studies of natural products: a challenge for their valuation. The case study of chamomile (Matricaria recutita L.). Industrial Crops and Products 40: 1-12.
23
Pourasadollahi A, Siosemardeh A, Hosseinpanahi F and Sohrabi Y, 2019. Physiological and agro-morphological response of potato to drought stress and hormone application. Journal of Plant Physiology and Breeding 9(1): 47-61.
24
Shore LS, Kapulnik Y, Ben-Dor B, Fridman Y, Wininger S and Shemesh M, 1992. Effects of estrone and 17β-estradiol on vegetative growth of Medicago sativa. Physiologia Plantarum 84: 217-222.
25
Simersky R, Novak O, Morris DA, Pouzar V and Strnad M, 2009. Identification and quantification of several mammalian steroid hormones in plants by UPLC-MS/MS. Journal of Plant Growth Regulation28: 125-136.
26
Simons RG and Grinwich DL, 1989. Immunoreactive detection of four mammalian steroids in plants. Canadian Journal of Botany 67: 288-296.
27
Sudhakar S, Li Y, Katz MS and Elango N, 2001. Translational regulation is a control point in RUNX2/Cbfa1 gene expression. Biochemical and Biophysical Research Communications 289: 616-622.
28
ORIGINAL_ARTICLE
Transferability of wheat SSR markers for determination of genetic diversity and relationships of barley varieties
Simple sequence repeat (SSR) markers are simple PCR-based co-dominant markers, which are highly polymorphic and informative due to the number and frequency of alleles, and thus they are most utilized among the molecular markers. However, the development of SSR markers is costly and time-consuming. Cross-species transferability of SSRs allows the SSRs isolated from one species to apply on a closely related species, which increases the utility of previously isolated SSRs. This study demonstrated the cross-species transferability of 196 SSR primer pairs of wheat in genetic diversity analysis of 40 varieties of barley (Hordeum vulgare L.). Of the 196 SSR primer pairs assayed, 59 (30.1%) showed transferability. Of the 59 primer pairs, 21 pairs were polymorphic with the polymorphism information content ranging from 0.19 to 0.70. The number of alleles detected at each locus ranged from one to seven with an average of 3.57. Cluster analysis using the Minimum Evolution algorithm and the coefficient of Number of Differences assigned the genotypes into five groups.
https://breeding.tabrizu.ac.ir/article_13277_25acaf29939adca31238920d545f4bdd.pdf
2020-12-01
89
98
10.22034/jppb.2020.13277
Barley
SSR
Transferability
Wheat
Homa
Zallaghi
homa.zallaghi@yahoo.com
1
Department of Plant Breeding and Biotechnology, University of Tabriz, Tabriz, Iran.
AUTHOR
Seyed Abolghasem
Mohammadi
mohammadi@tabrizu.ac.ir
2
Department of Plant Breeding and Biotechnology, Faculty of Agriculture, University of Tabriz, Tabriz, Iran.
LEAD_AUTHOR
Mohammad
Moghaddam
mmoghaddam@tabrizu.ac.ir
3
ِDepartment of Plant Breeding and Biotechnology, Faculty of Agriculture, University of Tabriz, Tabriz, Iran.
AUTHOR
Behzad
Sadeghzadeh
behzada4@yahoo.com
4
Dryland Agriculture Research Institute of Iran, Maragheh, Iran.
AUTHOR
Basudeba K, Kumar JR and Sanghamitra N, 2013. Cross-amplification polymorphism of rice microsatellites in Zingiberaceae. Research Journal of Biotechnology 8(3): 76-83.
1
Castillo A, Budak H, Varshney RK, Dorado G, Graner A and Hernandez P, 2008. Transferability and polymorphism of barley EST-SSR markers used for phylogenetic analysis. BMC Plant Biology 8: 97. doi.org/10.1186/1471-2229-8-97.
2
Chen SHY, Lin TY, Lin CHW, Chen WY, Yang CHH and Ku HM, 2010. Transferability of rice SSR markers to bamboo. Euphytica 175: 23-33.
3
Erayman M, Elhan E, Guzel Y and Eren AH, 2014. Transferability of SSR markers from distantly related legumes to Glycyrrhiza species. Turkish Journal of Agriculture and Forestry 38: 32-38.
4
Gupta PK, Rustgi S, Sharma S, Singh R, Kumar N and Balyan HS, 2003. Transferable EST-SSR markers for the study of polymorphism and genetic diversity in bread wheat. Molecular Genetics and Genomics 270: 315-323.
5
Khodayari H, Saeidi H, Akhavan Roofigar A, Rahiminejad MR, Purkheirandish M and Komatsuda T, 2012. Genetic diversity of cultivated barley landraces in Iran measured using microsatellites. International Journal of Bioscience, Biochemistry and Bioinformatics 4: 287-290.
6
Kuleung C, Baenziger PS and Dweikat I, 2004. Transferability of SSR markers among wheat, rye and triticale. Theoretical and Applied Genetics 108: 1147-1150.
7
Liu K and Muse SV, 2005. PowerMarker: an integrated analysis environment for genetic marker data. Bioinformatics 21: 2128-2129.
8
Lio YC, Lio S, Lio D, Wei YX, Lio C, Yang YM, Tao CG and Lio WS, 2014. Exploiting EST databases for the development and characterization of EST-SSR marker in blueberry (Vaccinium) and their crop species transferability in Vaccinium spp. Scientia Horticulturae 176: 319-329.
9
Magurran AE, 2004. Measuring Biological Diversity. Blackwell, pp. 215.
10
Mohammadvand Latifi M, Jamali SH, Mobasser S, Sadeghi L and Sadeghian SY, 2012. Identification and distinctness of barley varieties using SSR markers. Journal of Plant Physiology and Breeding 1(2): 73.
11
Naceur, A.B., Chaabane, R., El-Faleh, M., Ramla, C.A.D., Nada, A., Sakr, M. and Naceur, M.B. 2012. Genetic diversity analysis of North Africa’s barley using SSR markers. Journal of Genetic Engineering and Biotechnology, 10: 13-21.
12
Nie, M. 1973. Analysis of gene diversity in subdivided populations. Proceeding of National Academy of Sciences of the United States of America, 70: 3321-3323.
13
Peakall, R., Gilmore, S., Keys, W., Morgante, M. and Rafalski, A. 1998. Cross-species amplification of soybean (Glycine max) simple sequence repeats (SSRs) within the genus and other legume genera: implications for the transferability of SSRs in plants. Molecular Biology and Evolution, 15(10): 1275-1287.
14
Peakall, R.O.D. and Smouse, P.E. 2006. GENALEX 6: genetic analysis in Excel. Population genetic software for teaching and research. Molecular Ecology Notes, 1: 288-295.
15
Powell, W., Machray, G.C. and Provan, J. 1996. Polymorphism revealed by simple sequence repeats. Trends in Plant Science, 1: 215-222.
16
Saghai-Maroof, M.A., Biyashev, R.M., Yang, G.P., Zhang, Q. and Allard. R.W. 1994. Extra ordinarily polymorphic microsatellite DNA in barley: species diversity, chromosomal locations, and population dynamics. Proceeding of the National Academy of Sciences of the United States of America, 91: 5466-5470.
17
Sing, R., Narzary, D., Bhardwaj, J., Sing, A.K., Kumar, S. and Kumar, A. 2014. Molecular diversity and SSR transferability studies in Vetiver grass (Vetiveria Zizanioides L. Nash). Industrial Crops and Products, 53: 187-198.
18
Singh, R.K., Singh, R.B., Singh, S.P. and Sharma, M.L. 2011. Identification of sugarcane microsatellites associated to sugar content in sugarcane and transferability to other cereal genomes. Euphytica, 182: 335-354.
19
Tamura, K., Dudley, J., Nei, M. and Kumar, S. 2011. MEGA 5: Molecular evolutionary genetics analysis (MEGA) software, version 5.0. Molecular Biology and Evolution, 24: 1596-1599.
20
Tang, J., Gao, L., Cao, Y. and Jia, J. 2006. Homologous analysis of SSR-ESTs and transferability of wheat SSR-EST markers across barley, rice, and maize. Euphytica, 151: 87-93.
21
Varshney, R.K. 2004. Interspecific transferability and comparative mapping of barley EST-SSR markers in wheat, rye, and rice. Plant Science, 168: 195-202.
22
Wang, M.L., Barkley, N.A., Yu, J.-K., Dean, R.E., Newman, M.L., Sorrells, M.E. and Pederson, G.A. 2004. Transfer of simple sequence repeat (SSR) markers from major cereal crops to minor grass species for germplasm characterization and evaluation. Plant Genetic Resources, 3(1): 45-57.
23
Yildiz, M., Cuevas, H.E., Sensoy, S., Erdinc, C. and Baloch, F.S. 2015. Transferability of Cucurbita SSR markers for genetic diversity assessment of Turkish bottle gourd (Lagenaria siceraria) genetic resources. Biochemical Systematics and Ecology, 59: 45-53.
24
Zaloglu, S., Kafkas, S., Dogan, Y. and Gunery, M. 2015. Development and characterization of SSR Markers from pistachio (Pistacia vera L.) and their transferability to eight pistacia species. Scientia Horticulturae, 189: 94-103.
25
Zeid, M., Yu, J.K., Goldowitz, I., Denton, M.E., Costich, D.E., Jayasuriya, C.T., Saha, M., Elshire, R., Benscher, D., Breseghello, F., Munkvold, J., Varshney, R.K., Belay, G. and Sorrells, M.E. 2010. Cross-amplification of EST-derived markers among 16 grass species. Field Crops Research, 118: 28-35.
26
Zhang, L.Y., Bernard, M., Leroy, P., Feuillet, C. and Sourdille, P. 2005. High transferability of bread wheat EST-derived SSRs to other cereals. Theoretical and Applied Genetics, 111: 677-687.
27
ORIGINAL_ARTICLE
Comparing the efficiency of the three heterotic-group and traditional two heterotic-group classifications for the hybrid maize breeding
Increasing the efficiency of the hybrid-based maize breeding program has highly contributed to the heterotic group classification. The present study was aimed to compare the breeding efficiency of the three heterotic-group (TriHG) classification [Lancaster Sure Crop (LSC), Reid Yellow Dent (RYD), CIMMYT] system and usual two heterotic-group (DiHG) classification (RYD, LSC) system. To accomplish this, specific breeding efficiency (SBE) and general breeding efficiency (GBE) were estimated for the grain yield. The mating design was a line × tester scheme in which seven adapted tropical and subtropical lines were crossed to four testers. GBE increased by 128% in the TriHG classification system as compared to the DiHG system while no significant loss was observed in SBE. It seems that the TriHG system was advantageous over the DiHG system by improving the maize breeding efficiency. Therefore, using one tester from each of the three heterotic groups (RYD, LSC, CIMMYT) could be more efficient in hybrid-based maize breeding programs in temperate regions, including Iran.
https://breeding.tabrizu.ac.ir/article_13521_0046c706e8c3acbed777333935a567d5.pdf
2020-12-29
99
107
10.22034/jppb.2020.13521
DiHG
Heterotic group
Heterotic pattern
Line × tester
TriHG
Mohammadreza
Shiri
mohammadrezashiri52@gmail.com
1
Seed and Plant Improvement Institute, Karaj, Iran.
LEAD_AUTHOR
Abadi JM, Khavari KS, Syah SB, Movafegh S and Golbashy M, 2011. Estimation of combining ability and gene effects in forage maize (Zea mays L.) using line × tester crosses. Journal of Plant Physiology and Breeding 1: 57-67.
1
Barata C and Carena MJ, 2006. Classification of North Dakota maize inbred lines into heterotic groups based on molecular and testcross data. Euphytica 151: 339-349.
2
Ceccarelli S, 2015. Efficiency of plant breeding. Crop Science 55: 87-97.
3
Choukan R, Hossainzadeh A, Ghannadha MR, Warburton ML, Talei AR and Mohammadi SA, 2006. Use of SSR data to determine relationships and potential heterotic groupings within medium to late maturing Iranian maize inbred lines. Field Crops Research 95: 212-222.
4
Duvick DN, 2001. Biotechnology in the 1930s: the development of hybrid maize. Nature Reviews Genetics 2: 69-74.
5
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17
ORIGINAL_ARTICLE
Interpretation of genotype × environment interaction for grain yield of barley using the GGE biplot method
The identification of the most favorable cultivar(s) with high yield and stable performance is usually done based on the analysis of the genotype × environment (GE) interaction. The yield stability of 16 barley lines with two check varieties was studied in a randomized complete block design with four replications across three years at five locations in a multi-environment trial layout. The dataset was analyzed with a GGE (genotype main effect (G) + GE interaction) biplot method. Results indicated that the first two principal components (PCs) explained 81, 78 and 71% of the GGE sum of squares for 2017, 2018 and 2019 growing seasons, respectively. According to the average environment coordinate abscissa, G2, G13 and G18 were the best genotypes in terms of grain yield in years 2017 and 2018 while genotypes G2, G7 and G14 were the highest yielding genotypes in 2019. When both yield performance and stability were considered simultaneously, the G2 and G13 genotypes in 2017 and G2, G8 and G13 in 2018, were closer to the ideal genotype. In 2019, G2, G7 and G14 were the best in terms of grain yield and stability. In the "which-won-where pattern", the five locations in 2017 fell into four sectors with different winning genotypes as G2, G5, G14 and G13. In 2018, the five locations fell into three sectors in which G2, G4 and G17 were the highest yielding genotypes while in 2019, locations were positioned in four sectors and G2, G7, G10 and G13 were chosen as the winning genotypes. However, for practical use of the “which-won-where” pattern, the mean performance of genotypes over three years in the five test locations was taken into account. Although the results revealed six mega-environments, by neglecting small differences, we can assume only one mega-environment in which G2 (the check variety Khorram) was the best performing genotype.
https://breeding.tabrizu.ac.ir/article_13670_c11c78a4983aae626f9b7847b0ba33f3.pdf
2020-12-29
109
119
10.22034/jppb.2020.13670
Barley
GGE biplot
Grain Yield
Multi-environment trials
Singular value decomposition
Behrouz
Vaezi
bvaezi2009@gmail.com
1
Kohgiluyeh and Boyerahmad Agricultural and Natural Resources Research and Education Center, Agricultural Research, Education and Extension Organization (AREEO), Yasuj, Iran
AUTHOR
Hamid
Hatami Maleki
hatamimaleki@yahoo.com
2
Department of Plant Production and Genetics, Faculty of Agriculture, University of Maragheh, Maragheh, Iran.
LEAD_AUTHOR
Ali
Ahmadi
3
Lorestan Agricultural and Natural Resources Research and Education Center, Agricultural Research, Education and Extension Organization (AREEO), Khorram-Abad, Iran.
AUTHOR
Asghar
Mehraban
amehraban@gmail.com
4
Ardabil Agricultural and Natural Resources Research Center, Agricultural Research, Education and Extension Organization (AREEO),Parsabad, Iran
AUTHOR
Rahmatollah
Mohammadi
r.mohammadi@yahoo.com
5
Golestan Agricultural and Natural Resources Research and Education Center, Agricultural Research, Education and Extension Organization (AREEO), Gorgan, Iran
AUTHOR
Zeinab
Sabzi
zeinabs@yahoo.com
6
Agricultural and Natural Resources Research and Education Center, Agricultural Research, Education and Extension Organization (AREEO), Ilam, Iran
AUTHOR
Naser
Sabaghnia
sabaghnia@yahoo.com
7
Department of Plant Production and Genetics, Faculty of Agriculture, University of Maragheh, Maragheh, Iran.
AUTHOR
Ahmadi J, Vaezi B and Fotokian MH, 2012. Graphical analysis of multi-environment trials for barley yield using AMMI and GGE-Biplot under rain-fed conditions. Journal of Plant Physiology and Breeding 2: 43-54.
1
Bustos-Korts D, Romagosa I, Borras-Gelonch G, Casas AM, Slafer GA and Van Eeuwijk F, 2018. Genotype by environment interaction and stability reaction. In: Meyers R. (eds.). Encyclopedia of Sustainability Science and Technology. Springer, Germany.
2
Dehghani H, Ebadi A and Yousefi A, 2006. Biplot analysis of genotype by environment interaction for barley yield in Iran. Agronomy Journal 98: 388-393.
3
Dehghani H, Sabaghnia N and Moghaddam M, 2009. Interpretation of genotype-by-environment interaction for late maize hybrids’ grain yield using a biplot method. Turkish Journal of Agriculture and Forestry 33: 139-148.
4
Dia M, Wehner TC, Hassell R, Price DS, Boyhan GE, Olson S, King S, Davis AR and Tolla GE, 2016. Genotype × environment interaction and stability analysis for watermelon fruit yield in the United States. Crop Science 56: 1645-1661.
5
FAO, 2017. FAOSTAT. Food and Agriculture Organization of the United Nations. http://faostat.fao.org/.
6
Karimzadeh R, Mohammadi M and Sabaghnia N, 2013. Site regression biplot analysis for matching new improved lentil genotypes into target environments. Journal of Plant Physiology and Breeding 3: 51-65.
7
Le Marie CA, York LM, Strigens A, Malosetti M, Camp KH, Giuliani S and Hund A, 2019. Shovelomics root traits assessed on the EURoot maize panel are highly heritable across environments but show low genotype-by-nitrogen interaction. Euphytica 215: 173.
8
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9
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21
ORIGINAL_ARTICLE
Morphological and physiological responses to drought stress in eleven genotypes of the Juniperus species
Drought is one of the most prevalent and critical environmental stresses affecting a variety of plants, particularly ornamental plants. One of the useful methods to alleviate the effect of drought stress is to screen for and develop drought-tolerant varieties. In this study, a factorial experiment based on the completely randomized design was conducted to investigate the responses of 11 genotypes from different Juniperus species at two irrigation regimes (normal, drought: not irrigated for a four-week period) in terms of growth and biochemical characters.Drought stress had a significant negative impact on the assessed growth characters. The G3 and G8 genotypes had the highest root fresh weight and root dry weight at both normal and water-deficit stress conditions. G3 showed the highest root volume at normal conditions but at the drought stress, the highest root volume belonged to G1 and G8. At drought stress conditions, the leaf fresh weight and dry weight of G9, G8, G6, G4, G3 and G11 were higher than other genotypes. The stem fresh weight of G3 and G11 and the stem dry weight of G11 and G8 manifested higher values than other genotypes when water deficit stress was imposed. Stem diameter decreased in the seedlings at the drought stress, however, G2, G3, G4, G8, G9 and G11 had higher values than others at stress conditions. The relative water content decreased in the plants under stress, however, the reduction in G3, G5 and G6 were smaller than the rest of the genotypes. Among the genotypes, G5 and G3 showed the highest antioxidant activity under water-deficit stress. The genotypes G1, G6, G7 and G8 had also a notable increase in the antioxidant activity at drought stress conditions. Under drought stress, the highest increase in the proline content belonged to G3 followed by G5, G6 and G7 and the G5, G6, G10 and G8 genotypes had the highest amount of soluble sugars. In conclusion, G3 (Juniperus chinensis var. Sargentii) and G8 (Juniperus chinensis ‘Kallayʼs Compact’) showed mainly better performance under drought stress, which can be suggested as candidate drought-tolerant genotypes to be used in breeding programs for the sustainable development of urban landscape in arid and semi-arid areas. Although G5 (Juniperus procumbens ‘Nana’) had low biomass in this experiment, it showed high antioxidant activity, proline and soluble sugars at the drought stress conditions. Therefore, further investigation is needed, especially at more severe drought stress conditions, to elucidate its outstanding response to drought stress in terms of antioxidant activity and proline and soluble sugars content.
https://breeding.tabrizu.ac.ir/article_13680_82e1a4a783b849f278151ce3625f6953.pdf
2020-12-29
121
132
10.22034/jppb.2020.13680
Antioxidant Activity
Drought Stress
Juniperus
Morphological and physiological characters
Saghi
Keyghobadi
saghi94k@yahoo.com
1
Department of Horticultural Sciences, University of Guilan, Rasht, Iran.
LEAD_AUTHOR
Reza
Fotouhi Ghazvini
r.fotouhi@gmail.com
2
Department of Horticultural Sciences, University of Guilan, Rasht, Iran.
AUTHOR
Yahya
Tajvar
yahyataj80@gmail.com
3
Technology and Production Management Department, Citrus and Subtropical Research Fruits Center, Ramsar, Iran.
AUTHOR
Atefeh
Sabouri
a.sabouri@guilan.ac.ir
4
Department of Agronomy and Plant Breeding, University of Guilan, Rasht, Iran.
AUTHOR
Arshad M, Biswas K, Bisgrove S, Schroeder WR, Thomas BR, Mansfield SD, Mattsson J and Plant A, 2019. Differences in drought resistance in nine North American hybrid poplars. Trees 33: 1111-1128.
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43
ORIGINAL_ARTICLE
In vitro evaluation of drought tolerance in two grape (Vitis vinifera L.) cultivars
Abiotic stresses pose a major threat to agriculture. Therefore, developing plants that are more tolerant of these stresses is very important for improving crop productivity. Grapevines (Vitis vinifera L.) is an important fruit crop cultivated in the world. An in vitro experiment was designed to study the response of ‘White Seedless’ and ‘Flame Seedless’ cultivars of Vitis to drought stress. Treatments included four concentrations of PEG 6000, i.e., 0, 0.5, 1, and 2% (w/v), which were equivalent to 0, -0.035, -0.07, and -0.14 times the water potential, respectively. The single-node explants of Vitis grown on MS medium, supplemented with growth regulators BA (2 mg/l), NAA (0.2 mg/l), sucrose (30 g/l), agar (7 gr), and activated charcoal )200 mg/l), were transferred to the same medium but with different concentrations of PEG for 30 days. The results showed that the Flame Seedless cultivar had better growth characters than the White Seedless cultivar on the average of PEG concentrations. Flame Seedless also managed drought stress in terms of shoot length, the number of leaves per shoot, dry weight, chlorophyll a, chlorophyll b, and soluble carbohydrates more efficiently than White Seedless, and produced a high percentage of callus (87.5%) at the 1% PEG stress level. Although the White Seedless cultivar was not more vigorous than Flame Seedless but showed significantly higher proline content, non-significant reduction in relative water content, and a slightly lower reduction in shoot length, and fresh weight at 2% PEG as compared to the control. It seems that both grapevine varieties succeeded in dealing with the PEG drought stress with their special mechanisms.
https://breeding.tabrizu.ac.ir/article_14302_ec879aa9a27d2988a892b17bde4877a3.pdf
2020-12-29
133
145
10.22034/jppb.2020.14302
Drought Stress
In vitro culture
Polyethylene glycol
Vitis vinifera L
Fatemeh
Shirazi
engfatemehshirazi@yahoo.com
1
Department of Horticultural Science, Faculty of Agriculture, Bu-Ali Sina University, Hamadan, Iran
LEAD_AUTHOR
Mansour
Gholami
man.gholami@gmail.com
2
Department of Horticultural Science, Faculty of Agriculture, Bu-Ali Sina University, Hamadan, Iran
AUTHOR
Hassan
Sarikhani
sarikhani@basu.ac.ir
3
Department of Horticultural Science, Faculty of Agriculture, Bu-Ali Sina University, Hamadan, Iran
AUTHOR
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