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- Author or Editor: J.C. Tian x
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Lycopene content (LC) and soluble solid content (SSC) are important quality indicators for cherry tomatoes. This study attempted simultaneous analysis of inner quality of cherry tomato by Electronic nose (E-nose) using multivariate analysis. E-nose was used for data acquisition, the response signals were regressed by multiple linear regression (MLR) and partial least square regression (PLS) to build predictive models. The performances of the predictive models were tested according to root mean square and correlation coefficient (R2) in the training set and prediction set. The results showed that MLR models were superior to PLS model, with higher value of R2 and lower values of for RMSE firmness, pH, SSC, and LC. Together with MLR, E-nose could be used to obtain firmness, pH, soluble solid and lycopene contents in cherry tomatoes.
Two hundred and ninety F9 recombinant inbred lines (RILs) derived from the bread wheat cultivar Gaocheng 8901 and the waxy wheat cultivar Nuomai 1 were used in determining the high-molecular-weight glutenin subunit (HMW-GS) and waxy protein subunit combinations and their effects on the dough quality and texture profile analysis (TPA) of cooked Chinese noodles. Seven alleles were detected at Glu-1 loci. There were two alleles found at each of the Wx-A1, Wx-B1 and Wx-D1 loci. Eight allelic combinations were observed for HMW-GS, LMW-GS and waxy proteins, respectively. Both the 1/7+8/5+10 and 1/7+8/5+12 combinations contributed to dough elasticity, and the 1/7+8/5+10 combination also provided better TPA characteristics. Compared to Wx protein, HMW-GS was more important on dough alveogram properties. LMW-GS significantly affected springiness and cohesiveness; HMW-GS mainly affected the hardness; Wx×LMW-GS significantly affected the springiness, cohesiveness and chewiness; HMW-GS×Wx×LMW-GS mainly influenced the springiness and chewiness. But HMW-GS×LMW-GS only affected the spinginess. These indicated the TPA of noodles was significantly affected by the interactions between glutenin and Wx proteins.
The dwarf-male-sterile wheat is unique to China and has been improved by introducing good germplasm. In order to clear the subunits background of Dwarf-Male-Sterile wheat, sodium dodecyl sulphate polyacrylamide-gel electrophoresis (SDS-PAGE) was used to detect the high and low molecular weight glutenin subunits (HMW-GS and LMW-GS) compositions in BC1F1, F2 and F3 generations from Dwarf-Male-Sterile wheat. Twenty-five alleles and 49 HMW-GS compositions at the Glu-1 loci were detected in different generations. Null and subunit 1 were mainly existed at Glu-A1 , and 7 + 8 and 7 + 9 were primarily detected at Glu-B1 in different generations. Subunit combination 5 + 10 mainly appeared in BC1F1, while 2 + 12 major presented in F2 and F3 generations. HMW-GS compositions null, 7 + 8, 5 + 10 and null, 7 + 9, 5 + 10 showed higher frequencies than other banding patterns, followed by null, 14 + 15, 5 + 10 and null, 7 + 9, 2 + 12 combinations. In addition, some rare subunit combinations such as 14 + 15, 13 + 16, 17 + 18, 4 + 12, 2 + 10 and 5 + 12 were found in different generations. Eighteen alleles and 51 LMW-GS compositions at Glu-3 loci were found in different generations. Glu-A3 a and Glu-B3 d showed higher frequencies than others among three generations. There were mainly a, b, c alleles at Glu-D3 . Thirty, 31 and 14 different combinations were detected in BC1F1, F2 and F3 populations, respectively. There were some good combinations such as A3 d/ B3 h, A3 d/ B3 d/ D3 a, A3 b/ B3 b/ D3 a, A3 a/ B3 d/ D3 a for different quality characteristics. So some desirable subunit combinations could be selected from different generations and new cultivars with good quality under distinct subunits background should be bred from Dwarf-Male-Sterile wheat in future.
Starch is a product of photosynthetic activities in leaves. Wheat yields largely depend on photosynthetic carbon fixation and carbohydrate metabolism in flag leaves. The mapping of quantitative trait loci (QTLs) associated with flag leaf starch content (FLSC) in wheat (Triticum aestivum L.) was completed using unconditional and conditional QTL analyses. The FLSC of this population during the early grain-filling stage was measured at six stages in six environments. Combining unconditional and conditional QTL mapping methods, eight unconditional QTLs and nine conditional QTLs were detected, with five QTLs identified as unconditional and conditional QTLs. Four unconditional QTLs (i.e. qFLS-1B, qFLS-1D-1, qFLS-4A, and qFLS-7D-1) and one conditional QTL (i.e. qFLS-3A-1) were identified in two of six environments. Two QTLs (qFLS-1D-2 and qFLS-7D-1), which significantly affected the FLSC, were identified using the unconditional QTL mapping method, while three QTLs (i.e. qFLS-1A, qFLS-3A-1, and qFLS-7D-1) were detected using the conditional QTL mapping method. Our findings provide new insights into the genetic mechanism and regulatory network underlying the diurnal FLSC in wheat.
This study aimed to clarify the genetic mechanisms behind wheat flour color. Flour colorrelated traits (L*, a*, and b*) and polyphenol oxidase (PPO) activity are important parameters that influence the end-use quality of wheat. Dissecting the genetic bases and exploring important chromosomal loci of these traits are extremely important for improving wheat quality. The diverse panel of 205 elite wheat varieties (lines) was genotyped using a highdensity Illumina iSelect 90K single-nucleotide polymorphisms (SNPs) assay to disclose the genetic mechanism of flour color-related traits and PPO activity. In 2 different environments and their mean values (MV), 28, 30, 24, and 12 marker-trait associations (MTAs) were identified for L*, a*, b* traits, and PPO activity, respectively. A single locus could explain from 5.52% to 20.01% of the phenotypic variation for all analyzed traits. Among them, 5 highly significant SNPs (P ≤ 0.0001), 11 stable SNPs (detected in all environments) and 25 multitrait MTAs were identified. Especially, BS00000020_51 showed pleiotropic effects on L*, a*, and b*, and was detected in all environments with the highest phenotypic contribution rates. Furthermore, this SNP was also found to be co-associated with wheat grain hardness, ash content, and pasting temperature of starch in previous studies. The identification of these significantly associated SNPs is helpful in revealing the genetic mechanisms of wheat colorrelated traits, and also provides a reference for follow-up molecular marker-assisted selection in wheat breeding.
Protein and starch are important in wheat quality and yield. To understand the genetic relationship between protein and starch at the quantitative trait locus (QTL)/gene level, 168 doubled haploid (DH) lines were used at three locations over 2 years. The QTLs for proteinfraction contents and starch content were analyzed by unconditional and conditional QTL mapping. We detected 17 unconditional additive QTLs (four albumin QTLs, three globulin QTLs, six gliadin QTLs, four glutenin QTLs) controlling protein-fraction contents. We detected 19 conditional QTLs (five albumin QTLs, three globulin QTLs, five gliadin QTLs, six glutenin QTLs) based on starch content. Of these QTLs, QAlu1B, QGlo6A, QGli1B, QGli7A, QGlu1B and QGlu1D increased the protein-fraction contents independent of the starch content. These QTLs could regulate the usual inverse relationship between protein and starch in wheat seeds. The results could possibly be used in the simultaneous improvement of grain protein and starch content in wheat breeding.
The aphid Sitobion avenae F. is one of the most harmful pests of wheat growth in the world. A primary field screening test was carried out to evaluate the S. avenae resistance of 527 wheat landraces from Shaanxi. The results indicated that 25 accessions (4.74%) were resistant to S. avenae in the three consecutive seasons, of which accession S849 was highly resistant, and seven accessions were moderately resistant. The majority of S. avenae resistant accessions come from Qinling Mountains. Then, the genetic variability of a set of 33 accessions (25 S. avenae resistant and 8 S. avenae susceptible) originating from Qinling Mountains have been assessed by 20 morphological traits and 99 simple sequence repeat markers (SSRs). Morphological traits and SSRs displayed a high level of genetic diversity within 33 accessions. The clustering of the accessions based on morphological traits and SSR markers showed significant discrepancy according to the geographical distribution, resistance to S. avenae and species of accessions. The highly and moderately resistant landrace accessions were collected from the middle and the east part of Qinling Mountains with similar morphology characters, for example slender leaves with wax, lower leaf area, and high ear density. These S. avenae resistant landraces can be used in wheat aphid resistance breeding as valuable resources.
Abstract
This paper explores the prediction of the soluble solid content (SSC) in the visible and near-infrared (400–1,000 nm) regions of Baise mango. Hyperspectral images of Baise mangoes with wavelengths of 400–1,000 nm were obtained using a hyperspectral imaging system. Multiple scatter correction (MSC) was chosen to remove the effect of noise on the accuracy of the partial least squares (PLS) regression model. On this basis, the characteristic wavelengths of mango SSC were selected using the competitive adaptive reweighted sampling (CARS), genetic algorithm (GA), uninformative variable elimination (UVE), and combined CARS + GA-SPA, CARS + UVE-SPA, and GA + UVE-SPA characteristic wavelength methods. The results show that the combined MSC-CARS + GA-SPA-PLS algorithm can reduce redundant information and improve the computational efficiency, so it is an effective method to predict the SSC of mangoes.
