Genetic Variability and Correlation of Biochemical and Sensory Characteristics of Coffee

Organoleptic and biochemical attributes in the coffee bean determine the final cup quality of coffee which is a critical factor in the price determination of coffee in the market. The study aimed at determining the genetic variability of the green coffee bean. The trial sites were located at Siaya and Busia counties in Kenya. Nineteen different genotypes were established and included Arabusta coffee hybrids, backcrosses of Arabica to tetraploid Robusta, Arabica coffee, Robusta coffee, and Arabusta coffee. Randomized Complete Block Design with three replications in each site was used in conducting the experiment. The coffee beans were harvested in the year 2018 and extraction and calculation of sucrose, trigonelline, caffeine, and chlorogenic acids was carried using the recommended methods. The cupping procedure involved the use of five judges in assessing the flavor, aroma, balance, overall standard, acidity, body, and aftertaste of the roasted coffee beans. The sensory evaluation used the Specialty Coffee Association (SCA) method. There were significant variations recorded for the traits that were measured. All the traits were highly heritable registering values of > 50% for heritability whereby, caffeine and oil were highly heritable traits with 90.8% and 88.9% respectively. Oil had a high phenotypic coefficient of variation, genotypic variation, and response values when compared to the other traits. All the organoleptic traits were positively correlated with sucrose, trigonelline, and oil but the correlation with caffeine and chlorogenic acids was negative. The genotypic effects contributed largely to the high heritability recorded with a low influence from the environmental factors.

Predicting Physical Appearance from DNA Data—Towards Genomic Solutions

The idea of forensic DNA intelligence is to extract from genomic data any information that can help guide the investigation. The clues to the externally visible phenotype are of particular practical importance. The high heritability of the physical phenotype suggests that genetic data can be easily predicted, but this has only become possible with less polygenic traits. The forensic community has developed DNA-based predictive tools by employing a limited number of the most important markers analysed with targeted massive parallel sequencing. The complexity of the genetics of many other appearance phenotypes requires big data coupled with sophisticated machine learning methods to develop accurate genomic predictors. A significant challenge in developing universal genomic predictive methods will be the collection of sufficiently large data sets. These should be created using whole-genome sequencing technology to enable the identification of rare DNA variants implicated in phenotype determination. It is worth noting that the correctness of the forensic sketch generated from the DNA data depends on the inclusion of an age factor. This, however, can be predicted by analysing epigenetic data. An important limitation preventing whole-genome approaches from being commonly used in forensics is the slow progress in the development and implementation of high-throughput, low DNA input sequencing technologies. The example of palaeoanthropology suggests that such methods may possibly be developed in forensics.

Line × tester Study in Bread Wheat (Triticum aestivum L.) for Important Biochemical and Morphological Traits

: Using line × tester analysis, the current research analyses parental genotypes and their combinations in normal conditions and identifies the genes influencing yield characteristics. In the present study, 15 diverse genotypes, including 10 lines, 5 testers, and 50 F1s hybrids, were evaluated for 13 morphological and 2 biochemical traits. A suitable location was taken to study the effect of 15 characters. The results exposed that ability mean squares were significant for all studied additive and non-additive components. In this direction, the general combining ability of PBW-343, DBW-39, K-402, K-1317, KRL-210, and K-68 were higher than the remaining parents. For morphological traits like yield, the top five crosses were described based on SCA effects, namely, HD-3086 × HD-3171, K-402 × K-9107, K-1317 × K-9107, HD-2967 × K-0307 and K-402 × K-68 in F1 generation. In addition, the high value of heritability was estimated for plant height (77.32%), spike length (32.26%), biological yield/plant (59.52%), and grain yield/plant (68.76%). However, the moderate values of heritability were estimated for days to maturity (22.78%) and phenol color reaction (18.00%). The higher genetic advance was not found for recorded characters; however, a moderate genetic advance was recorded for grain yield per plant (13.15%) and harvest index (11.72%). High heritability coupled with moderate genetic advance was recorded for two characters grain yield per plant and harvest index in F1 and F2 generations.

High-Density Single Nucleotide Polymorphisms Genetic Map Construction and Quantitative Trait Locus Mapping of Color-Related Traits of Purple Sweet Potato [Ipomoea batatas (L.) Lam.]

Flesh color (FC), skin color (SC), and anthocyanin content (AC) are three important traits being used for commodity evaluation in purple-fleshed sweet potato. However, to date, only a few reports are available on the inheritance of these traits. In this study, we used a biparental mapping population of 274 F1 progeny generated from a cross between a dark purple-fleshed (Xuzishu8) and white-fleshed (Meiguohong) sweet potato variety for genetic analyses. Correlation analysis showed a significant positive correlation among AC, SC, and FC. Medium-to-high heritability was observed for these traits. We detected single nucleotide polymorphisms (SNPs) by specific length amplified fragment sequencing (SLAF-seq) with the average sequencing depth of 51.72 and 25.76 for parents and progeny, respectively. Then we constructed an integrated genetic map consisting of 15 linkage groups (LGS) of sweet potato spanning on 2,233.66 cm with an average map distance of 0.71 cm between adjacent markers. Based on the linkage map, ten major quantitative trait loci (QTLs) associated to FC, SC, and AC were identified on LG12 between 0 and 64.97 cm distance, such as one QTL for SC and FC, respectively, which explained 36.3 and 45.9% of phenotypic variation; eight QTLs for AC, which explained 10.5–28.5% of the variation. These major QTLs were highly consistent and co-localized on LG12. Positive correlation, high heritability, and co-localization of QTLs on the same LG group confirm the significance of this study to establish a marker-assisted breeding program for sweet potato improvement.

Estimation of Genetic Variability, Heritability and Genetic Advance in Potato (Solanum tuberosum L.) Genotypes for Tuber Yield and Yield Related Traits

Potato is a high potential food security crop in Ethiopia. Genetic variability is the basis of all crop improvement programs. The study was conducted at Adet in 2018 with the objective of assessing the extent and pattern of genetic variability of potato genotypes for yield and yield related traits. A total of 36 potato genotypes were evaluated for 18 quantitative traits in simple lattice design. The analysis of variance revealed that highly significant difference among the tested potato genotypes for all quantitative traits except stem number per hill. The phenotypic coefficient of variation was ranged from 4.56 to 56.01% (for specific gravity and unmarketable tuber yield ha-1 respectively) and the genotypic coefficient of variation was ranged from 2.32 to 40.66% (specific gravity and late blight severity percentage respectively). Days to attain 50% emergence, leaf area index, number of marketable and total tubers per plant, marketable and total tuber yield ha-1, and late blight severity percentage showed high heritability and high genetic advance as percent of mean. Most of the traits had high phenotypic coefficient of variation and genotypic coefficient of variation; and coupled high heritability with high genetic advance as percent of mean. Traits having high heritability and high genetic advance as percent of means is effective for simple selection.

Environmental Variability of Thousand Kernel Weight in Maize Hybrids of Different Maturity Groups

Thousand kernel weight (TKW) is an important yield component trait affected by the environmental conditions. This study’s objectives were to determine an environmental variability for the TKW in 32 maize hybrids, sorted in four FAO maturity groups (FAO300, 400, 500 and 600), and to compare 12 environments in Croatia (six locations in two years) according to the joint linear regression and stability analyses across the maturity groups. In general, the effects of the environment, genotype, and their interaction (GEI) were significant. A three-factor ANOVA revealed the greatest and highly significant year effect, while the location effect was non-significant across all four FAO groups. A stability analysis did not detect any preferences with regard to the locations and trends across the FAO groups. It indicates that all locations in the Pannonian region included in this study were suitable for an evaluation of the TKW in maize genotypes belonging to all maturity groups. The TKW seems to be an appropriate yield-component trait for maize breeding due to a high heritability and linear GEI nature.

The Effects of Siblings and Twin Testosterone Transfer on Autistic Traits

Background: Having twin and non-twin siblings might influence autistic traits both prenatally and postnatally. The twin testosterone transfer hypothesis suggests that girls with a twin brother are exposed to higher levels of prenatal testosterone than girls with a twin sister. Prenatally, increased testosterone exposure could masculinize neural development and increase autistic traits. Postnatally, siblings may provide example behaviour, which could reduce autistic traits. Methods: We studied pre- and postnatal influences of twin and non-twin siblings on (mother and teacher-reported) autistic traits in 7,714 dizygotic twins. We examined the effect of gender of the proband child and of the siblings. We fitted regression models (for boys and girls separately) with as predictors sex of co-twin and having older and/or younger siblings. Results: Prenatally, girls’ (mother-reported) autistic traits were slightly lower for those with a twin brother than those with a twin sister, β = -.08, p = .001. This difference was not replicated in teacher-reported autistic traits, β = .01, p = .734. Boys’ (mother and teacher-reported) autistic traits were not related to the sex of their cotwin, p’s > .05. Postnatally, girls’ teacher-reported autistic traits were slightly higher if they had an older brother, β = .07, p = .013. Other than this small effect, girls’ autistic traits were not related to having siblings. Likewise, boys’ autistic traits were not related to having siblings. Conclusions: We do not find increased autistic traits in girls with a twin brother compared to a twin sister. This finding contributes to the body of literature that rejects the twin testosterone transfer hypothesis. In all, we find little evidence for pre- and postnatal sibling influences. Besides, our findings suggest that parent reports on autistic traits in twins might be slightly biased. Our findings align with ASD’s high heritability and absence of shared-environmental influences.

Morpho-molecular Characterization of Maize Inbred Lines Accelerating Parental Selection for Hybridization

Characterization of genetic diversity is the foundation step for crop improvement, which provides a basis for analyzing combining ability and heterosis of inbred genotypes during a hybridization program. An investigation was carried out at the field laboratory of the Genetics and Plant Breeding department in Bangabandhu Sheikh Mujibur Rahman Agricultural University, to elucidate the genetic architecture by evaluating 12 morphological and 4 molecular (SSR) markers within 52 diverse S1 genotypes, and to assess the relationship of molecular and morphological GD. An almost equal amount of PCV and GCV coupled with high heritability and genetic advance for the traits cob weight (gm), NKPC, and NKPR lead to the selection of promising genotypes based on these characters. Correlation coefficient and scatter plot matrix established a positive and strong relationship of KL (mm), KW (mm), and KT (mm) with 100 kernel weight (gm) suggesting the importance of kernel morphology. Mahalanobis D2 statistics revealed the highest inter-cluster distance between I and II. The percentages of molecular variance within the population and among the population were 76% and 14 %, respectively. The optimum K-value was 5. Heatmap relying on molecular GD exposed MMIL-28, MMIL-54, and MMIL-96 as the most diverse lines. SHE analysis hypothesized the increase of richness and diversity over time. Less correlation between the divergence generated from morphological traits and molecular markers suggested that the morphological variation may be determined by environmental factors and also by genetic factors. A strategy for the effective selection of predicting parental lines for a future hybridization program was developed.

Exploring the Genetic Variability for Yield Attributing Traits among the Indigenous and Exotic Collection of Wheat in Cis-Himalayan Region of West Bengal, India

A field experiment was conducted at Instructional Farm, Uttar Banga Krishi Viswavidyalaya, during the 2018-19 rabi season to study the genetic components and genetic variability based on eleven number of quantitative traits in 254 bread wheat lines, which were collected from NBPGR, New Delhi. Analysis of variance for treatment showed high significance for all the traits except grain yield polt-1. Estimated GCV and PCV were high for awn length, peduncle length, plant height and AUDPC. Plant height (97.83), awn length (95.49), peduncle length (94.88), test weight (90.98), days to 50% flowering (87.66), number of grains spike-1 (70.33) and spike length (62.3) showed high heritability along with a high degree of genetic advance. Finally, 254 wheat accessions were grouped into three clusters based on the dendrogram analysis using the ward method.

GENETIC VARIABILITY FOR GRAIN NUTRIENTS CONTENT IN COASTAL RICE COLLECTIONS OF BANGLADESH

Overcoming malnutrition through biofortification breeding in rice is aimed to assist nutritional food security in Bangladesh. So to select parents for nutritional improvement, estimation and exploitation of mineral nutrients reserves of rice grain and their variability assessment in different genotypes is essential. Eighty-five (85) T. aman rice genotypes collected from different coastal regions of Bangladesh were evaluated at the Advanced Plant Breeding laboratory, GPB of BSMRAU to estimate the grain nutrients content and to elucidate their genetic variability among the genotypes. Considerable significant variation (0.1% level of probability) was noted among the genotypes for studied different grain nutrient contents and yield per hill. The mean values of N, P, K, Ca, Mg, Na, Zn, Fe, Cu, Mn and grain yield/ hill were 10788.24 mg/kg, 804.85 mg/kg, 3798.58 mg/kg, 13795.29 mg/kg, 2778.87 mg/kg, 3771.17 mg/kg, 7.25 mg/kg, 5.01 mg/kg, 1.05 mg/kg, 1.90 mg/kg and 433.29 g, respectively. Box and whisker plots analysis were done to represent data graphically for better understanding. Histogram was used to present the frequency distribution of genotypes for N, P, K, Ca, Mg, Na, Zn, Fe, Cu, Mg and Grain yield/hill content in 85 diverged rice genotypes All the traits had equality in genotypic and phenotypic variances with high heritability and high genetic advance which indicated preponderance of additive gene effects for these traits. The genotype R080 (Chinigura) contained the highest content of grain P, Fe and Cu. The R030 (Mota Dhan), R040 (Dudh Kalam) and R019 (Chikon Dhan) were noted for the highest Ca, Mg and Na content, respectively. The maximum N and Zn content were observed in R029 (Dudh Kolom) and R075 (Gopal Bogh), respectively. R083 (Lal Dhan) was marked for the highest grain yield/ hill and K content. Genetic variability parameters, heat map analysis and neighbor joining clustering methods indicated these genotypes including R079 can be considered for biofortification program and used as parents for the improvement of those grain nutrients in rice breeding.