Evaluation of Cold Tolerance in Rapeseed (Brassica napus L.) 
Using Stress Tolerance Indices

Oghan, Hassan Amiri; Ataei, Reza; Gholamhosseini, Majid; Alizadeh, Bahram

doi:10.29252/jcpp.9.2.13

Cited by 2 publications

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“…Rapeseed planting is facing restrictions due to the spread of salinity in Iran (Rameeh 2011;Saberi et al 2021). The main strategy to increase production in saline conditions is to use improved cultivars using the hybridization method (Amiri-Oghan et al 2012).…”

Section: Introductionmentioning

confidence: 99%

Using artificial neural network to evaluate salinity indices to identify rapeseed salinity tolerant cultivars

Saberi,

Ravari,

Mehrban

et al. 2024

Preprint

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In arid and semi-arid regions of the world, including Iran, soil salinity is one of the major abiotic stresses. One of the ways to achieve high performance in these areas is to use salt-tolerant varieties of canola. In order to evaluate the salt tolerance of canola genotypes based on the eight indices using analysis of variance, regression and an artificial neural network (ANN), 39 cultivars and liens of rapeseed were evaluated in terms of tolerance to salinity with the Artificial Neural Network and other statistical methods. Canola varieties were sown in a randomized complete block experiment with four replications in two not identical irrigation conditions (normal and salinity, respectively, 0.831 dSm−1 and 8.7 dSm−1) in Kerman, Iran. The experimental outcomes (the existence of a significant difference between cultivars, as well as the significance of the environmental × cultivar interaction effect and on the other hand the non-significance, 0.021, of the correlation between cultivar's performance in two irrigation conditions) showed that there are the necessary genetic diversity between genotypes for breeding purposes. The four endurance indices including harmonic mean, stress tolerance index, mean product, and geometric mean product had positive and significant correlations with seed performance in both irrigation conditions. According to this, these four indices were the best for predicting salinity tolerant cultivars. The varieties such as Talaye, Talaieh, T98007, Ahmadi, Modena, Option 500 and PP-4010 had high yield in both environments and they are recommended for cultivation in salty soils.

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Section: Introductionmentioning

confidence: 99%

Using artificial neural network to evaluate salinity indices to identify rapeseed salinity tolerant cultivars

Saberi,

Ravari,

Mehrban

et al. 2024

Preprint

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“…Estimation of additive (GCA) and non-additive (SCA) gene actions within a breeding population is imperative; it is used to determine which breeding procedures efficiently improve the performance of the traits of interest (Dudley and Moll, 1969). Most of the past studies on combining abilities have shown significant GCA and SCA effects for yield and its component traits (Rameah et al, 2003;Akbar et al, 2008;Huang et al, 2010;Shiva, 2011;Amiri-Oghan et al, 2012;Azizinia, 2016;Meena et al, 2016;Naheed et al, 2017). However, intra-species hybridization is considered one of the best ways of combining desired traits and generating variation within the population (Dar et al, 2016).…”

Section: Introductionmentioning

confidence: 99%

Combining ability and gene action analysis in a half-diallel cross of Brassica rapa L.

Zeba¹,

Ali²,

Liton³

et al. 2020

J. Agric. Sci. Pract.

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Fifteen hybrids along with six parents were tested to identify good combiners through analyzing combining ability and gene action for yield and its attributes. The experiment was conducted in randomized complete block design with three replications during 2010/11 at research farm of Sher-e-Bangla Agricultural University (SAU), Dhaka. Data for days to 50% flowering and 80% maturity, plant height, number of primary and secondary branches, number of pods per plant, number of seeds per pod, pod length, seed yield and 1000-seed weight was recorded for analysis.The results showed that mean squares for parents, hybrids, parent vs hybrid were significantly different (p<0.01 or p<0.05) for most of the traits. Highly significant mean squares due to general combining ability (GCA) were found for all the traits except for length of pod, whereas highly significant mean squares due to specific combining ability (SCA) were also found for days to 50% flowering, number of secondary branches per plant, number of pods per plant, length of pod and seed yield per plant. This indicated that both additive and non-additive gene effects were important but additive gene effects were predominant for the expression of most of the measured traits. Estimates of GCA and SCA effects for yield and its attributes suggested that parent BARI Sarisha-6, BARI Sarisha-15 and Tori-7 was good combiners for different traits. Hayman’s graphical analysis indicated both over- and partial-dominance for growth and yield attributes. As dominant (non-fixable) variation was high for most of the attributes, substantial improvements of these traits may be possible by transferring complementary gene into non-epistatic high-dominance crosses or eliminating duplicate genes from high-dominance crosses. Considering GCA, SCA and per se performance BARI Sarisha-6, BARI Sarisha-15 and Tori-7 might be good parents towards an effective breeding programme.

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Evaluation of Cold Tolerance in Rapeseed (Brassica napus L.) Using Stress Tolerance Indices

Cited by 2 publications

References 0 publications

Using artificial neural network to evaluate salinity indices to identify rapeseed salinity tolerant cultivars

Using artificial neural network to evaluate salinity indices to identify rapeseed salinity tolerant cultivars

Combining ability and gene action analysis in a half-diallel cross of Brassica rapa L.

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