High Volume Instrument Research Articles

Non-contact Method for Measurement of Colour Variation in a Cotton Sample

Colour is the visual perceptual property in the cotton grade classification of Universal Cotton Standards. We undertook an experimental study on the variation in cotton colour using the Non-contact method. Rd (degree of reflectance) and +b (yellowness) are globally recognized colour parameters of cotton, which are measured by HVI (High Volume Instrument). The Non-contact method is used for the evaluation of colour variation within cotton samples. The results obtained from the Non-contact method were compared with those of other conventional methods used globally for the color measurement of cotton fibers. Additionally image analysis is interpreted with the variation in cotton colour. Results confirmed a strong co-relation between the Non-contact method and image analysis for the colour variation of cotton.

The relationship between instrumental leaf grade and Shirley Analyzer trash content in cotton lint

With the increasing acceptance of high volume instrument (HVI™) instrumental leaf grade index in both domestic and international trading, there is a continued interest in the relationship between instrumental leaf grade and equivalent trash gravimetric content (% percent by mass) from cotton customers and regulators. Due to the complexity of not only trash type, size, and its weight distribution but also the nature of HVI and gravimetric methods, it is an on-going challenge to examine such a relationship. In this study, the Shirley Analyzer (SA) was used to determine the gravimetric cotton trash in percent by mass (%). This system is the traditional cotton trash reference method that is still utilized as a routine tool in the cotton industry, despite being a destructive process that is both labor-intensive and time-consuming. This study first investigated the correlations between three SA trash readings ( SAvisible, SAinvisible, and SAtotal) and respective leaf grade categories, and it revealed a general trend of increasing SAvisible and SAtotal trash content with elevating leaf grade. Then, comparison of SAvisible trash content in the current study to that in separate studies indicated a good agreement for low leaf grade cottons (<4). Next, the principal component analysis of near infrared spectra from SAvisible trash portions revealed a different pattern in PC1 score between low leaf grade (1–4) and high leaf grade (5 and 6) SA visible trash remains, implying a general change of more leaf-related trash in low leaf grade cottons to more non-leaf-related trash in high leaf grade cottons.

Variation in the advanced fiber information system cotton fiber length-by-number distribution captured by high volume instrument fiber length parameters

Variation in cotton fiber length impacts processability at the mill and the quality of spun yarns. The High Volume Instrument (HVI) and Advanced Fiber Information System (AFIS) are cotton fiber quality assessment instruments able to quickly assess a myriad of fiber quality characteristics. HVI testing provides the fiber length parameters most widely utilized by the cotton industry, Upper Half Mean Length and Uniformity Index. However, HVI fiber length parameters do not account for the complete within-sample variation in fiber length, such as the shortest fibers in the sample. AFIS testing is able to characterize the complete within-sample distribution of fiber length within a sample of cotton by evaluating individual fibers. Within-sample variation in fiber length is an important cotton fiber quality concern because it impacts processing performance and yarn quality. In this paper, the fiber length for 9127 commercial cotton bales was evaluated on both HVI and AFIS. The AFIS length distributions are used to characterize the complete distribution of fiber length within each bale. A novel statistical technique is introduced and is used to characterize a set of multivariate axes that characterize the total within-bale variation in fiber length among the complete set of commercial bales. These results suggest that less than half of the variation in cotton fiber length captured by the AFIS length distributions is captured by the two length parameters provided by HVI testing. If an experimental factor has no significant impact on an HVI fiber quality parameter, an alternative cotton fiber length measurement such as the AFIS length distribution should be considered.

LED Utilization in Cotton Color Measurement

ABSTRACTThe color measurement of the cotton fiber is very important property of the cotton fiber and it plays important role in grading of cotton. Globally used color parameters of cotton fiber are Rd and +b. These parameters are measured by HVI (High Volume Instrument). Cotton color standards are ceramic tiles and cotton samples which are provided by USDA. This paper discusses the utilization of non-contact method by using LEDs as light source to measure the color parameters of cotton standards and comparing with color parameters of HVI. The comparison of cotton color parameters are performed by using the spectral data of different light sources.

Tracking Cotton Fiber Quality and Foreign Matter through a Stripper Harvester

The main objective of this project was to track cotton fiber quality and foreign matter content through the harvesting and conveying/cleaning systems on a brush-roll stripper harvester. Seed cotton samples were collected from four locations on a cotton stripper harvester in 2011 and 2012 along with handpicked seed cotton samples. The four machine locations included: 1) after the harvested cotton was conveyed out of the row unit but before being engaged by the cross auger conveyor, 2) from the separation duct inlet after the cotton was conveyed by the cross auger, 3) from the basket by-passing the field cleaner (before field cleaner, BFC), and 4) from the basket after the cotton was processed through the field cleaner. Seed cotton samples collected at each location were analyzed for foreign matter content and ginned to produce fiber for High Volume Instrument (HVI) and Advanced Fiber Information System (AFIS) fiber analyses. Results show little difference between the initial entry in the machine until the BFC location, and provide evidence that the field cleaner was the most effective system on a cotton stripper for removing foreign matter. AFIS and HVI results indicate that the harvesting, conveying, and cleaning systems had minimal effects on fiber characteristics not associated with foreign matter. Generally most parameters were not affected significantly until the seed cotton passed through the field cleaner, after which the parameters were reduced to similar levels of hand-harvested seed cotton.

English

An experiment was performed in a cotton-producing property located in Primavera do Leste - MT - (Brazil). the quantitative losses and the presence of bark and stems in the cotton fiber quality measuring instrument as analyzed by High Volume Instrument (HVI) was noted . The study was conducted to investigate a combined speed of work with a mechanical adjustment of the distance of the pressure plates and the screws on the platform. Another objective of this study was to determine reducing quantitative and qualitative losses of cotton fiber. The platform was set at three different velocities (1.02, 1.38 and 1.60 m s-1). Two different distances (plate with pressure – 3 mm and plate without pressure 6 mm were set as the distance between the spindles and the pressure plates. At these distances, the plants are pressed onto the spindle exerting pressure on the spindles. The collected fiber content of impurities and the efficiency of the machine were analyzed as a function of the total productivity and quantitative losses. Factorial statistical analysis was performed on the data using the Tukey test at 5% probability. A greater presence of impurities and lowest cotton crop losses was observed at the smallest distance between the spindles and the pressure plates. Key words: Picker, cotton, fiber quality, harvest efficiency, losses.

Accurate prediction of cotton ring-spun yarn quality from high-volume instrument and mill processing data

The derivation and performance of yarn quality prediction models in a program called Cottonspec is reported. Cottonspec incorporates a large database of fiber and yarn data from commercial spinning mills, a series of regression-based models predicting yarn quality from measured cotton fiber quality parameters and yarn specifications and a user interface. The inclusion of independent variables into prediction equations was dependent on the criteria that their inclusion was statistically significant and that variables had a theoretically direct influence on yarn structure. Yarn data was corrected to allow for twist, yarn count and yarn irregularity before correlation with fiber properties. Differences in yarn testing results between mills could be corrected by a Mill Correction Factor. Adherence to these criteria and the ability to draw on the very large database meant prediction ability of the models was excellent, as demonstrated in a series of cross-validations.

Evaluation of Innovative Cotton Genotypes Against Insect Pest Prevalence, Fiber Trait, Economic Yield and Virus Incidence in Pakistan

Abstract Cotton (Gossypium hirsutum) is known as important commodity globally. The experiment was conducted at Cotton Research Station, Multan, Punjab-Pakistan, to evaluate resistance of nine innovative cotton cultivars against insect pest complex were used along with their fiber traits, economic yield and virus incidence. Population of jassid, whitefly and thrips was recorded by using leaf turn method, bollworms by counting whole fruiting parts (buds, flowers and bolls), virus by counting healthy and virus effected plants per plot, yield of seed cotton was determined by hand harvesting method, while qualitative fiber properties were measured through HVI spectrum-1 (high volume instrumentation) method. Cotton genotype NIAB-Bt-2 is resistant to jassid, whitefly and thrips with maximum GOT, staple length. In case of bollworms, all genotypes are resistant to spotted and american bollworm, except FH-142 and MNH-988. No genotype is resistant to pink bollworm in leftover bolls. Best yield performance was recorded on FH-142 (2041.54 kg/ha) with minimum CLCuV incidence. Further our research should recognize the share of one pest species on the yield and fiber quality of cotton by managing other pest species to define better management strategies. Our studies concluded that the genotype NIAB-Bt-2 has less insect attack i.e., sucking pest as well as bollworms, virus and other fiber characteristics like GOT, staple length as compared with other cotton genotypes should be recommended for general cultivation and being a resistant germplasm it should be included in breeding program for the development of new cotton strains.

Application of near infrared spectroscopy in cotton fiber micronaire measurement

The term “micronaire” describes an important cotton fiber property by characterizing both the fiber maturity and fineness. In practice, micronaire is regularly measured in laboratories with the well established high volume instrumentation (HVI™) protocol. In most scenarios, cotton breeders/geneticists sent cotton breeding line field trial samples to laboratories equipped to use the HVI™ systems available for fiber micronaire determination. Researchers have previously investigated the use of NIR as an alternative means of measuring micronaire either at breeding sites or in standard laboratories. As a proof-of-concept investigation, this study collected both near infrared (NIR) spectra and HVI™ micronaire from a total of 381 cottons harvested in the 2011 and 2012 crop years. Partial least square (PLS) calibration model relating NIR spectral information to fiber HVI™ micronaire was developed and then applied to both a validation sample set from identical crop years and an independent test sample set from the 2014 crop year. Results indicated an acceptable bias (or differences between HVI™ measured and NIR predicted micronaire) and an over 97% correctly predicted micronaire (within ±0.30 micronaire unit) in an independent test set. Therefore, the development of a robust and effective NIR model for rapid laboratory micronaire assessment that would be applicable to remote/breeding locations is feasible.

Comparative Relationship of Fiber Strength and Yarn Tenacity in Four Cotton Cultivars

<p class="1Body">High volume instrumentation (HVI<sup>TM</sup>) measurement is a primary and routine tool of providing fiber properties to cotton researchers. There have been considerable studies designed to derive yarn quality from acquired fiber quality data by various means, including HVI. There is also of desired information about the comparison of yarn quality within a cotton cultivar or among the cultivars, as such knowledge could be informative in attempts to understand the selection of cotton cultivars. The purpose of this preliminary study was to characterize the fiber HVI strength and yarn skein tenacity of four cotton cultivar harvested from three locations in different crop years. Instead of developing linear regression models from acquired fiber property parameters to predict yarn tenacity, this study applied a simple ratio method (i.e., correct fiber strength or yarn tenacity with fiber micronaire component) to relate fiber strength with yarn tenacity. The results indicate that three cultivars (DP 393, Phytogen 72, and FM 958) show stronger correlation between micronaire corrected yarn tenacity and micronaire corrected fiber HVI strength. It implies the feasibility of utilizing HVI fiber micronaire and strength property data, as a semi-quantitative and fast tool, to compare the yarn tenacity performance within a cotton cultivar or between cultivars.</p>

Botanical Trash Mixtures Analyzed with Near-Infrared and Attenuated Total Reflectance Fourier Transform Spectroscopy and Thermogravimetric Analysis

Botanical cotton trash mixed with lint reduces cotton’s marketability and appearance. During cotton harvesting, ginning, and processing, trash size reduction occurs, thus complicating its removal and identification. This trash causes problems by increasing ends down in yarn formation and thus processing efficiency. The Uster® High Volume Instrument (HVI) and Shirley Analyzer are extensively used to determine trash levels in cotton lint, but they do not specifically identify its origin. This study was performed to determine the potential for recognizing differences between botanical cotton trash mixtures via near-infrared (NIR) spectroscopy and attenuated total reflectance-Fourier transform infrared (ATR/FT-IR) spectroscopy, and thermogravimetric analysis (TGA). A "proof of concept" was demonstrated that showed the promise of NIR and ATR/FT-IR spectroscopy along with TGA to be employed to identify binary mixtures of botanical cotton trash. In the case of the ATR/FT- IR results, the leaf and seed coat mixtures in the presence of cotton yielded the lowest accuracy of the trash mixtures. This might have arisen from the presence of noncellulosics in the samples.

Response Surface Regression Models for Prediction of Ring Spun Yarn Properties

In this study, the response surface methodology is used to predict the mechanical properties of yarn, their unevenness and hairiness by using the high-volume instrument (HVI) properties of raw cotton and the parameters of the spinning process. Therefore, five different blends of cotton are processed and spun into ring yarns (Nm13, Nm19, Nm 21, Nm31 and Nm37). Each count is spun at five twist levels (450, 500, 650, 750 and 850 trs/m). The models that are developed by using response surface regression with many iterations on a Minitab16 statistical software predict very well the different yarn properties since the R2 values obtained are very important. In addition, these models show that metric number and twist have the highest effect on the four studied parameters

Digieye Application In Cotton Colour Measurement

Abstract Colour is one of the most important properties of cotton raw materials. It helps in determining and classifying the quality of fibres according to the Universal Cotton Standards. Organoleptic and instrumental techniques are applied to assess the color of cotton. Worldwide, the colour parameters of cotton are measured by the High Volume Instrument (HVI), which provides information on reflectance (Rd) and yellowness (+b) that is specific for cotton, but are not the typical and globally recognized colour characteristics. Usually, worldwide, the colour of textile products and other goods is assessed utilizing the spectrophotometer, which provides the colour data that is widely recognized and accepted by the CIE L*a*b* colour space. This paper discusses utilizing the DigiEye system to measure the colour parameters of cotton samples and compares the results with the colour parameters from the HVI.

Economic Yield, Fiber Trait and Sucking Insect Pest Incidence on Advanced Genotypes of Cotton in Pakistan

Abstract To evaluate resistance against sucking insect pest of cotton 16 cultivars were used along with their economic yield and fiber traits. Population of jassid, whitefly and thrips was recorded by using leaf turn method, yield of seed cotton was determined by hand harvesting method, while qualitative fiber properties were measured through high volume instrumentation (HVI) method. Best yield performance and staple length was of FH- 158 (4000 kg/ha) (28.1 mm), respectively. Cotton cultivar FH-172 showed resistance toward jassid and thrips but FH-158 showed resistance against jassid. Thus these resistance cultivars along with other cultivars possessing resistance against insect pest should be explored. Additional research should identify the part of one pest species on the yield and fiber quality of cotton by managing other pest species to define better management strategies.

Classification of cotton foreign matter using color features extracted from fluorescent images

The presence of foreign matter affects the quality and ultimately the monetary value of cotton lint. Current methods, such as the High Volume Instrument, compute the overall area of the foreign matter, but cannot identify the specific type. A fluorescent imaging system was investigated to classify the six types of botanical and seven types of non-botanical foreign matter under blue and ultraviolet (UV) light-emitting diode (LED) excitation lights, respectively. Two color models (RGB (red, green, blue) and HSV (hue, saturation, value)) were used and ratio images and single-channel images were examined. The F-values from the multivariate analysis of variance were used to select the three most contributing color features from the blue LED (R/G, H, V) and the UV LED dataset (B/G, S, V). The linear discriminant analysis model achieved classification rates of 80% or higher for bract, green leaf, hull, paper, plastic bag, plastic packaging, seed, and stem, and classification rates between 60% and 80% for bark, seed coat, and twine. The study demonstrated that fluorescence imaging is a promising tool to classify major types of cotton foreign matter and could be used for cotton classing.

Blue and UV LED-induced fluorescence in cotton foreign matter.

BackgroundCotton is an important domesticated fiber used to manufacture a variety of products and industrial goods. During harvesting with cotton strippers and cotton pickers, it is contaminated with foreign matter from botanical and non-botanical sources which adversely affect the quality and consistency of cotton, and therefore reduces its market value. To improve the current grading done by the High Volume Instrument (HVI) and human inspectors, it was explored whether fluorescence imaging can be used for cotton foreign matter detection.ResultsEight types of botanical foreign matter (bark, bract, brown leaf, green leaf, hull, seed coat, seed, stem), and four types of non-botanical foreign matter (paper, twine, plastic bale packaging, plastic bag) were subjected to a fluorescence spectroscopy analysis to determine their optimal excitation and emission wavelength range. Matrix 3D scans were performed in the excitation range from 300 nm to 500 nm, and emission range from 320 nm to 700 nm, and the results indicated the photo-excitable fluorescence in the aforementioned excitation range for all the selected foreign matter categories. Consequently, the blue and the UV LEDs were selected as the excitation sources. The blue LED light provided optimal excitation light for bark, brown leaf, bract, green leaf, hull, and stem, while the UV LED light provided optimal excitation light for paper, plastic bag, plastic packaging, seed, seed coat, and twine.ConclusionsUV and blue light induces fluorescence in 12 types of botanical and non-botanical cotton foreign matter. An imaging apparatus with blue and UV light excitation sources, and a consumer grade SLR camera was successfully developed to capture and characterize fluorescent images of cotton foreign matter. Based on the results, fluorescent imaging could be a promising method for cotton foreign matter detection. Future studies will focus on the classification of cotton foreign matter categories and to further refine the image processing sequence.Electronic supplementary materialThe online version of this article (doi:10.1186/1754-1611-8-29) contains supplementary material, which is available to authorized users.

Comparing cotton fiber quality from conventional and round module harvesting methods

The introduction of the John Deere 7760 spindle harvester to the Australian cotton industry in 2008, with on board module building capacity producing round modules, has led to the rapid uptake of this technology by growers due to a reduction in labor requirements. There have, however, been anecdotal reports from cotton classing facilities and growers that the quality of cotton harvested by the John Deere 7760 is different and more variable compared to cotton harvested by the conventional spindle basket harvesting and separate module building method. The aim of this research was to compare the average fiber quality and the variability of quality between bales of cotton produced by these two harvesting methods. Four fields located in the southern and central cotton growing areas of Australia were planted with two popular upland varieties. Alternate groups of rows across each field were harvested using either the round module or conventional basket harvesting method, with harvested seed cotton ginned at the same gin. Fiber samples were assessed for quality attributes typically used to class and value cotton in Australia. There was no significant difference of average results between the two harvest methods for High Volume Instrument (HVI) determined upper half mean length and bundle strength. However, HVI micronaire was marginally yet significantly lower and HVI reflectance higher for fiber from the round module system, which was attributed to the round harvesters being able to harvest more fiber (including immature fiber from the top of plants) and less trash. The small difference in reflectance, however, did not translate into a practical difference, with there being no significant difference measured between the two harvesting systems for visually determined color and leaf grade. The normalized variability (% coefficient of variation) of fiber quality between bales was greater for the round module system, which was attributed to less blending during the sequential ginning of round modules in contrast to the vertical building of equivalent multiple (round module) layers of seed cotton in larger conventional modules that undergo more blending when fed longitudinally into the gin. While the round modules in this research were harvested and ginned according to industry standards and in sequence, less than favorable in-field conditions and out-of-sequence ginning would more than likely compound the variation in fiber quality between bales. The impact of these variables on fiber quality would have significant practical implications, which will require further investigation.

Regressional Estimation of Cotton Sirospun Yarn Properties from Fibre Properties

Abstract In this paper, it is aimed at determining the equations and models for estimating the sirospun yarn quality characteristics from the yarn production parameters and cotton fibre properties, which are focused on fibre bundle measurements represented by HVI (high volume instrument). For this purpose, a total of 270 sirospun yarn samples were produced on the same ring spinning machine under the same conditions at Ege University, by using 11 different cotton blends and three different strand spacing settings, in four different yarn counts and in three different twist coefficients. The sirospun yarn and cotton fibre property interactions were investigated by correlation analysis. For the prediction of yarn quality characteristics, multivariate linear regression methods were performed. As a result of the study, equations were generated for the prediction of yarn tenacity, breaking elongation, unevenness and hairiness by using fibre and yarn properties. After the goodness of fit statistics, very large determination coefficients (R2 and adjusted R2) were observed.

Evaluation of Cotton Productivity by Fruiting Zone in Diverse Growing Locations

The amount and quality of cotton (Gossypium spp.) produced within a growing season is the result of many factors, but the influence of genotype is substantial. The objective of this study was to determine how growing location, fruiting behavior, and cultivars interact to produce a cotton crop. Five commercial cultivars were studied at multiple locations in Texas and Virginia. Plant height, first sympodia, and number of sympodia were measured. Plants were harvested by fruiting zone and lint yield, lint percent, seed weight, and high-volume instrumentation (HVI) fiber data were ascertained. Results indicate that cultivar had a significant effect on plant height and fruiting habit, but year also significantly affected traits measured. In addition, lint yield, lint percent, seed weight, and fiber traits were significantly affected by fruiting zone at most locations and years. It was determined that relative differences among cultivars remained constant across growing locations for plant morphology and fiber traits. Differences in lint yield per fruiting zone were not distinguishable.

Optimizing Irrigation and Plant Density for Improved Cotton Yield and Fiber Quality

An important limitation to cotton (Gossypium hirsutum L.) production in the Texas High Plains is water shortage. A 2‐yr study was conducted at two locations in Lubbock, TX, in 2007 and 2008 to determine the optimal irrigation and plant density for cotton production in the Texas High Plains based on yield and fiber quality. A field experiment was conducted by using a split plot design, with irrigation (0, 2.54 and 5.08 mm d−1) as the main plot, and plant density (75,300; 150,600; and 226,000 plants ha−1) as the subplot. Two central rows of each plot were machine harvested to determine lint yield. Fiber quality was tested by both High Volume Instrument (HVI) and Advanced Fiber Information Systems (AFIS). The results showed environmental conditions heavily impact lint yield and fiber quality. Irrigation played a significant role in yield and fiber quality. Under appropriate weather conditions at Quaker 2008, 5.08 mm d−1 irrigation rate increased seed cotton yield by 36.4 and 214.3%, compared with 2.54 and 0 mm d−1, respectively. Irrigation of 5.08 mm d−1 increased fiber length by number, uniformity, and short fiber content. The fineness and maturity ratio and subsequently micronaire decreased. Plant density seemed to play a smaller role in determining yield and fiber quality. Based on profitability, higher yield did not necessarily translate to higher net returns. We concluded that weather pattern and irrigation heavily impact yield and fiber quality in the Texas High Plains.