Spatial variability of cotton plume charactersAbstract
The final quality of cotton produced is critically influenced by the characteristics of the fibers. The objective of this study was to map and evaluate the spatial correlation between cotton lint productivity and lint quality parameters measured by the High Volume Instruments (HVI) using geostatistical analysis. The x and y axes of a Cartesian coordinate system were defined, and a geostatistical experimental grid was established. The sampling grid consisted of 100 equally spaced points arranged in a square grid with 9.9 m spacing. The analyses performed included cotton lint productivity (PR), spinning consistency index (SCI), micronaire (Mic), upper half average length (UHML), short fiber index (SF), strength (Str), and leaf grade (TrId). Results were presented through semivariograms and kriging maps of the studied attributes, showing zones with the observed values. Results also indicate that cotton (cultivar FM 978 6LTP) grown in the Chapadões region, located in the Midwest of Brazil, has fiber test results very similar to those found in cotton varieties in different parts of the world such as Africa, Europe, and Asia. PR, SCI, Mic, UHML, and SF showed spatial variability. The attributes SCI and UHML showed a negative correlation with cotton lint productivity (R2 = 0.96 and R2 = 0.96 respectively), while SF showed a positive correlation (R2 = 0.60) with cotton lint productivity.
Keywords:
precision agriculture; Gossypium hirsutum L; HVI; productivity
Introduction
Cotton (Gossypium hirsutum L. var. latifolium Hutch.) cultivation is of great importance worldwide, including in Brazil. Its production provides raw material for the textile industry, agrobusiness, and byproducts for human consumption (INDEA, 2023). Its wide range of applications makes cotton one of the most important agro-industrial crops (Dias & Santos, 2023).
Among the various uses of cotton, lint is the primary comercial product. According to Moura et al. (2020), the longer fibers of seed cotton are mainly used for the manufacture of yarns for the textile industry. These same authors also report that short fibers surrounding the seed, known as linters (fibers less than 12 mm in length in Gossypium hirsutum L. var. latifolium Hutch), are used in the manufacture of absorbent cotton, rustic fabrics, upholstery, filters, and gunpowder wicks.
Given the diversity of cotton fibers and their characteristics, a laboratory analysis is essential to assess fiber quality. The final quality of the cotton is determined by the intrinsic and extrinsic fiber characteristics. Intrinsic characteristics, also known as fiber technological properties, are genetically controlled but can be influenced by the environmental conditions. These properties are quantified using the High Volume Instruments (HVI) (Costa et al., 2006).
Cotton fiber quality is evaluated by visual classification and laboratory analysis using the High-Volume Instrument (HVI) (Sayeed et al., 2021). HVI measures the technological properties of cotton fibers, providing parameters that are essential for determining their economic value and suitability for different textile applications (De-Carli & Oliveira, 2021). The widespread adoption of HVI has significantly advanced cotton quality evaluation and commercialization, enabling the progress of cotton farming globally, even though it is an ancient crop.
Advances in precision agriculture, particularly geostatistical techniques, have improved the understanding of spatial variability in crop data. These methods enable the analysis of spatial correlations between a primary variable and other agronomic or quality related-variables. According to Montanari et al. (2015) and Oliveira et al. (2023) geostatistical techniques such as simple data interpolation (kriging) and cross-interpolation (cokriging) enable the estimation of the spatial variability of a target variable based on another, more easily measured variable. These approaches can be used to investigate spatial correlations between cotton lint productivity and its intrinsic fiber quality characteristics.
Thus, the objective of this study was to map and evaluate the spatial correlation between cotton lint productivity and lint quality parameters measured by the High Volume Instruments (HVI) using geostatistical analysis. Consequently, these results could be compared with the fiber qualities of cotton produced in other parts of the world.
Material and Methods
The study was conducted in Paraíso das Águas, Mato Grosso do Sul State, Central-West region of Brazil. The experimental area corresponded to Fazenda Indaiá II, situated at geographic coordinates: latitude 19º1’33” S, longitude 53º0’37” W and altitude of 608 meters above sea level. According to the Köppen and Geiger climate classification, the region is characterized by a humid tropical climate (Cfa), with average temperatures ranging from 14 to 31 °C (Alvares et al., 2013). The average annual rainfall was 1303 mm. The monthly average air temperature and rainfall recorded during the experimental period are presented in Figure 1.
Monthly average air temperature and rainfall distribution in the study area throughout the 2022/23 growing season.
In the selected experimental area, the sector of the cultivated area with the highest slope variation and terrain heterogeneity was considered in order to obtain a wider range of values among the sampled points. According to Santos et al. (2018), the soil was classified as Quartzarenic Neosol with a sandy texture. The experimental área cultivated with the cotton cultivar FM 978 6LTP comprised 60 ha. Sowing was carried out on November 20, 2022, with 0.90 m spacing between rows, resulting in a plant density of 95,000 plants ha-1.
The x- and y- directions of the Cartesian coordinate system were defined, followed by the stablishment of a regular geostatistical sampling grid. The grid consisted of 100 sampling points equally spaced in a square arrangement, with 9.9 m intervals between points. (Figure 2). The grid was generated using AutoCAD (2025), a software available in the student version, covering an experimental area of 0.98 ha.
Geostatistical grid with 100 sampling points established in the experimental area Fazenda Indaiá II, Paraíso das Águas, MS, Brazil.
The crop cycle of the analyzed cultivar was completed after 187 days. On May 26, 2023, three plants were collected from each sampling point and subject to analysis. The material from healthy cotton bolls was separated, processed and weighed. After processing, the obtained lint samples were forwarded for evaluation according to established cotton classification standards.
Geostatistical analyses were conducted at the Chapadão do Sul Campus (CPCS) of the Federal University of Mato Grosso do Sul (UFMS). The experimental semivariograms were modeled according to the spatial variability of the data: Gaussian (Gau), Exponential (Exp), or Spherical (Sph) models were selected for attributes showing spatial dependence, while the Pure Nugget Effect (PNE) was considered When no spatial dependence was detected. (Oliveira et al., 2021). Laboratory analyses were performed at AMPASUL (South Mato Grosso Cotton Producers Association), located in Chapadão do Sul, Brazil. Fiber quality classification was carried out using the Uster High Volume Instruments (HVI) 1000. By integrating fiber quality measurements with productivity data, seven attributes were obtained for subsequent analysis. The evaluated atributes were defined according to the requirements established in Normative Instruction No. 24, of July 14, 2016 (MAPA, 2016) as follows:
Cotton lint productivity (PR)
Cotton lint productivity was determined by harvesting all bolls (lint and seed) from three randomly selected plants at each sampling point. After processing, only the lint fraction obtained from each sampling point was considered for analysis. This lint mass was weighed using a precision balance, and the average lint yield per plant was expressed in grams. Subsequently, this value was converted from grams per plant to arrobas (@). Cotton lint productivity per hectare (@ ha-1) was calculated by multiplying the lint yield per plant by the plant population density per hectare.
Spinning Consistency Index (SCI)
The Spinning Consistency Index (SCI) was calculated using a multiple regression equation developed from the interrelationships and correlations between the physical properties of cotton fibers and textile yarns performance. The SCI is used by spinning mills for cotton classification, storage management, and the selection of blends among cotton bales to optimize raw material homogenization, process stability and logistics. Therefore, it contributes to increased spinning efficiency, improved product quality, and cost optimization.
The data analysis involved the generation of spatial distribution maps using kriging and cokriging techniques in GS+ software version 7.0. Subsequently, spatial correlations among the study variables were assessed after the construction of their respective spatial patterns. This analysis was conducted using the output files generated by GS+ software, while maintaining the original spatial coordinates of the sampling points to preserve the spatial structure of the dataset.
Micronaire (Mic)
Micronaire is an index that reflects the combined effects of cotton fiber fineness and maturity. The micronaire values resulting from fiber testing are influenced by variations in fiber fineness and maturity, which are determined by both the cotton cultivar and environmental conditions during crop development.
The micronaire index can be used to assess the thickness and maturity of cotton fibers (Matic-Leigh & Cauthen, 1994; Long et al., 2009; Adel et al., 2011; Siddiqui et al., 2020; Sief et al., 2022; Bange et al., 2022). When the micronaire index is below 3.0, cotton fibers are classified as very fine. Values ranging from 3.0–3.9 indicate fine fibers, whereas values between 4.0 and 4.9 correspond to medium fibers. Fibers with micronaire values from 5.0–5.9 are classified as coarse; and values above 6.0 indicate very coarse fibers. According to Jumaniyazov et al. (2021), the optimal micronaire range for cotton fibers is between 3.5 and 4.9.
Upper half mean length (UHML)
The upper half mean length (UHML), defined as the average length of the 50% (fifty percent) longest cotton fibers in a sample, is expressed in inches to three decimal places or in millimeters to two decimal places. This parameter is widely used for the international classification and commercialization of cotton.
Short fiber index (SFI)
The Short Fiber Index represents the percentage of fiber with lengths below 0.50 inches (12.7 mm) present in a cotton sample. This index can be determined using mathematical equations or derived from the fiber length distribution curve generated by fiber optic measurements. The SFI is calculated through a sophisticated algorithm that converts the optical signal obtained from the fiber array into a mathematical fiber length distribution curve.
Strength (Str)
Fiber strength representes the force, expressed in grams-force (gf), required to break a bundle of cotton fibers with a linear density of one tex. The maximum force (Max Force) corresponds to the breaking force required to rupture the fiber bundle and is expressed in grams-force. Tex is a unit of linear density defined as the mass, in grams, of 1000 meters of textile material, including fibers, mats, ribbons, wicks, and yarns. This parameter is used in standardized test methods to determine cotton fiber tenacity and elongation at break using High Volume Instrument (HVI)-type systems.
Leaf grade (TrId) (L.G.)
Leaf Grade is a classification code (TrId) obtained by comparing cotton samples with the Universal Physical Standards. Reference parameters establish the equivalence between the Universal Physical Standards of the Leaf Grade (L.G.) and the percentage of area (% Area) occupied by impurities relative to the total area measured by the trash meter of HVI-type systems.
Results and Discussion
A descriptive analysis of cotton lint productivity and fiber quality attributes is presented in Table 1. The evaluated parameters exhibited considerable variation among the studied attributes.
Ibrahim et al. (2021), using HVI analysis, characterized the fiber properties of six Egyptian cotton varieties (Gossypium barbadense L.) from the Giza series, including four long-staple and two extra long-staple cultivars. The results reported by these authors are consistent with those obtained in the present study. For the Upper Half mean length (UHML), Ibrahim et al. (2021) observed values ranging from 28.70 to 35.50 mm, whereas the 100 sampling points evaluated in the presente study showed a variation from 29.14 and 31.79 mm. Similarly, the Short Fiber Index (SF) reported by these authors ranged from 5.40 to 7.80 %, while the values obtained in the present study ranged from 5.4 and 11.2 %. These results indicate that the cotton cultivated in the Chapadões region, located in the Brazilian Midwest, exhibits fiber quality characteristics comparable to those reported for Egyptian cotton cultivar planted in Africa. One point that stands out is that cotton is considered the most important fiber crop in the world. Cotton is considered one of the most importante natural fiber crops worldwide, and Egyptian cotton has being internationally recognized as the best fiber crop quality. Furthermore, Egyptian cotton remains an important agricultural commodity in Egypt (El-Bary, 2013; Abdel-Aty et al. 2023; Ibrahim et al. 2022).
It is worth noting that the Egyptian varieties (Giza series) used for comparison belong to the species Gossypium barbadense, which is genetically recognized for producing extra-long and high-strength fibers, while the cultivar evaluated in this study (FM 978) belongs to the species Gossypium hirsutum. Despite this fundamental genetic difference, the fiber quality attributes observed in Brazilian cotton were comparable to those reported for Egyptian cotton. This finding suggests that the edaphoclimatic conditions and crop management practices adopted in the Chapadões region, located in the Brazilian Midwest may have contributed to the Enhanced expression of the qualitative expression fiber quality features in the Gossypium hirsutum cultivar, resulting in characteristics approaching those typically associated with G. barbadense.
Kartal & Efe (2021), evaluating eight cotton cultivars from Turkey, using HVI, reported fiber length, fiber strength, and Spinning Consistency Index (SCI) values of 30.21 m, 31.76 g tex-1, and 104.68, respectively. All these attributes corroborate the present study, indicating that the cotton grown in the Chapadões region, located in the Midwest of Brazil, has fiber quality characteristics comparable to those reported for Turkish cotton cultivars.
Analyzing the fiber quality indicators obtained through HVI analysis, Jumaniyazov et al. (2021), verified a micronaire index of 4.0 and the fiber (Mic) strength of 32.23 g tex-1 for cotton fibers. These values fall within the ranges observed in the present study, and are close to the respective mean values, indicating that cotton cultivated in the Chapadões region, located in the Brazilian Midwest, has fiber test results very similar to those found in cotton cultivars grown in Central Asia, particularly Uzbekistan.
Table 2 presents the geostatistical analyses of the simple semivariograms for cotton lint characteristics, as well as the cross-semivariograms, highlighting the spatial correlations among the evaluated variables. Positive spatial correlation was observed between cotton lint productivity and the Short Fiber Index (PR = f(SF)), whereas negative spatial correlations were identified between cotton lint productivity and the Spinning Consistency Index (PR = f(SCI)) and upper half mean length (UHML).
Estimated parameters for the simple and crossed semivariograms of the components in relation to the variables cotton lint productivity (PR), spinning consistency index (SCI), micronaire (Mic), upper half average length (UHML), short fiber index (SF), strength (Str) and leaf grade (TrId), in cotton plants cultivated in the municipality of Paraíso das Águas, MS.
Table 2 shows that fiber strength (Str) and leaf grade (TrId), presented a pure nugget effect, indicating the absence of spatial dependence between the sampled points. As the textile industry representes the main consumer sector of cotton, fiber quality is a critical attribute that direct influences the comercial value of the product. This quality is affected, among other factors, by harvesting practices, which require careful management to prevent deterioration of the harvested cotton and maintain its market value (Embrapa, 2005). Therefore, mechanized harvesting operations must be conduct using a modern equipment capable of performing multiple functions, including temporary storage, pressing, baling, and wrapping the fibers in a polyethylene film that protects the seed cotton, which can weigh up to 2,500 kg (De-Carli & Oliveira, 2021). These authors also highlighted that cylindrical roll baling technology allows continuous harvesting operations, reducing interruptions for unloading and minimizing the incorporation of impurities into the harvested cotton. In this context, it is important to emphasize that Leaf Grade is influenced not only by harvesting practices but also by crop management strategies, such as the application of growth regulators and defoliants before harvesting, which contribute to reducing leaf retention (TrId) in cotton bolls.
Table 2 also presents the cross-validation results of the semivariogram models, which are essential for evaluating the reliability of the fitted semivariograms and the accuracy of the generated kriging maps (Oliveira et al., 2023).
The cross-semivariograms of PR = f(SCI) and PR = f(UHML) indicated an inverse spatial correlation due to the negative sign of the nugget and sill parameters. This negative relationship resulted in a downward curvature of the cross-semivariogram models, indicating that locations with higher cotton lint productivity were associated with lower SCI and UHML values, respectively. Conversely, the cross-semivariogram for PR = f(SF) revealed a direct spatial correlation, indicating that locations with higher cotton lint productivity were also associated with higher SFI values.
Water availability during the cotton boll formation period is a critical factor influencing fiber development and quality. In the present study, a positive spatial correlation was observed between cotton lint productivity (PR) and the short fiber index (SF), indicating that areas with higher productivity tended to have a higher percentage of short fibers. This relationship may be associated with the rainfall distribution observed in the experimental area during the crop cycle, as presented in Figure 1. Although the accumulated precipitation during the crop cycle was 1303 mm, a marked reduction in rainfall occurred in February (230 mm), coinciding with the boll development and fiber elongation stages of cotton in the Brazilian Midwest. In comparison, January and March recorded precipitation volumes of 280 mm and 190 mm, respectively, indicating that February was not the driest month in absolute terms. However, this period corresponds to a phase of high crop water demand, during which water deficit may restrict fiber elongation and contribute to an increase in the proportion of short fibers. Thus, the similarity of SFI values observed in the present study and those reported for cotton cultivars from other countries, such as Egypt, may be related to comparable physiological responses of cotton plants to water limitations occurring critical phenological stages.
The simple and crossed semivariograms (left panels), as well as the kriging and cokriging maps (right panels) of the variables evaluated in relation to cotton lint productivity are presented in Figures 3 and 4.
Kriging maps and simple semivariograms of the evaluated cotton properties. (A) Cotton lint productivity (PR), (B) Spinning consistency index (SCI), (C) Micronaire (Mic), (D) Upper half mean length (UHML), a (E) Short fiber index (SF) of cotton plants cultivated in Paraíso das Águas, Mato Grosso do Sul, Brazil.
Cokriging maps and cross semivariograms (A) Cotton lint productivity as a function of spinning consistency index (SCI): PR = f(SCI), (B) Cotton lint productivity as a function of upper half mean length (UHML): PR = f(UHML) and (C) Cotton lint productivity as a function of short fiber index SF: PR = f(SF) in cotton plants cultivated in Paraíso das Águas, Mato Grosso de Sul, Brazil.
Figure 3A presents the kriging map of cotton lint productivity (PR). The regions exhibiting higher cotton lint productivity correspond to areas with more favorable soil physical conditions, characterized by lower soil compaction and, consequently, higher cotton lint productivity (Oliveira Rampazzo et al., 2024). However, cotton lint productivity is also influenced by optimal crop management practices and the physiological development stage of the plants. The period from seedling emergence to the emission of the first true leaf is classified as stage V0. Subsequently, the vegetative stages are defined according to the development of successive true leaves: V1 corresponds to the period from the end of V0 until the second true leaf reaches a main vein length of 2.5 cm, followed by V2, V3, V4, V5, and subsequent stages according to the same criterion. During the reproductive phase, the stages aredesignated as B1, beginning with the appearance of the first visible flower bud, followed by sequential stages (B2, B3, etc) according to the development of additional flower buds. After flowering, the nomenclature changes from “Bn” to Fn, representing the opening of the flower derived from each respective flower bud. Finally, with the emergence of the first boll, the crop enters the boll development stage, designated as C1, followend by subsequent stages (C2, C3, etc.) (Dias & Santos, 2023).
Direct selection based solely on yield is difficult and inefficient (Abdel-Aty et al., 2022; Shah et al., 2022), due to the complex interactions among agronomic traits and environmental factors (Lamlom et al., 2024). Therefore, a comprehensive understanding of cotton fiber quality parameters and their effects on the spinning process and yarn quality is vessential (Tesema, 2024). Figure 3B shows the spatial distribution of the spinning consistency index (SCI), which is considered a strong indicator of fiber quality and its potential added value. The kriging map (Figure 3B) revealed considerable spatial variability in SCI values, with the eastern regions exhibiting the lowest index value. According to Kartal & Efe (2021) the ginning system can significantly influence SCI values, as processing conditions may affect fiber properties and, consequently, yarn performance.
The Micronaire (Mic) variable (Figure 3C) shows areas with lower analyzed indices in the central region of the map. The Micronaire Index is an important parameter for assessing cotton fiber fineness, maturity, and natural linear density (Liu et al., 2014). This measurement is based on the relationship between the air permeability of the fiber sample and its fineness (Jumaniyazov et al., 2021). Therefore, the micronaire index provides valuable information regarding fiber thickness and maturity (Long et al., 2009; Adel et al., 2011). The price decreases as micronaire values deviate from the optimal range. However, changes in micronaire values do not alter the intrinsic cotton fiber type (Jumaniyazov et al., 2021).
Thermal conditions also exerted a significant influence on cotton fiber technological quality, particularly affecting micronaire (Mic) and strength (Str) attributes. The average temperature throughout the crop cycle ranged from 20 °C to 24 °C (Figure 1). High temperatures, especially during the fiber maturation phase, can accelerate fiber development and result in thinner cell walls and immature fibers, which are associated with lower micronaire values and reduced fiber strength. On the other hand, periods of moderate temperatures can favor cellulose deposition and cell wall thickening, increasing fiber maturity and, consequently, increasing micronaire values. The absence of spatial dependence for fiber strength (Str) observed in this study may indicate that thermal conditions were relatively homogeneous in the area or that other factors, such as cultivar genetics, had a greater influence on this characteristic. The similarity between of micronaire and strength values obtained in this study and those reported for cotton cultivated in temperate and tropical regions of different continents suggests that the environmental conditions of the Chapadões region in the Brazilian Midwest, despite their specific characteristics, promote fiber quality responses comparable to those observed in diverse production environments, such as Turkey and Uzbekistan. These findings reinforce the adaptability of cotton and the applicability of HVI-derived quality parameters as universal indicators of fiber performance.
The upper half mean length (UHML) (Figure 3D) showed spatial variability within the studied area, with most values ranging from 30.1 to 31.6 mm. It was also observed that the regions with the highest UHML values did not correspond to the most productive areas, as indicate by the comparison with Figures 3A, 3B, and 4B. Cotton fiber length is commonly expressed as mean length and upper half mean length (UHM). Fibers shorter than 0.5 inches (12.7 mm) contribute to the Short Fiber Index (SF), which is presented in the kriging map in Figure 3E. The values shown on this map represent the percentage of short fibers relative to the total fiber weight in the analyzed sample.
The advantage of relating attributes through cross-semivariogram is that an attribute that is easier to obtain to estimate another atribute that is more difficult or costly to measure. In the present study, cotton bolls can be collected close to harvest, and the fiber quality characteristics can be determined using HVI analysis. Based on fiber properties, such as SCI, UHML, and SF, it is possible to estimate cotton lint productivity through spatial relationship. Information on fiber quality is important for determining the potential end use of cotton, whether for yarn production for domestic markets or export purposes.
Fiber length parameters are determined by calculating the light transmission curve generated by scanning the cross-section of a compressed fiber bundle with a light source. The measurement extends from the compression point to the end of the clamp-shaped support used in special clamps. Depending on the change in the light intensity transmitted through the fiber sample, parameters sucha as upper Half mean length, a longitudinal uniformity index, and short fiber content are determined (Jumaniyazov et al., 2021).
The coded results of laboratory analyses are subsequently reported on the bale label using the acronym HVI (High Volume Instrument - equipment used to measure the intrinsic characteristics of cotton fiber) (Sayeed et al., 2021). These results are fundamental for cotton valuation and for determining its suitability for specific applications within the textile industry, including both domestic and international markets (De-Carli & Oliveira, 2021).
Conclusions
Results indicate that cotton fibers (cultivar FM 978 6LTP) cultivated in the Chapadões region, located in the Midwest of Brazil, exhibited fiber quality parameters comparable to those reported for cotton cultivars produced in major cotton-growing regions of Africa, Europe and Asia.
Cotton lint productivity (PR), Spinning Consistency Index (SCI), Micronaire (Mic), Upper Half Mean Length (UHML), Short Fiber Index (SF) showed spatial variability.
The results demonstrate that key cotton lint quality attributes, such as length (UHML), spinning consistency (SCI) and short fiber index (SF), showed significant spatial variability within the growing area, and were spatially correlated with lint productivity. These findings indicate that the technological quality of cotton fiber is determined not only by the genetic characteristics of the cultivar, but also by environmental conditions experienced during crop development. In particular, the water availability, light, and temperature conditions prevailing in the Chapadões region of Midwestern Brazil, especially during the critical phases of boll formation and fiber development, directly influenced parameters such as micronaire and fiber strength.
It is important to emphasize that the present study was conducted using the FM 978 6LTP cotton cultivar. This cultivar exhibited mean fiber quality characteristics of 30.51 mm for Upper Half Mean Length, 31.41 g tex⁻ 1 of fiber strength and a micronaire value of 4.44, all of which fall within the expected range for the cultivar. These results indicate that fiber quality expression under field conditions was consistent with its genetic potential. However, the spatial variability data observed in the presente study demonstrates that fiber quality characteristics can vary significantly according to the growing environment and crop management practices. Consequently, these findings should not be generalized to other cotton cultivars, as genotype-specific responses to environmental factors may differ. Thus, future studies evaluating multiple cultivars under contrasting environmental conditions are warranted to improve theunderstanding of genotype x environment interaction governing cotton fiber quality in the Chapadões region of Midwestern Brazil.
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Source: Adapted from 
Source: Adapted from 
