Genome resequencing-based high-density genetic map and QTL detection for yield and fiber quality traits in diploid Asiatic cotton (Gossypium arboreum).

Cotton is the most important fiber crop in the world. Asiatic cotton (Gossypium arboreum, genome A2) is a diploid cotton species producing spinnable fibers and important germplasm for cotton breeding and a significant model for fiber biology. However, the genetic map of Asiatic cotton has been lagging behind tetraploid cottons, as well as other stable crops. This study aimed to construct a high-density SNP genetic map and to map QTLs for important yield and fiber quality traits. Using a recombinant inbred line (RIL) population and genome resequencing technology, we constructed a high-density genetic map that covered 1980.17 cM with an average distance of 0.61 cM between adjacent markers. QTL analysis revealed a total of 297 QTLs for 13 yield and fiber quality traits in three environments, explaining 5.0-37.4% of the phenotypic variance, among which 75 were stably detected in two or three environments. Besides, 47 QTL clusters, comprising 131 QTLs for representative traits, were identified. Our works laid solid foundation for fine mapping and cloning of QTL for yield and fiber quality traits in Asiatic cotton.

Characterization of Developmental Immature Fiber ( im) Mutant and Texas Marker-1 (TM-1) Cotton Fibers Using Attenuated Total Reflection Fourier Transform Infrared (ATR FT-IR) Spectroscopy.

The immature fiber ( im) mutant is one type of cotton fiber mutant with unique characteristics of non-fluffy cotton bolls. Compared to its near-isogenic wild type Texas Marker-1 (TM-1), im fiber has a thin secondary cell wall and is less mature. In this work, we applied the previously proposed principal component analysis (PCA) and simple algorithms to analyze the attenuated total reflection Fourier transform infrared (ATR FT-IR) spectra of developmental im and TM-1 fibers. The results from these approaches could not effectively and consistently indicate the inherent difference between TM-1 and im fibers at the same developmental stage. The difference between TM-1 and corresponding im fibers was detected when comparing the normalized intensity variations of the 730 cm-1 bands. The 730 cm-1 band intensities in developmental im fibers are temporally lower than those in developmental TM-1 fibers although they became similar when the TM-1 and im fibers are fully mature. The observation might imply the likelihood of temporal reduction of amorphous regions in developmental im fibers rather than in developmental TM-1 fibers.

Detection and discrimination of cotton foreign matter using push-broom based hyperspectral imaging: system design and capability.

Cotton quality, a major factor determining both cotton profitability and marketability, is affected by not only the overall quantity of but also the type of the foreign matter. Although current commercial instruments can measure the overall amount of the foreign matter, no instrument can differentiate various types of foreign matter. The goal of this study was to develop a hyperspectral imaging system to discriminate major types of foreign matter in cotton lint. A push-broom based hyperspectral imaging system with a custom-built multi-thread software was developed to acquire hyperspectral images of cotton fiber with 15 types of foreign matter commonly found in the U.S. cotton lint. A total of 450 (30 replicates for each foreign matter) foreign matter samples were cut into 1 by 1 cm2 pieces and imaged on the lint surface using reflectance mode in the spectral range from 400-1000 nm. The mean spectra of the foreign matter and lint were extracted from the user-defined region-of-interests in the hyperspectral images. The principal component analysis was performed on the mean spectra to reduce the feature dimension from the original 256 bands to the top 3 principal components. The score plots of the 3 principal components were used to examine clusterization patterns for classifying the foreign matter. These patterns were further validated by statistical tests. The experimental results showed that the mean spectra of all 15 types of cotton foreign matter were different from that of the lint. Nine types of cotton foreign matter formed distinct clusters in the score plots. Additionally, all of them were significantly different from each other at the significance level of 0.05 except brown leaf and bract. The developed hyperspectral imaging system is effective to detect and classify cotton foreign matter on the lint surface and has the potential to be implemented in commercial cotton classing offices.

Discrimination of unprocessed cotton on the basis of geographic origin using multi-element stable isotope signatures.

RATIONALE: Cotton is the most commonly used natural plant product for the manufacture of yarns and textiles. Consumer perception regarding differences in textile quality in relation to geographic provenance of cotton as well as stringent product labelling requirements demand for the supply chain to furnish proof of geographic provenance beyond merely paper-based audit trails. METHODS: We have applied isotope ratio mass spectrometry to generate multivariate data sets of raw cotton. A two-point equilibration process with water at ambient temperature was used to account for hydrogen exchange between free hydroxyl groups in the cellulose lattice at ambient humidity, prior to hydrogen isotope analysis. RESULTS: The molar fraction of exchangeable hydrogen in cotton at ambient temperature was found to be 0.046, which is in good agreement with the expected exchange fraction of 0.05. Hierarchical cluster analysis of multivariate stable isotope abundance data from 17 US cotton and 15 non-US cotton samples was able to cluster 15 of the 17 US cotton samples in one group. CONCLUSIONS: Hierarchical cluster analysis of multivariate stable isotope signatures of raw cotton showed great promise as an analytical tool to differentiate between US and non-US cotton and possibly even to be able to group unprocessed cotton according to geographic origin.

Investigating the provenance of un-dyed spun cotton fibre using multi-isotope profiles and chemometric analysis.

The analysis of un-dyed spun cotton fibres can be challenging within a forensic science context where discrimination of one fibre from another is of importance. Conventional microscopic and chemical analysis of these fibres is generally unsuccessful because of their similar morphology. In this work we have explored the potential of isotope ratio mass spectrometry (IRMS) as a tool for spun cotton fibre analysis in an attempt to reveal any discriminatory information available. Seven different batches of un-dyed spun cotton fibre from four different countries were analysed. A combination of the hydrogen and oxygen isotopic data facilitated the correct association of the samples, demonstrating, for the first time, the applicability of IRMS to fibre analysis in this way.

[Research on the trash content measurement and classification of ginned cotton by using NIR spectroscopy technique].

Near infrared (NIR) spectroscopy was investigated to predict trash content and classify types of ginned cotton by using a fiberoptic in diffuse reflectance mode. Different spectra preprocessing methods were compared, and partial least-squares (PLS) regression was established to predict the trash content of ginned cotton. Discriminant analysis (DA) was used to classify various types of lint and content level of trash. The correlation coefficient r was 0.906 for optimal PLS model using three factors based on first-order derivative spectra, and RMSEC and RMSEP was 0.440 and 0.823 respectively. To classify ginned cotton with and without plant trash, the accuracy rate reached 95.4% using 15 principal components (PCs) via DA, whereas the prediction accuracy rate was only 80.9% for the classification of sample types due to containing foreign fiber, and the classification result for the content level of trash in lint was not good for the samples without any preprocessing. The result indicated that the NIR spectra of sample can be used to predict trash content in ginned cotton, which is often disturbed by type, content and distribution of foreign matters, and the accuracy of some prediction model is unsatisfactory. In order to improve the prediction accuracy, some methods would be applied in future research, such as pretreatment according to acquisition request of solid sample, or using transmission mode.

Cotton fiber quality characterization with light scattering and fourier transform infrared techniques.

Fiber quality measurement is critical to assessing the value of a bale of cotton for various textile purposes. An instrument that could measure numerous cotton quality properties by optical means could be made simpler and faster than current fiber quality measurement instruments, and it might be more amenable to on-line measurement at processing facilities. To that end, a laser system was used to investigate cotton fiber samples with respect to electromagnetic scattering at various wavelengths, polarization angles, and scattering angles. A Fourier transform infrared (FT-IR) instrument was also used to investigate the transmission of electromagnetic energy at various mid-infrared wavelengths. Cotton samples were selected to represent a wide range of micronaire values. Varying the wavelength of the laser at a fixed polarization resulted in little variation in scattered light among the cotton samples. However, varying the polarization at a fixed wavelength produced notable variation, indicating that polarization might be used to differentiate among cotton samples with respect to certain fiber properties. The FT-IR data in the 12 to 22 microm range produced relatively large differences in the amount of scattered light among all samples, and FT-IR data at certain combinations of fixed wavelengths were highly linearly related to certain measures of cotton quality including micronaire.

Novel search algorithms for a mid-infrared spectral library of cotton contaminants.

During harvest, a variety of plant based contaminants are collected along with cotton lint. The USDA previously created a mid-infrared, attenuated total reflection (ATR), Fourier transform infrared (FT-IR) spectral library of cotton contaminants for contaminant identification as the contaminants have negative impacts on yarn quality. This library has shown impressive identification rates for extremely similar cellulose based contaminants in cases where the library was representative of the samples searched. When spectra of contaminant samples from crops grown in different geographic locations, seasons, and conditions and measured with a different spectrometer and accessories were searched, identification rates for standard search algorithms decreased significantly. Six standard algorithms were examined: dot product, correlation, sum of absolute values of differences, sum of the square root of the absolute values of differences, sum of absolute values of differences of derivatives, and sum of squared differences of derivatives. Four categories of contaminants derived from cotton plants were considered: leaf, stem, seed coat, and hull. Experiments revealed that the performance of the standard search algorithms depended upon the category of sample being searched and that different algorithms provided complementary information about sample identity. These results indicated that choosing a single standard algorithm to search the library was not possible. Three voting scheme algorithms based on result frequency, result rank, category frequency, or a combination of these factors for the results returned by the standard algorithms were developed and tested for their capability to overcome the unpredictability of the standard algorithms' performances. The group voting scheme search was based on the number of spectra from each category of samples represented in the library returned in the top ten results of the standard algorithms. This group algorithm was able to identify correctly as many test spectra as the best standard algorithm without relying on human choice to select a standard algorithm to perform the searches.

New approach to environmental tobacco smoke exposure and its relation to reemission processes.

Indoor air quality is one of the factors that determine human well-being and health. Being aware of this fact, it is essential to identify the origin, kind, mechanism, and effects of harmful substances contained in the air. The issue concerning the contents and primary emission of these substances from building materials and interior furnishings is well known. Adverse effects of environmental tobacco smoke (ETS), including exposure of passive smokers, are also very well documented. To the contrary, reports on secondary and indirect emissions, especially those focused on mechanisms by which pollution is "transferred" by materials used in interior furnishings are very rare. Textiles are used in a great variety of ways as functional and decorative materials. These materials in general, and textile floor coverings in particular, are extensively utilized in fitting apartments, public buildings, and transport means. Studies on this aspect of the role played by textile materials in ETS exposure have been only fragmentary documented.

Genetic analysis for F1 yield traits with conditional approach in island cotton (Gossypium barbadense L.).

A genetic model with additive, dominance and genotype x environment interaction effect was employed to analyze the 3-year data of F(1) hybrids from 5 x 4 diallel cross, whose parents were Island cotton and had different fruit branch types. Unconditional and conditional genetic variances were conducted for analyze genetic impacts of yield components on yield. Results of unconditional genetic variances showed that there were no additive variance of total lint yield. But conditional additive effects of total lint yield, when excluding the phenotype of boll weight, boll number at prefrost, boll number at postfrost, and lint yield at prefrost, indicated that improving the additive effects of the total lint yield was still possible. Crossing and selecting component traits with high contributive additive effects could obtain good offsprings. Yield components contributed large dominance effects to the heterosis of lint yield at prefrost and total lint yield in crosses. Yield component traits were controlled with each other. The traits having positive contributive effects could be applied to further improve target traits.

Enhanced production of cellobiohydrolases in Trichoderma reesei and evaluation of the new preparations in biofinishing of cotton.

In the search for suitable cellulase combinations for industrial biofinishing of cotton, five different types of Trichoderma reesei strains were constructed for elevated cellobiohydrolase production: CBHI overproducers with and without endoglucanase I (EGI), CBHII overproducers with and without endoglucanase II (EGII) and strains overproducing both CBHI and CBHII without the major endoglucanases I and II. One additional copy of cbh1 gene increased production of CBHI protein 1.3-fold, and two copies 1.5-fold according to ELISA (enzyme-linked immunosorbent assay). The level of total secreted proteins was increased in CBHI transformants as compared to the host strain. One copy of the cbh2 expression cassette in which the cbh2 was expressed from the cbh1 promoter increased production of CBHII protein three- to four-fold when compared to the host strain. T. reesei strains producing elevated amounts of both CBHI and CBHII without EGI and EGII were constructed by replacing the egl1 locus with the coding region of the cbh1 gene and the egl2 locus with the coding region of cbh2. The cbh1 was expressed from its own promoter and the cbh2 gene using either the cbh1 or cbh2 promoter. Production of CBHI by the CBH-transformants was increased up to 1.6-fold and production of CBHII up to 3.4-fold as compared with the host strain. Approximately similar amounts of CBHII protein were produced by using cbh1 or cbh2 promoters. When the enzyme preparation with elevated CBHII content was used in biofinishing of cotton, better depilling and visual appearance were achieved than with the wild type preparation; however, the improvement was not as pronounced as with preparations with elevated levels of endoglucanases (EG).