Plant species identification using fecal DNAs from red-eared slider and Reeves’ pond turtle in agricultural canals for rural ecosystem conservation

Fecal DNA samples from the red-eared slider and Reeves’ pond turtle, suspected pests of lotus root paddies, were used to identify the plant species eaten by these turtles in order to develop a strategy for rural ecosystem conservation. The fecal samples were obtained from young and adult individuals (mostly female) of both species living in agricultural canals surrounding lotus root paddies in Tokushima Prefecture, Japan. The samples were screened for the presence or absence of DNA from nine plant species using PCR and plant species-specific primers for the rbcL gene of chloroplast DNA. In the red-eared slider, our analysis identified seven plant species in the fecal DNA samples of adults and three plant species in those of young individuals. In Reeves’ pond turtle, our analysis identified two plant species from adult fecal samples and one species from those of young individuals. Thus, adult red-eared sliders consume a greater range of plants than young red-eared sliders or Reeves’ pond turtles. Both turtle species, independently of age, consumed lotus plants and were likely to cause feeding damage to lotus roots. Considering the plant species detected in adult red-eared sliders and these plant habitats, we suggest that this adult turtle is likely to travel between the agricultural canals and the lotus root paddies. These findings will help the development of strategies for preventing damage to lotus roots by these turtles; furthermore, they indicate that fecal DNA analysis will be applicable to investigation of the feeding habits of other animal species.     

Modeling the water and nitrogen transports in a soil–paddy–atmosphere system using HYDRUS-1D and lysimeter experiment

Efficient water and fertilizer use is of paramount importance both in rain-fed and irrigated rice cultivation systems to tread off between the crop water demand during the dry spell and the fertilizer leaching. This lysimeter study on paddy in a lateritic sandy loam soil of the eastern India, to simulate the water and solute transports using the HYDRUS-1D model, reveals that this model could very well simulate the soil depth-specific variations of water pressure heads and nitrogen (N) concentrations with the efficiency of >86 and 89%, respectively. The change in the level of water ponding depth did not have a significant effect on the time to peak and the temporal variability of N concentration in the bottom soil layer. The lysimeter-scale water balance analysis indicated that the average deep percolation loss and crop water use were 35.01 ± 2.03 and 39.74 ± 1.49% of the total water applied during the crop growth period, respectively. Similarly, the amount of N stored in the plant and lost through soil storage, deep percolation, and other losses (mineralization, denitrification, and gaseous N loss to the atmosphere through plant leaves) were 1.60 ± 0.16, 0.17 ± 0.04, 12.00 ± 0.48, and 86.23 ± 0.41% of the total applied nitrogen, respectively. The simulation results reveal that a constant ponding depth of 3 cm could be maintained in paddy fields to reduce the N leaching loss to 7.5 kgN/ha.     

Predicting adoption of double cropping in paddy fields of northern Iran: a comparison of statistical methods

Factors affecting the adoption of double cropping were explored in rice farms of Fouman County of Guilan Province in northern Iran using artificial neural networks (ANNs), linear discriminant analysis (LDA), and logistic regression (LGR). Eleven factors (age, education, occupation, family size, type of farm ownership, distance to the agricultural service center, attending agricultural extension courses, use of financial resources and bank loans, number of domestic animals, area under cultivation, and social participation) were examined. An additional objective was to compare the ability of the three models in predicting the adoption of double cropping. ANNs showed an overall predictive power of 89.8%. LDA showed an overall predictive power of 83.2%, with seven of the eleven independent variables being effective on the adoption of double cropping. LGR indicated an overall predictive power of 87.6%, with eight of the eleven independent variables being effective on the adoption of double-rice cropping. ANNs showed higher power than LGR and LDA in predicting the adoption of double cropping. Based on all three methods used for analysis, the most important independent variables were social participation and area under cultivation (positive factors) as well as distance to the agricultural service center and family members (negative factors). Establishment of cooperatives or other kinds of farmers’ associations to foster social participation could motivate adoption of double cropping, particularly among small-scale farmers. To increase agricultural services, more local centers should be created in rural areas. The government should promote double cropping through effective incentives and technology transfer to small-scale farmers.     

Updating the elite rice variety Kongyu 131 by improving the <Emphasis Type="Italic">Gn1a</Emphasis> locus

Background

Kongyu 131 is an elite japonica rice variety of Heilongjiang Province, China. It has the characteristics of early maturity, superior quality, high yield, cold tolerance and wide adaptability. However, there is potential to improve the yield of Kongyu 131 because of the relatively few grains per panicle compared with other varieties. Hence, we rebuilt the genome of Kongyu 131 by replacing the GRAIN NUMBER1a (Gn1a) locus with a high-yielding allele from a big panicle indica rice variety, GKBR. High-resolution melting (HRM) analysis was used for single nucleotide polymorphism (SNP) genotyping.

Results

Quantitative trait locus (QTL) analysis of the BC₃F₂ population showed that the introgressed segment carrying the Gn1a allele of GKBR significantly increased the branch number and grain number per panicle. Using 5 SNP markers designed against the sequence within and around Gn1a, the introgressed chromosome segment was shortened to approximately 430 Kb to minimize the linkage drag by screening recombinants in the target region. Genomic components of the new Kongyu 131 were detected using 220 SNP markers evenly distributed across 12 chromosomes, suggesting that the recovery ratio of the recurrent parent genome (RRPG) was 99.89%. Compared with Kongyu 131, the yield per plant of the new Kongyu 131 increased by 8.3% and 11.9% at Changchun and Jiamusi, respectively.

Conclusions

To achieve the high yield potential of Kongyu 131, a minute chromosome fragment carrying the favorable Gn1a allele from the donor parent was introgressed into the genome of Kongyu 131, which resulted in a larger panicle and subsequent yield increase in the new Kongyu 131. These results indicate the feasibility of improving an undesirable trait of an elite variety by replacing only a small chromosome segment carrying a favorable allele.

     

Heterosis and combining ability of seven maize germplasm populations

Understanding the combining ability and heterosis of available germplasm is a prerequisite for successful maize improvement and breeding. The objectives of this study were to analyze the combining ability and heterosis of seven representative maize germplasm populations, and further, to evaluate their potential utility in germplasm improvement. A total of 21 crosses were made among these seven populations in a complete diallel without reciprocals. The parental populations and 21 crosses were evaluated for days to silking (DS), ear height (EH), and grain yield (GY) in the Northeast and Yellow and Huai River maize growing areas in China in 2012. Csyn5, Csyn7, Cpop.11, and Cpop.12 had desirable general combining ability (GCA) effects for DS and EH in both the Northeast China mega-environment (NCM) and the Yellow and Huai River Regions of China mega-environment (YHCM). Cpop.11 possessed a favorable GCA effect for GY in the NCM, as did Csyn5, Cpop.17, and Cpop.18 in the YHCM. Csyn6 and Csyn7 exhibited tremendous yield-enhancing potential in both mega-environments. Additionally, six combinations including Csyn7 × Csyn6, Csyn5 × Csyn6, Cpop.11 × Cpop.18, Cpop.12 × Cpop.17, Csyn7 × Cpop.17, and Csyn5 × Csyn7 exhibited better specific combining ability effects for GY, yield performance, and mid-parent heterosis in the appropriate mega-environment. These results indicated that the seven populations would be very useful for the improvement of related agronomic traits, and the six candidate combinations possessed great potential for further improvement and utilization.     

Improved genetic parameter estimations in zoysiagrass by implementing post hoc blocking

Randomized complete block (RCB) design is the most widely used experimental design in biological sciences. As number of treatments increases, the block size become larger and it looses the capacity to control the variance within block, which is its original purpose. A method known as post hoc blocking could be used in these cases to improve the genetic parameter estimation and thus obtain an unbiased assessment of the performance of a given treatment. In trufgrass breeding, as other breeding program, this is a common challenge. The goal of this study was to test the capacity of different post hoc blocking designs to improve the genetic parameter estimation of zoysiagrass (Zoysia spp.). We evaluated two post hoc blocking designs; row–column (R–C) and incomplete block (IB) designs on five genotype trials located in Florida. The results showed that post hoc R–C design had superior model fitting than both the original RCB and the post hoc IB designs when studied at the single measurement level and at the site level. The narrow-sense heritability (0.24–0.40) and the genotype-by-measurement correlation (0.57–0.99) did not change significantly when R–C was compared to the original RCB design. The ranking of the top performing genotypes changed considerably when comparing RCB to R–C design, but the degree depended on the location analyzed. We conclude that the change in the ranking of the top (potentially select individuals) is coming from the better control of intra-block environmental variation, and this could potentially have a significant impact on the breeding selection process.     

Association mapping reveals loci associated with multiple traits that affect grain yield and adaptation in soft winter wheat

Genome-wide association studies (GWAS) are useful to facilitate crop improvement via enhanced knowledge of marker-trait associations (MTA). A GWAS for grain yield (GY), yield components, and agronomic traits was conducted using a diverse panel of 239 soft red winter wheat (Triticum aestivum) genotypes evaluated across two growing seasons and eight site-years. Analysis of variance showed significant environment, genotype, and genotype-by-environment effects for GY and yield components. Narrow sense heritability of GY (h ²  = 0.48) was moderate compared to other traits including plant height (h ²  = 0.81) and kernel weight (h ²  = 0.77). There were 112 significant MTA (p < 0.0005) detected for eight measured traits using compressed mixed linear models and 5715 single nucleotide polymorphism markers. MTA for GY and agronomic traits coincided with previously reported QTL for winter and spring wheat. Highly significant MTA for GY showed an overall negative allelic effect for the minor allele, indicating selection against these alleles by breeders. Markers associated with multiple traits observed on chromosomes 1A, 2D, 3B, and 4B with positive minor effects serve as potential targets for marker assisted breeding to select for improvement of GY and related traits. Following marker validation, these multi-trait loci have the potential to be utilized for MAS to improve GY and adaptation of soft red winter wheat.     

Characterization of resistance to the wheat stem sawfly in spring wheat landrace accessions from targeted geographic regions of the world

Plant landraces have long been recognized as potential gene pools for biotic and abiotic stress-related genes. This research used spring wheat landrace accessions to identify new sources of resistance to the wheat stem sawfly (WSS) (Cephus cinctus Norton), an important insect pest of wheat in the northern Great Plains of North America. Screening efforts targeted 1409 accessions from six geographical areas of the world where other species of grain sawflies are endemic or where a high frequency of accessions possesses the resistance characteristic of solid stems. Resistance was observed in approximately 14% of accessions. Half of the lines displayed both antixenosis and antibiosis types of resistance. Among the resistant accessions, 41% had solid or semi-solid stems. Molecular genetic screening for haplotypes at the solid stem QTL, Qss.msub.3BL, showed that 15% of lines shared the haplotype derived from ‘S-615’, the original donor of the solid stem trait to North American germplasm. Other haplotypes associated with solid stems were also observed. Haplotype diversity was greater in the center of origin of wheat. Evaluation of a representative set of resistant landrace accessions in replicated field trials at four locations over a three year period identified accessions with potential genes for reduced WSS infestation, increased WSS mortality, and increased indirect defense via parasitoids. Exploitation of distinct types of plant defense will expand the genetic diversity for WSS resistance currently present in elite breeding lines.     

Using unsupervised learning techniques to assess interactions among complex traits in soybeans

Soybean yield components and agronomic traits are connected through physiological pathways that impose tradeoffs through genetic and environmental constraints. Our primary aim is to assess the interdependence of soybean traits by using unsupervised machine learning techniques to divide phenotypic associations into environmental and genetic associations. This study was performed on large scale, jointly analyzing 14 quantitative traits in a large multi-parental population designed for genetic studies. We collected phenotypes from 2012 to 2015 from a soybean nested association panel with 40 families of approximately 140 individuals each. Pearson and Spearman correlations measured phenotypic associations. A multivariate mixed linear model provided genotypic and environmental correlations. To evaluate relationships among traits, the study used principal component and undirected graphical models from phenotypic, genotypic, and environmental correlation matrices. Results indicate that high phenotypic correlation occurs when traits display both genetic and environmental correlations. In genetic terms, length of reproductive period, node number, and canopy coverage play important roles in determining yield potential. Optimal grain yield production occurs when the growing environment favors faster canopy closure and extended reproductive length. Environmental associations found among yield components give insight into the nature of yield component compensation. The use of unsupervised learning methods provides a good framework for investigating interactions among various quantitative traits and defining target traits for breeding.     

Identification and validation of root length QTLs for water stress resistance in hexaploid wheat (<Emphasis Type="Italic">Titicum aestivum</Emphasis> L.)

Thorough understanding of the genetic mechanisms governing drought adaptive traits can facilitate drought resistance improvement. This study was conducted to identify chromosome regions harbouring QTLs contributing for water stress resistance in wheat. A RIL mapping population derived from a cross between W7984 (Synthetic) and Opata 85 was phenotyped for root length and root dry weight under water stress and non-stress growing conditions. ANOVA showed highly significant (p ≤ 0.01) variation among the RILs for both traits. Root length and root dry weight showed positive and significant (p ≤ 0.01) phenotypic correlation. Broad sense heritability was 86% for root length under stress and 65% for root dry weight under non-stress conditions. A total of eight root length and five root dry weight QTLs were identified under both water conditions. Root length QTLs Qrln.uwa.1BL, Qrln.uwa.2DS, Qrln.uwa.5AL and Qrln.uwa.6AL combined explained 43% of phenotypic variation under non-stress condition. Opata was the source of favourable alleles for root length QTLs under non-stress condition except for Qrln.uwa.6AL. Four stress specific root length QTLs, Qrls.uwa.1AS, Qrls.uwa.3AL, Qrls.uwa.7BL.1 and Qrls.uwa.7BL.2 jointly explained 47% of phenotypic variation. Synthetic wheat contributed favourable alleles for Qrls.uwa.1AS and Qrls.uwa.3AL. Two stable root dry weight QTLs on chromosomes 4AL and 5AL were consistently found in both water conditions. Three validation populations were developed by crossing cultivars Lang, Yitpi, and Chara with Synthetic W7984 to transfer two of the QTLs identified under stress condition. The F_2.3 and F_3.4 validation lines were phenotyped under the same level of water stress as RILs to examine the effect of these QTLs. There were 13.5 and 14.5% increases in average root length due to the inheritance of Qrls.uwa.1AS and Qrls.uwa.3AL, respectively. The result indicated that closely linked SSR markers Xbarc148 (Qrls.uwa.1AS) and Xgwm391 (Qrls.uwa.3AL) can be incorporated into MAS for water stress improvement in wheat.