Comparisons of Minicard ratings with ion chromatography sugar profiles of water extracts of cotton fibers and those of Minicard sticky spot materials

Abstract

Specific levels of the carbohydrates melezitose and trehalulose deposited on the surface of cotton fibers are indicators of whitefly or aphid contamination. These deposits could cause stickiness problems during cotton ginning and textile processing. Cotton stickiness is highly complex, but surface carbohydrates may play the largest role in manifesting an issue. We utilized ion chromatography (IC) to identify and quantify nine sugars of interest present in the water extracts of 25 cotton samples to create sugar profiles for each sample: inositol, trehalose, glucose, fructose, trehalulose, sucrose, melezitose, raffinose and maltose. We compared the sugar profiles to the respective Minicard ratings of either NONE, LIGHT, MODERATE or HEAVY to draw correlations between the IC data and the rating. Trehalulose and melezitose in water extracts highly and positively correlate to Minicard ratings, confirming past researchers’ attribution of cotton stickiness to insect sugars. Trehalose and maltose also highly correlated, possibly due to their marker content in honeydew. Glucose and fructose moderately correlated to the ratings. IC studies of the collected Minicard sticky spot material found trehalulose and melezitose were the most prevalent sugars in HEAVY rated samples. Glucose and fructose were present in larger amounts in the MODERATE versus HEAVY rated samples. This result may indicate that the Benedict Test, which attributes these reducing sugars to stickiness, may not be sufficient for conjecturing a stickiness issue. When comparing the averages of the nine sugars present in water extracts versus those sugars contained in Minicard sticky spots, the overall distributions were very similar.

Keywords

properties materials surface modification chemistry processing fabrication

Over the years, the production rates and efficiency of cotton fiber processing technologies have changed and their performance has improved, thereby changing the requirements for a higher quality cotton fiber. The spinning of yarn performance is affected by the fiber characteristics, such as fiber morphology (convolutions), geometric features (length, fineness), static electrical forces, waxes, salts and sugars.¹ The sugars present on the fiber are usually a combination of plant metabolic sugars and entomological sugars. If the cotton is over contaminated with insect sugars, they should be detected prior to the beginning of the cotton fiber processing.^2,3 This is because cotton stickiness if a very serious problem in textile areas, including the growing, ginning and spinning sectors, and can cause major problems during opening, carding and through to spinning, many times resulting in financial losses.⁴

Silverleaf Whitefly (Bemisia tabaci) and Cotton Aphid (Aphis gossypii) honeydew deposits have been reported to be responsible for most cases of cotton fiber stickiness, due to their high amounts of entomologically produced carbohydrates.^4,5 Melezitose is the dominant insect sugar produced from aphids, and trehalulose is the dominant insect sugar produced by the whitefly.⁴ Distinguishing the ratio of melezitose and trehalulose allows for an identification of the insect responsible for the contamination.⁶ Even though high-performance anion exchange chromatography (IC) is one of the most useful techniques to determine oligosaccharides and is used to scientifically and analytically identify and quantify the presence and ratio of the individual sugars on the cotton fiber surface, it has not been definitively established that chemical analyses (such as IC alone) can give an accurate account of whether or not a cotton sample will be sticky.⁷

Some cotton fiber sectors also use a number of other physical techniques to find cotton stickiness for a particular cotton crop.⁴ The physical testing methods are used because they are simple and are direct measures of the stickiness phenomenon and because some stakeholders believe that using IC to determine the surface carbohydrates of a small sample taken from a cotton bale may not necessarily reveal whether or not a bale will have an actual stickiness processing issue.⁵

The mechanical instruments that have been developed to evaluate the stickiness of cotton are the Minicard (MC) instrument, the Lintronics Fiber Contamination Tester (FCT), the Sticky Cotton Thermodetector (SCT) and the High Speed Stickiness Detector, among others (some of which are no longer commercially available).⁸ The MC and Thermodetector are two techniques used by the United States Department of Agriculture Agricultural Research Service (USDA ARS) cotton processing facility in New Orleans, LA; both result in rating systems that give gradations of stickiness from “non-sticky” or “none” to “strong” or “heavy” stickiness. The MC is a smaller version of a full size card, while the Thermodetector inflicts a temperature increase for a short period of time onto cotton fiber that has been pressed between two plates so as to thermally transfer the sticky spots onto aluminum foil.

Since the Thermodetector could change the physical properties of the cotton due to the increased temperature directly applied to the fibers, the MC might be a better representation of what happens to the surface sugars present on cotton fibers during the normal cotton processing procedures and is a favored method of measuring stickiness by several cotton research/processing facilities.⁹ Trehalulose and melezitose both undergo thermochemical degradation at sufficiently high temperatures; trehalulose degrades quickly at 200℃ (which can be reached during cotton processing) and melezitose degrades more slowly.⁶ The operating temperature of the thermodetector (84 ± 4℃) has been reported to cause more trehalulose sticky spot build-up due to trehalulose’s low melting point (∼48℃) and high hygroscopy.⁸ In this study, we compared the IC data with the MC only, since the Thermodetector could change the surface chemical property of the fiber due to the infusion of temperature across the cotton fiber samples.

The MC facilitates clumping of “sticky spots” onto the drum and roller of the machine, allowing for a physical representation of the propensity of the fibers to cause processing issues in the full-scale machinery. Those sticky spots can be collected and analyzed further for more in-depth information about the contamination. However, the MC procedure is not always as precise as desired and does not identify the sugar type; so, a technique that could support the finding of the MC when predicting stickiness is desirable.⁵ For that reason, we were interested in imitating a full-scale process using the MC and comparing its results to the IC data collected from water extracts to determine whether surface carbohydrate information can predict cotton stickiness, or at least reveal the cause of a stickiness rated cotton.

Firstly, this research aims to further reveal the relationship of the MC technique’s ratings to surface sugar content, by determining whether or not there is a correlation to the sugars-of-interest ratio profile obtained via the IC. By testing the carbohydrates present in the water extract of raw unaltered cotton fibers, using IC and then comparing the results to the MC ratings, we will examine their relationship to attempt to better understand the impact of carbohydrate content on stickiness.

Secondly, by dissolving the sticky spots of the cotton fiber created during the MC process, then utilizing IC to develop a sugar profile for the spots, we aim to clarify the relationship between pre and post MC tested sugar profiles by comparing MODERATE and HEAVY rated samples. Our overall research objective was to determine a proof-of-concept approach to answer whether or not IC could be used as an alternative to detect and/or diagnose a cotton stickiness issue if more information were known about the sugar content.^6,10

Materials and methods

Materials

The following were carbohydrate standards and eluents used for IC analysis: inositol 98+% was obtained from Acros Organics (New Jersey, USA). Trehalose, D-(+)-trehalose dehydrate; glucose, D-(+)-glucose), fructose (D-(-)-fructose; sucrose, melezitose, (α-D-glucopyranosyl-[1→3]-β-D-fructofuranosyl-[2→1]-α-D-glucopyranoside) hydrate, 99+%; raffinose, D-(+)-raffinose pentahydrate; and maltose monohydrate were purchased from the Sigma-Aldrich Corporation (St. Louis, MO). Trehalulose, 90% 1-O-alpha-D-glucopyranosyl-D-fructose was purchased from Chem Service Inc. (West Chester, PA). Sodium hydroxide solution, 50%, was obtained from Fischer Scientific (Fair Lawn, NJ). All reagents were used as received without further purification.

Acrodisc® syringe filters with 17 mm PVDF (Polyvinylidene fluoride) membranes (diameter 13 mm, pore size 0.2 µm) were obtained from Thermo Scientific (Rockwood, TN), and the Corning LSE™ Vortex Mixer was purchased from Corning Incorporated (Corning, NY). The water used in this study was distilled, deionized, and then further purified with a Millipore Direct-Q® 3UV, 8 system from EMD Millipore Corporation (Billerica, MA).

Cotton fiber samples

Twenty-five cotton fiber samples, ranging from NONE to HEAVY stickiness rating, as determined by physical MC testing, were obtained from the Southern Regional Research Center in New Orleans, LA (USDA ARS), and used in this study. All samples were measured three times using the preparation method described in the following sections, and then the results were averaged.

Cotton fiber sample extraction for ion chromatography analysis

For carbohydrate analysis via IC, 1 g of cotton was obtained by pinching small aliquots from the total cotton sample in order to increase random sampling. The raw cotton fiber sample was placed in a centrifuge tube, where 20 mL of ultrapure deionized water was added. The cotton/water sample was capped and vortexed at ∼5000 rpm for 30 seconds, then again for 5 minutes at ∼3500 rpm. The water extract from the vortexed samples was then filtered through a 0.2 µm syringe filter to remove any cotton fibers and particulate, and then it was placed in a 1.5 mL auto-sampler glass vial for analysis on the ion chromatograph instrument.

Ion chromatography

IC was performed on a Dionex DX-5000 instrument fitted with two Dionex CarboPac PA-1 (4 mm × 250 mm) columns connected in series using a pulsed amperometric detector. The analytics software used was a Dionex Chromeleon 7.2 CDS, which is a Thermo Scientific software. The elution was carried out using a flow rate of 0.80 mL/min. An isocratic eluent delivery was employed using 200 mM NaOH for 28.5 minutes. The column and compartment temperatures were set at 30℃.

A stock standard matrix of eight of the sugars (inositol, trehalose, glucose, fructose, sucrose, melezitose, raffinose and maltose) was created by dissolving the sugars in water. The stock standard solution was diluted further to create a standard calibration curve via the IC. The trehalulose standard stock was prepared and run on the IC separately, since the trehalulose syrup was only 90% pure (which is common, by industrial standards) and contained levels of glucose, fructose and an unidentified component.

It is important to note that standard solutions were run and calibration curves were created every time samples were analyzed throughout the experiments; the calibration curves maintained linearity, with R² values of greater than 0.98 for each sugar. Also, every time a sample was used for comparison, a new water extract had to be created for that sample, as microbial activity may have degraded some of the sugars, which were washed off the cotton over time. A five minute equilibration time after every sample run and blank solutions run intermittently between standards and samples confirmed that there were no residual higher molecular weight carbohydrates eluting from the column in the next sample run. Results of the nine primary constituent sugars of interest found in the cotton fiber water extracts are reported in mg relative to the 1 g of cotton for all samples.

Minicard

The MC is similar to a full-size production card and the analysis was performed by fitting a 10 g cotton fiber sample to a rectangular metal plate template (∼11 cm × 25 cm) at ∼24℃ and 55% relative humidity. The cotton batt was then fed into the card. As the cotton fiber wraps around the roll and the drum of the MC, the “sticky” fibers get stuck on the drum, then those sticky fiber spots are counted and graded, and finally collected for IC analysis.

The MC ratings were determined using a procedure from a previous publication and were categorized into four levels as follow: no stickiness (0) with less than five spots; light stickiness (1) from 5 to 15 spots; moderate stickiness (2) with more than 15 spots of smaller sizes; heavy stickiness (3) with more than 15 spots of larger and varying sizes.¹¹ Wrapping of fibers around the machinery and the size of the spots are also taken into consideration during gradation.¹¹

Sticky spot preparation

For carbohydrate analysis via IC of the sticky spots material collected from the MC, the fibers were peeled off and weighed for each sample replicate. However, for the NONE, LIGHT and two of the MODERATE rated samples, there was not enough sticky material present on the MC for further analysis. Each sticky spot material sample was placed in a centrifuge tube, where 10 mL of ultrapure deionized was added, then vortexed at ∼5000 rpm for 30 seconds, then again for 5 minutes at ∼3500 rpm. The water extract from the vortexed samples was then filtered through a 0.2 µm syringe filter to remove any cotton fibers and particulate, and then it was placed in a 1.5 mL auto-sampler glass vial for analysis on the ion chromatograph instrument via the instrumental method from the Ion chromatography section.

Statistics

All data analysis was conducted using the SAS PROC GLIMMIX with estimates of means and standard errors generated using LS MEANS with the stickiness ratings (NONE, LIGHT, MODERATE and HEAVY) as class and the sugar variables as response. Correlations were done using PROC CORR, using the stickiness rating as a variable and correlating it with the sugar amounts. The correlations between the stickiness ratings and the sugars were performed as a Polyserial correlation using the Likelihood Ratio Test (Pr > ChiSq), and the correlations among the sugars were performed using a Pearson Correlation, both at the 0.05 level of probability. The stickiness ratings data was considered as ordinal with multinomial distribution and the sugar amount data was considered as continuous, but not normally distributed (version 9.4; SAS Institute, Cary, NC).

Results and discussion

In this study, nine constituent sugars (inositol, trehalose, glucose, fructose, trehalulose, sucrose, melezitose, raffinose and maltose) obtained from the surface of cotton fibers via water extraction, and mechanically obtained from the sticky spots of the MC process, were identified and quantified via high-performance anion exchange chromatography (IC). Aliquots of the 25 cotton samples were processed (in triplicate) via the MC and given stickiness ratings of NONE (two samples), LIGHT (eight samples), MODERATE (seven samples) and HEAVY (eight samples), based on the MC rating system. The samples were then named with the characteristic stickiness gradation and a number; for example, sample LIGHT 6.

In the “Raw” cotton fiber water-extracted IC sugar profiles versus Minicard ratings section, the ratings from the MC are compared to the sugar profiles that were determined by the IC, for a proof-of-concept correlation of the surface sugars to the stickiness ratings. In the Sticky spot IC sugar profiles versus Minicard ratings section, the sugars determined via the IC for sticky spot material (collected from MODERATE and HEAVY samples) are compared to the stickiness ratings; the Water-extracted cotton fiber sugar profiles versus sticky spot sugar profiles section relates water extract IC sugar profiles to sticky spot IC sugar profiles.

“Raw” cotton fiber water-extracted IC sugar profiles versus Minicard ratings

A previously developed modified IC method for efficient sugar separation, identification and quantification was used to determine whether a surface sugar profile is comparable to the rating produced by the MC (the chromatogram of the standards is shown in Figure 1).¹² If correlations are found between IC sugar profiles and MC ratings, it may allow for a better understanding of the impact of surface sugars on stickiness and of the makeup of the sticky spots, as well as the future validation of IC as a tool to determine the cause and possible presence of stickiness.

Figure 1.

Ion chromatogram of nine sugars present in 0.1 mg/mL concentrations.

Different portions of the 25 cotton samples were separately put through a water extraction (in triplicate) to collect sugars from the surface of the fibers, then the extracts were analyzed, via the IC instrument, for the nine sugars. The means of the sugar amounts found in the water extract for each sugar (across the NONE, LIGHT, MODERATE and HEAVY MC-rated samples) are presented in Table 1.

Table 1.

Sugar amount mean (in water extract) via ion chromatography (mg) for each stickiness rating

Water IC	n	Inositol	Trehalose	Glucose	Fructose	Trehalulose	Sucrose	Melezitose	Raffinose	Maltose
3 = Heavy	8	0.220^a	0.168^a	0.813^a	1.076^a	2.583^a	0.418^a	1.250^a	0.006^b,c	0.142^a
2 = Moderate	7	0.166^b	0.011^b	0.488^a	0.351^b	0.145^b	0.109^a	0.024^b	0.065^b	0.004^b
1 = Light	8	0.184^a,b	0.018^a,b	0.410^a	0.225^b	0.151^b	0.096^a	0.023^b	0.113^a	0.002^b
0 = None	2	0.173^a,b	0.014^a,b	0.372^a	0.130^b	0.145^b	0.046^a	0.016^b	0.028^b,c	0.000^b

a,b

Within the same sugar, the same letters indicate no difference statistically, and different letters indicate they are different statistically at p < 0.05.

IC: ion chromatography.

The HEAVY rating is significantly different (p < 0.05) from the other ratings for the trehalulose, melezitose, maltose and fructose extracted using water and analyzed using the IC method (Table 1). Trehalulose, melezitose and fructose are the sugars with the highest means within the HEAVY sample set; because of the higher means of trehalulose and melezitose this may indicate that these two sugars have some influence in the stickiness of fibers due to insects. Glucose, fructose, sucrose and maltose showed a distinctive upward trend of increasing extracted sugar amounts as the MC rating increased from NONE to HEAVY. The proportion of the extracted sugars in the latter group is much lower than trehalulose and melezitose for the HEAVY rated samples.

These increases lend to the theory of potentially being able to find a constituent sugar content profile where each surface sugar present in a certain amount may determine a sample’s cause of stickiness. It is also important to keep in mind that a certain threshold of sugar ratios may play a role in affecting the hygroscopies of the individual surface sugars; the combination of low sugar melting point and high hygroscopy could potentially cause accumulation of sticky materials on the textile equipment.¹³ For instance, the melting point of the raffinose (80℃) present in the LIGHT and MODERATE rated samples may have influenced the stickiness of those samples on the MC; for confirmation further analysis would also be needed.

The intricacies of the sugar profiles become even more evident in Figures 2(a)–(c), where bar graphs help to visualize the relationships of the amounts of water-extracted surface sugars in each individual sample compared to its particular MC rating set (keeping in mind that the mg scales on the y-axis are different for each graph). Aside from the general increases in the sugar contents from NONE/LIGHT to HEAVY samples, there is also a noticeable change in the pattern of the ratios of the sugars present. For example, fructose is found to be higher in amount than glucose when the sample set changes from LIGHT rated samples to HEAVY rated samples, confirming the trend of the means shown in Table 1.

Figure 2.

Visual bar graph representation for the sugar amount profiles for cotton water extract samples that were rated via the Minicard as (a) NONE/LIGHT, (b) MODERATE and (c) HEAVY. Mean values for the data are presented in Table 1.

Although sample MODERATE 7 (Figure 2(b)) contains amounts of glucose (1.618 mg) and fructose (1.694 mg) that are much higher with relation to the other MODERATE rated samples; those particular sugar amounts might seem to fit better with the set of HEAVY rated samples (Figure 2(c)); the trehalulose (0.498 mg) value for sample MODERATE 7 is still much lower than the trehalulose values for all of the HEAVY rated samples in Figure 2(c). This fact of having lower trehalulose amounts present could have influenced the MC rating, which put sample MODERATE 7 as a MODERATE rating rather than a HEAVY rating, thus further validating trehalulose’s increased influence on stickiness over that of the reducing sugars.

As with other samples, such as LIGHT 5 and LIGHT 8 (Figure 2(a)), which contain averages of 0.591 and 0.815 mg of glucose and 0.421 and 0.739 mg of fructose, respectively, it becomes evident that high levels of glucose and fructose do not sufficiently indicate whether or not a sample will test as HEAVY stickiness on the MC machine. This information runs contradictory to the popular Benedict test, which is a colorimetric method used to test for the presence of the aldehyde functional group (–CHO). The test works by reducing the cupric ions (Cu⁺ complexed with citrate ions) to cuprous ions (Cu⁺⁺) by the –CHO group, thus resulting in a red cuprous oxide precipitate (Cu₂O).⁴ It is interesting to note that even some samples that tested as LIGHT stickiness on the MC contain amounts of reducing sugars, such as glucose and fructose, that are as high as that of samples that tested HEAVY on the MC.

Table 2 shows the correlations among the sugars in the water extracts of the 25 samples and the MC ratings, where trehalulose and melezitose were highly positively correlated (p < 0.001) to the MC rating values with correlation coefficients of 0.974 and 0.996, respectively. Glucose was positively correlated (p < 0.05) to MC ratings with a correlation coefficient value of 0.477 (Table 2). The fructose obtained from the water extract was moderately correlated with the MC ratings (p < 0.01) at a value of 0.669. These correlation findings may suggest that the two insect sugars highly influence the MC ratings and the higher the rating, the higher the amounts of trehalulose and melezitose on sticky cotton, as shown by the means in Table 1. This information also serves as an indication that the Benedict test may not be a sufficient method to determine the stickiness of a cotton sample, as mentioned before. There is also a suggestion here that while reducing sugars can lead to stickiness either by their presence in insect honeydew (more likely) or by build-up on the processing machinery over time, they do not always cause stickiness.

Table 2.

Correlation values between the nine sugars present in the water extracts and the Minicard ratings

Water IC	N	Mean	SD	Correlations
Water IC	N	Mean	SD	I	T	G	F	TU	S	ME	R	M	RT
1. Inositol (I)	25	0.19	0.05	1
2. Trehalose (T)	25	0.06	0.13	0.265	1
3. Glucose (G)	25	0.56	0.37	0.689‡	0.679‡	1
4. Fructose (F)	25	0.52	0.60	0.593†	0.815‡	0.947‡	1
5. Trehalulose (TU)	25	0.93	1.42	0.314	0.731‡	0.613‡	0.800‡	1
6. Sucrose (S)	25	0.20	0.27	0.367	0.832‡	0.824‡	0.844‡	0.715‡	1
7. Melezitose (ME)	25	0.42	0.71	0.273	0.782‡	0.600†	0.796‡	0.975‡	0.730‡	1
8. Raffinose (R)	25	0.06	0.06	−0.113	−0.393	−0.351	−0.463*	−0.567†	−0.373	−0.583†	1
9. Maltose (M)	25	0.05	0.10	0.208	0.950‡	0.616‡	0.813‡	0.824‡	0.719‡	0.859‡	−0.474*	1
10. Rating (RT)	25	n/a	n/a	0.323	0.957‡	0.477*	0.669†	0.974‡	0.836‡	0.996‡	−0.563†	0.984‡	1

p < 0.05, †p < 0.01, ‡p < 0.001. Means and SDs are for the entire sample set of 25 cottons, across all stickiness levels.

IC: ion chromatography.

The lower correlation coefficient of the glucose may indicate that the higher the MC rating, the glucose level reduces, while the relative fructose increases with respect to the glucose. Trehalose was highly positively correlated (0.957) with the stickiness ratings; this was not surprising, as trehalose is produced by insects and is a known marker in whitefly honeydew.⁴ Maltose is the other sugar that was highly positively correlated with a value of 0.984. Maltose is composed of two molecules of glucose joined together through an α-1.4-glycoside linkage and has been found to be present in the honeydew of most aphid species and is a stimulating marker for aphid predators.¹⁴ Inositol was not significantly correlated to the MC ratings, with a value of 0.323. The trehalose, trehalulose and melezitose (0.975) are highly positively correlated (p-value < 0.001), and these three sugars are produced by insects, which could reaffirm their relationship with stickiness.

The water extract correlations with the MC rating may indicate the following: (1) trehalulose and melezitose are heavily responsible for a cotton sample’s stickiness rating, although the type of insect infestation could be different on each of the 25 samples, with higher infestations in the heavier rated cotton; (2) that other honeydew markers such as trehalose and maltose can backup a cotton’s propensity to be rated as sticky; (3) that we can potentially use the water extract to determine the cause of cotton stickiness when taking into account these sugars’ relationships to one another. Furthermore, the ratio of trehalulose and melezitose in a given sample is not only a determinant of the type of insect causing the infestation, but also potentially a key factor in determining a correlation between surface sugars and stickiness.⁴

Sticky spot IC sugar profiles versus Minicard ratings

As mentioned, IC is not as widely utilized for screening sticky cotton as the Thermodetector and the MC, due to its relative speed and cost of the analyses.² However, significant differences and comparisons could potentially help researchers to better understand the surface sugars present during a stickiness problem, the makeup of the sticky spots, and the validation of IC as a tool to determine fiber stickiness. We examined the relationship between the IC data collected from the sugars present in the actual sticky spots left by processing the samples on the MC versus the MC ratings.

We collected the sticky spots from the MC drum and dissolved the residue in water to obtain the sugar profiles, repeating the preparation and IC methods used in the cotton water extract process, as in the “Raw” cotton fiber water-extracted IC sugar profiles versus Minicard ratings section. The MC rating system is based on the concept that samples rated NONE do not leave sticky spot material behind on the roller and samples rated LIGHT leave very little material, it is not surprising that we could not collect sufficient material for IC analysis on those samples; therefore, for this part of our research we only analyzed the MODERATE and HEAVY ratings. Also, two of the six MODERATE rated samples also did not yield sufficient sticky spot material to be able to perform replicate IC analyses; therefore, the sticky spot sugar profiles for the MODERATE samples reflect only the averages for five of the MODERATE samples.

Table 3 shows the mean values of the sugars analyzed via IC from the sticky spots for comparison to Table 1, which showed the mean values of the sugars present from the “raw” cotton fiber for the MODERATE and HEAVY rated samples. The means are distinctly and significantly different for trehalose, glucose, trehalulose and melezitose, with a strong indication that these particular MODERATE rated samples’ sticky spots tend to contain higher amounts of glucose and fructose relative to the sample sugars, where the HEAVY rated samples have clear indications of insect sugar contaminations (with trehalulose and melezitose and the trehalulose marker increasing over 90%).

Table 3.

Sugar amount means via ion chromatography (mg) collected from each sticky spot in the Minicard

Minicard IC	n	Inositol	Trehalose	Glucose	Fructose	Trehalulose	Sucrose	Melezitose	Raffinose	Maltose
3 = Heavy	8	0.372^a	1.400^a	3.957^b	10.025^a	36.663^a	4.204^a	14.338^a	0.001^a	0.893^a
2 = Moderate	5	0.330^a	0.138^b	15.593^a	16.442^a	2.117^b	1.858^a	0.751^b	0.698^a	0.422^a

a,b

Within the same sugar, the same letters indicate no difference statistically, and different letters indicate they are different statistically at p < 0.05.

IC: ion chromatography

Under the standard of the MC ratings at the USDA ARS at the Southern Regional Research Center in New Orleans, a rating of MODERATE or HEAVY is considered sticky cotton. Table 3 shows us interesting and significantly different trends. Going from MODERATE to HEAVY rated samples, the sticky spots’ trehalulose increases its mass amounts from 2.117 to 36.663 mg and the melezitose increases in mass from 0.751 to 14.338 mg (p-value <0.05). The glucose and fructose reduce their mg content from 15.593 to 3.957 mg and from 16.442 to 10.025 mg, respectively. This may indicate that cotton stickiness is due primarily to the high proportional amounts of trehalulose and melezitose in the HEAVY rated samples, and the reduction of amounts of glucose and fructose could be due to the overwhelming proportional presence of the former sugars.

As previously mentioned, the most informative sugar profile results likely lie in the content ratio relationships between the LIGHT and MODERATE rated samples, as evidenced by the relatively large differences in the sugar means for the MODERATE and HEAVY rate samples in Table 3 (except inositol). Another important factor is that it may be possible to determine the sugars causing stickiness using IC, contrary to the Benedict test assumption that identifying reducing sugars will give a definitive answer on stickiness levels. Figure 3 further visually illustrates the relationship between the MC rating and the sugars contained within the sticky spot material for the individual MODERATE and HEAVY rated samples.

Figure 3.

Visual bar graph representation for the sugar amount profiles for the sticky spot material collected from the samples that were rated via the Minicard as MODERATE or HEAVY. Mean values for the data are present in Table 3.

Since MODERATE and HEAVY rated samples cause processing problems, then the sugar content relationships causing the stickiness issues theoretically fall somewhere near the sugar amounts retrieved from the sticky spots retrieved from the MC for the MODERATE and LIGHT samples. However, one must take special care to take the entire profile of sugars into consideration and not depend on threshold amounts of only one or two sugars. This is because, for example, Figure 3 illustrates that the MODERATE samples have relatively low mg amounts of trehalulose and melezitose; however, the MODERATE samples are still quite capable of causing havoc while processing fiber. Therefore, taking the entire profile into account, we can see that the MODERATE rated samples are likely sticky due to the build-up of glucose and fructose. Readily apparent in Figure 3, when comparing MODERATE (black bars) and HEAVY (gray bars) sticky spot samples overall, glucose and fructose present in the material are much higher in the MODERATE rated samples, leading to the erroneous conclusions of heavy stickiness by the Benedict Test.

Water-extracted cotton fiber sugar profiles versus sticky spot sugar profiles

Using the IC data from the “Raw” cotton fiber water-extracted IC sugar profiles versus Minicard ratings and Sticky spot IC sugar profiles versus Minicard ratings sections, comparisons were made in order to determine whether a sugar profile from cotton that is simply rinsed is related with respect to the material actually forming the sticky spots. Figures 4 and 5 show the average amounts of sugars present in the sticky spots collected from the MC for MODERATE and HEAVY rated samples and from the water extract collected from the “raw” cotton fiber samples. One gram of the “raw” cotton fiber was rinsed to give the sugar amounts present in the water extract, while 10 g of cotton was processed via the MC for sticky spot material collection.

Figure 4.

Overlay of the average sugar amount profiles for cotton water extract and sticky spot samples that were rated MODERATE via the Minicard.

Figure 5.

Overlay of the average sugar amount profiles for cotton water extract and sticky spot samples that were rated MODERATE via the Minicard.

Only microgram to milligram ranges of sticky spot material were dissolved in water for the sticky spot IC analysis, yet the amounts of the sugars collected from the sticky spots are higher than those collected via the water extracts. This is understandable, since more cotton was used in the MC method. This concentration of sugars is also desirable so we can more clearly ascertain the composition of the sugar profiles the physical stickiness methods produce and the relative ratios between the sugars present.

When overlaying the average sugar profiles of the sticky spot solutions with the average sugar profiles of the “raw” cotton fiber water extract in Figures 4 and 5, we observed that the relative ratios of the sugars from the rinse and MC processed methodologies stay roughly the same. The friction of the drum and roll in the MC do not force the sugars present on the surface of a non-sticky cotton fiber to deposit onto the roller and drum to form sticky spots. As a result, we can deduce that the stickiness level rating forms as a result of the concentration and ratios of the sugars present on the cotton surface from high glucose and fructose, and low trehalulose and melezitose in MODERATE stickiness rated cotton, to low glucose and fructose, and high trehalulose and melezitose in HEAVY stickiness rated cotton.

The water-extracted sugar profile would give a similar indication of whether or not there is a sufficient sugar content profile present on the cotton to cause a stickiness problem. As a proof-of-concept, these findings of sugar profiles are encouraging as they relate to stickiness ratings, and the profile ratios may give more indication of a correlation with physical testing ratings.

It is important to note that the averages of the mg amounts of the sugars present in MODERATE and HEAVY rated water extracts maintain similar profile distributions as the average mg amounts found in the sticky spot material for those rated samples. This signifies that an IC cotton water extract may give a good indication of the composition of the sticky material that will be left behind by the MC. Thus, the concentration, ratio and distribution of the sugars present may potentially forecast the cause of potential stickiness in cotton. Further work should be performed using many more samples and replications in order to increase the precision and reduce the variability of the experiments among samples and their carbohydrates, and to find robust sugar content ratios involved in causing stickiness.

Although the sugar profile ratio from the “raw” cotton fiber’s water extract and the sugar profile ratio from the sticky spot solution are significantly different due to their sugars amounts, the sugars actually causing the stickiness are high in both solutions (Figures 4 and 5), and the sugar profile ratios of MODERATE and HEAVY stickiness rated samples do indeed remain roughly the same.

Conclusions

We have shown a proof-of-concept study comparing the IC-obtained surface sugar profiles of 25 NONE, LIGHT, MODERATE and HEAVY MC-rated cotton fiber samples to their MC ratings, which revealed that there are identifiable trends in the surface sugar content of cotton and its MC rating. A combination of nine surface entomological and physiological carbohydrates were identified and quantified to establish whether IC could potentially be used to indicate a stickiness issue in cotton and the influential sugars. We found promising preliminary data indicating that trehalulose and melezitose have the highest sugar concentrations in these particular HEAVY rated samples and they, along with the potential markers trehalose and maltose, have the highest positive correlations to the MC ratings. It was also found that glucose and fructose have MODERATE correlations to the MC ratings.

The IC analysis of the sticky spot material collected from the MC drum showed that trehalulose and melezitose have the highest presence in the HEAVY rated cotton samples, with glucose and fructose being the sugars likely responsible for causing the MODERATE ratings. The relative trend and sugar ratios also were similar (although the mass amounts change) in the “raw” fiber rinse compared to the sticky spot materials.

The important finding in this work was in the importance of taking the entire sugar content profile into consideration when trying to determine the cause of cotton’s MC stickiness rating. While trehalulose and melezitose are indeed stickiness culprits, other sugars may be responsible for a processing issue through build-up. We have shown that, at this time, IC is a great complementary tool to help determine cotton stickiness causes and to aid in understanding the sugar content involved in it.

This sugar profile consistency proves that a water extract yields similar proportional information of the surface sugars present on sticky samples as the ones obtained from the MC, especially for glucose, fructose, trehalulose and melezitose. It can be theorized that if it is possible to isolate the exact sugar mass amounts and relationships that progress a sample from a LIGHT to a MODERATE to a HEAVY MC rating, then it may be possible that only accurate IC information for those four sugars mentioned above would be needed in a water extract to successfully predict cotton fiber stickiness. Therefore, this correlational relationship derived between cotton surface sugar profiles and physical stickiness testing methods are the rationale for future in-depth relational studies.

For a completely thorough stickiness fingerprint, and thus a predictive comparison between the water-extracted sugar profile and MC ratings, an automated pretreatment of the chromatographic profiles or pattern-recognition IC software may be needed, as well as a larger sample of cotton fibers with more replications to reduce variability between samples and sugars, for a more precise and less variable analysis.¹⁵

Footnotes

Declaration of conflicting interests

The authors declared no potential conflicts of interest with respect to the research, authorship and/or publication of this article.

Funding

The authors received no financial support for the research, authorship and/or publication of this article.

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