Study on fine mapping of QTL for juice yield traits of sweet sorghum (Sorghum dochna)

The stem juice yield is a key factor that influences both the biological and economic production of sweet sorghum [Sorghum dochna (Forssk.) Snowden]. To elucidate upon the genetic basis of the stem juice yield, an F₅ population developed from a cross between the low juice yielding Xinliang52 (XL52) and high juice yielding W455 lines, were used in a quantitative trait locus (QTL) analysis. A main effect of the QTL controlling stem juice yield was separated with an SSR marker called Xtxp97, which explained 46.7% of the phenotypic variance. In addition, F₅ and F₆ populations were constructed with XL52 and W452 as the parents to further verify the QTLs, and a significant correlation was found between the juice yield trait and the Xtxp97 marker. Based on the progeny tests of 29 recombinants, QJy-sbi06 was located in a region of about 21.2 kb on chromosome 6, where a candidate gene encoding an NAC transcription factor (sobic.006G147400) was identified. Combining the different population association analysis and sequencing technology showed that XL52 inserted a 1.8 kb transposon in the NAC to directly interrupt and inactivate the juice yield gene. This study also demonstrated that the colour of the leaf midribs was controlled by a single gene and was significantly positive correlated with juiciness (r = 0.784, P < 0.01). These results could lay the foundation for map-based cloning of QJy-sbi06 and provide genes or QTLs for breeding sorghum lines with a high juice yield and quality.

Comparative Analysis Reveals Changes in Some Seed Properties in Amaranth Mutant Variety ‘Zobor’ (A. hypochondriacus × A. hybridus)

The aim of our long-term research program is to improve the quality and quantity of amaranth production through mutation breeding using γ-radiation. In this paper, we present the characterization of the new variety ‘Zobor’ of A. hypochondriacus × A. hybridus developed by radiation-induced mutagenesis of hybrid K-433. Multiyear phenotypic characterization of an important yield parameter (1000-seed weight) showed that the studied mutant variety ‘Zobor’ has an advantage in seed weight over the nonirradiated control seeds of K-433 with predictable performance of this yield trait. ‘Zobor’ exhibited changes in seed morphometric parameters, starch particle size, and pasting properties with no change in amylose content and swelling power. Moreover, the seeds of ‘Zobor’ showed the significantly highest folate content among selected amaranth varieties. The mutant variety could, therefore, be interesting for the development of functional foods and as a low-management crop, attractive for cultivation in Europe.

Quantifying Cereal Productivity on Sandy Soil in Response to Some Soil-Improving Cropping Systems

Little information is available on the effect of soil-improving cropping systems (SICS) on crop productivity on low fertility sandy soils although they are increasingly being used in agriculture in many regions of the world due to the growing demand for food. The study aimed at quantifying the effect of four soil-improving cropping systems applied on sandy soil on cereal productivity (yield of grain and straw and plant height) in a 4-year field experiment conducted in Poland with spring cereal crops: oat (2017), wheat (2018), wheat (2019), and oat (2020). The experiment included the control (C) and the following SICS: liming (L), leguminous catch crops for green manure (LU), farmyard manure (M), and farmyard manure + liming + leguminous catch crops for green manure together (M + L + LU). To quantify the effect of the SICS, classic statistics and the Bland–Altman method were used. It was shown that all yield trait components significantly increased in the last study year (2020) under SICS with M and M + L + LU. All yield trait components were significantly lower in the dry years (2018–2019) than in the wet years (2017 and 2020). The relatively large rainfall quantity in May during intensive growth at shooting and the scarce precipitation during later growth in the dry year 2019 resulted in a significantly greater straw yield compared to the other dry year 2018. The values of Bland–Altman bias (mean difference between the particular SICS and the control) varied (in kg m−2) from −0.002 for LU in 2019 to 0.128 for M and 0.132 for M + L + LU in 2020. The highest limits of agreement (LoA) were in general noted for all yield trait components (the least even yield) in the most productive SICS including M and M + L + LU in the wet year 2020. The Bland–Altman ratio (BAR) values indicate that quantification of the effects of all soil-improving practices was most uncertain in the dry year 2018 for the grain yield and in the wet year 2020 for the straw yield and much less uncertain for the plant height in all SICS and study years. The results of this study provide helpful information about the effect of the SICS on the different yield trait components depending on the period of their application and weather conditions prevailing during the growing season.

Selection criteria for yield in safflower (Charthamus tinctorius L.) genotypes under rainfed conditions

This research was conducted on 20 safflower genotypes and lasted 3 years (2014-2016) in the Central Anatolia Region of Turkey. The experiments were conducted in randomized block design with four replications. The relationships among yield 9 other traits in safflower genotypes were investigated. As the average of three years, the greatest seed yield (SY) was obtained from genotype G5 (PI 451952) with 3156.3 kg·ha-1. It was followed by genotypes G4 (PI 525458) and G9 (PI 306686) with 3013.2 and 2977.1 kg·ha-1, respectively. Among the standard cultivars, the greatest seed yield (2750.4 kg·ha-1) was obtained from the Dinçer cultivar. The greatest oil content (OC) was obtained from the genotype G11 (PI 537665) with 36.5%. It was followed by the genotypes G9 (PI 306686) (35.4%), G6 (PI 537598) (35.4%) and G14 (PI 560169) (35.3%). Oil contents varied between 29.1-36.5%. Yield-trait relationships were assessed through both correlation analysis and GT (Genotype by Trait) biplot analysis. Based on the results of the two approaches, plant height (PH), number of branches (NB), number of heads (NH) and thousand-seed weight (TSW) were identified as the most significant selection criteria for yield from safflower. The combined use of correlation and biplot analysis in the assessment of relationships among the traits improved the chance for success.

Genetic diversity and trait profiles of some Amaranthus genotypes

Knowledge of the pattern of trait variation among accessions, and the trait profiles of the accessions is crucial for improvement of a crop. Twenty-one Amaranthus accessions were evaluated in 2018 and 2019 to investigate the extent of genotypic diversity among the amaranth accessions and their trait profiles. Data were subjected to analysis of variance, and correlation and principal component analyses. Taking stem weight (SWT) as the yield, the accession × yield-trait combination (GYT) biplot was employed to investigate the trait profiles of the accessions. Accession, year, and accession × year mean squares were significant (P≤0.05/0.01) for most of the measured traits. The first three principal components explained 88.18% of observable variation among the accessions and identified plant height (PHT), number of leaves per plant (NOL), and root weight (RWT) as the major contributors. Significant (P≤0.01) correlation was observed in the association of SWT with NOL, TBM, and RWT. Accessions NGB00019 and NGB00061 were associated with the sector containing all the YT combinations considered. However, NGB00019 was identified as the best combiner of yield with other traits. Further studies involving more traits should determine the trait profiles of the remaining accessions.

Selection of Wheat Ideotype Based on Multiple Traits using Genotype by Yield-Trait Approach

In plant breeding, a novel genotype-by-yield trait (GYT) biplot approach was introduced to select superior genotypes based on multiple traits. The present study demonstrated the application of the GYT biplot model to evaluate the superior wheat advanced lines from a panel of 24 genotypes to select the ideotype for end users. Results show that the genotype-by-trait (GT) biplot covered 57% of the total variation of the data to reveal that grain yield was strongly associated with 1000-grain weight and grain width. In contrast, the GYT biplot explained 90.2% of the total variation which was significantly much higher than GT biplot. According to tester vector view of GYT biplot almost all the yield trait combinations were associated with each other at different degree of association; whereas the genotypes present within the acute angles of tester vectors (yield trait combinations) had the trait profile contributed positively towards grain yield. The polygon biplot of GYT had eight sectors, out of which only three had the yield trait combinations. The eight genotypes were the polygon vertex among which the advanced line DF1906 of first sector was designated as the best genotype for spike length, number of spikelets per spike, grain weight per spike and number of grains per spike. Additionally, the DF1912 of second sector was early maturing coupled with high 1000-grain weight while DF1917 of third sector had short stature and gave the highest harvest index. The average tester coordination (ATC) biplot grouped 13 genotypes as superior and nine as inferior genotypes and recommended two advanced lines DF1912 and DF1917 as ideotype based on balanced traits profile. These findings strengthened the argument that the GYT biplot analysis is better than other selection indices and guaranteed the selection of superior genotypes and rejection of inferior ones based on multiple traits yield combinations. © 2021 Friends Science Publishers

Soybean productivity, stability, and adaptability through mixed model methodology

ABSTRACT: The genotype × environment (G×E) interaction plays an essential role in phenotypic expression and can lead to difficulties in genetic selection. Thus, the present study aimed to estimate genetic parameters and to compare different selection strategies in the context of mixed models for soybean breeding. For this, data referring to the evaluation of 30 genotypes in 10 environments, regarding the grain yield trait, were used. The variance components were estimated through restricted maximum likelihood (REML) and genotypic values were predicted through best linear unbiased prediction (BLUP). Significant effects of genotypes and G×E interaction were detected by the likelihood ratio test (LRT). Low genotypic correlation was obtained across environments, indicating complex G×E interaction. The selective accuracy was very high, indicating high reliability. Our results showed that the most productive soybean genotypes have high adaptability and stability.

High-Throughput Genotyping of Resilient Tomato Landraces to Detect Candidate Genes Involved in the Response to High Temperatures

The selection of tolerant varieties is a powerful strategy to ensure highly stable yield under elevated temperatures. In this paper, we report the phenotypic and genotypic characterization of 10 tomato landraces to identify the best performing under high temperatures. The phenotyping of five yield-related traits allowed us to select one genotype that exhibits highly stable yield performances in different environmental conditions. Moreover, a Genotyping-by-Sequencing approach allowed us to explore the genetic variability of the tested genotypes. The high and stable yielding landrace E42 was the most polymorphic one, with ~49% and ~47% private SNPs and InDels, respectively. The effect of 26,113 mutations on proteins’ structure was investigated and it was discovered that 37 had a high impact on the structure of 34 proteins of which some are putatively involved in responses to high temperatures. Additionally, 129 polymorphic sequences aligned against tomato wild species genomes revealed the presence in the genotype E42 of several introgressed regions deriving from S. pimpinellifolium. The position on the tomato map of genes affected by moderate and high impact mutations was also compared with that of known markers/QTLs (Quantitative Trait Loci) associated with reproductive and yield-related traits. The candidate genes/QTLs regulating heat tolerance in the selected landrace E42 could be further investigated to better understand the genetic mechanisms controlling traits for high and stable yield trait under high temperatures.