Automation continues to play a greater role in agricultural production with commercial systems now available for machine vision identification of weeds and other pests, autonomous weed control, and robotic harvesters for fruits and vegetables. The growing availability of autonomous machines in agriculture indicates that there are opportunities to increase automation in cotton production. This article considers how current and future advances in automation has, could, or will impact cotton production practices. The results are organized to follow the cotton production process from land preparation to planting to within season management through harvesting and ginning. For each step, current and potential opportunities to automate processes are discussed. Specific examples include advances in automated weed control and progress made in the use of robotic systems for cotton harvesting.

Within-sample variation in cotton fiber length is important when explaining variation in yarn quality. However, typical High Volume Instrument (HVI) length parameters, the Upper Half Mean Length (UHML) and Uniformity Index (UI), do not characterize the total within-sample variation in fiber length. HVI fiber length measurements are based on the fibrogram principle where the HVI generates a curve called a fibrogram and reports the UHML and UI. Our results, based on 19,628 commercial bales, reveal that the typical HVI length measurements do not characterize unique types of length variation. Fibrograms from a subset of 538 commercial samples suggest that the fibrograms capture additional within-sample variation in fiber length that is not being currently reported. Two additional sets of samples were then used to evaluate the importance of this additional length variation. Partial Least Square Regression models and leave-one-out cross-validation reveal that the HVI fibrogram explains yarn quality better than current HVI length parameters and is comparable with the Advanced Fiber Information System (AFIS) length distribution by number. The validation results show that the models built with the HVI fibrogram are better than models with the current HVI length parameters and at least as good as the AFIS length distribution by number when predicting yarn quality. Fiber length variation captured by the whole fibrogram could provide a new tool to breeders for selecting breeding lines and spinners for purchasing cotton bales.

The lint yield and fiber quality of cotton produced in the Southern High Plains of the USA have improved over the last decade, renewing interest in finding harvest and ginning practices that better preserve fiber quality. Previous research showed that picker harvesting and roller ginning may better preserve fiber quality, but conventional roller ginning was too slow to be adopted as the primary ginning system used for Upland cotton. Advancements in roller ginning technology have increased the ginning rate per unit width of rotary-knife roller gins to approximately equal that of saw gins. Research has shown that improvements in nep content and fiber length characteristics afforded by conventional roller ginning compared to saw ginning are maintained by the new high-speed roller gins (HSRGs). The objective of this work was to compare the fiber quality, seed quality, ginning rate, and lint turnout of Upland cotton produced in the Southern High Plains, harvested using a picker or a stripper, and ginned using saw or HSRG systems. The findings of this work indicate that the HSRG substantially improved the length characteristics of the Upland cultivars tested regardless of harvest method. Turnout was higher for the HSRG and for picker harvested cotton. Nep content was reduced for picker harvested cotton and the HSRG. The fiber length distribution and nep content improvements from the HSRG system make this fiber more attractive to ring spinning mills that produce high-count yarns for high-value products.

There is a need for low-cost, high-accuracy measurement of water content in various materials. This study assesses the performance of a new microwave swept frequency domain instrument (SFI) that has promise to provide a low-cost, high-accuracy alternative to the traditional and more expensive time domain reflectometry (TDR). The technique obtains permittivity measurements of soils in the frequency domain utilizing a through transmission configuration, transmissometry, which provides a frequency domain transmissometry measurement (FDT). The measurement is comparable to time domain transmissometry (TDT) with the added advantage of also being able to separately quantify the real and imaginary portions of the complex permittivity so that the measured bulk permittivity is more accurate that the measurement TDR provides where the apparent permittivity is impacted by the signal loss, which can be significant in heavier soils. The experimental SFI was compared with a high-end 12 GHz TDR/TDT system across a range of soils at varying soil water contents and densities. As propagation delay is the fundamental measurement of interest to the well-established TDR or TDT technique; the first set of tests utilized precision propagation delay lines to test the accuracy of the SFI instrument’s ability to resolve propagation delays across the expected range of delays that a soil probe would present when subjected to the expected range of soil types and soil moisture typical to an agronomic cropping system. The results of the precision-delay line testing suggests the instrument is capable of predicting propagation delays with a RMSE of +/−105 ps across the range of delays ranging from 0 to 12,000 ps with a coefficient of determination of r² = 0.998. The second phase of tests noted the rich history of TDR for prediction of soil moisture and leveraged this history by utilizing TDT measured with a high-end Hewlett Packard TDR/TDT instrument to directly benchmark the SFI instrument over a range of soil types, at varying levels of moisture. This testing protocol was developed to provide the best possible comparison between SFI to TDT than would otherwise be possible by using soil moisture as the bench mark, due to variations in soil density between soil water content levels which are known to impact the calibration between TDR’s estimate of soil water content from the measured propagation delay which is converted to an apparent permittivity measurement. This experimental decision, to compare propagation delay of TDT to FDT, effectively removes the errors due to variations in packing density from the evaluation and provides a direct comparison between the SFI instrument and the time domain technique of TDT. The tests utilized three soils (a sand, an Acuff loam and an Olton clay-loam) that were packed to varying bulk densities and prepared to provide a range of water contents and electrical conductivities by which to compare the performance of the SFI technology to TDT measurements of propagation delay. For each sample tested, the SFI instrument and the TDT both performed the measurements on the exact same probe, thereby both instruments were measuring the exact same soil/soil-probe response to ensure the most accurate means to compare the SFI instrument to a high-end TDT instrument. Test results provided an estimated instrumental accuracy for the SFI of +/−0.98% of full scale, RMSE basis, for the precision delay lines and +/−1.32% when the SFI was evaluated on loam and clay loam soils, in comparison to TDT as the bench-mark. Results from both experiments provide evidence that the low-cost SFI approach is a viable alternative to conventional TDR/TDT for high accuracy applications.

The tensile properties of cotton are essential quality traits for determining the performance of a material in textile processing. Characterization of the tensile properties of cotton has evolved from manual assessments by a human to a diverse series of mechanical methods. The early techniques of characterizing tensile properties of fibres were carried out using modified yarn testing equipment and bundles of cotton fibres. In the mid-twentieth century, instruments specifically designed to measure the tensile properties of cotton fibres were developed and adopted by the industry. The early developments in fibre-specific instruments utilized a flat bundle approach that dominated the industry until the advent of high-speed cotton testing with the High Volume Instrument (H.V.I.) implementation in the later part of the twentieth century. The H.V.I. utilizes a tapered beard approach to arranging the fibres for testing. Although tensile properties consist of breaking strength and elongation, the focus has been mainly on breaking strength. The textile industry recognized the importance of elongation early on. However, the difficulties in measuring the relatively small breaking elongations with accuracy, precision, and efficiency relegated the measurement to an afterthought. Modern high-speed testing has made elongation testing practical; however, the lack of calibration materials limited the use of elongation in comparing results. The recent development and implementation of elongation calibration cottons for high-speed tensile testing has renewed interest and restored the feasibility of characterizing cotton for strength and elongation. The history of characterizing cotton fibre tensile properties is reviewed from manual to modern high-speed automated testing. The relationship between fibre strength and elongation is discussed for single-fibre and bundle testing. Approaches to assess the tensile properties of cotton, such as considering the modulus and the work-to-break, are discussed. Factors that may influence fibre elongation, such as genetics and environment, are discussed, and the influence of elongation on textile processing and quality.

The removal of plastic contamination in cotton lint is an issue of top priority to the U.S. cotton industry. One of the main sources of plastic contamination showing up in marketable cotton bales, at the U.S. Department of Agriculture’s classing office, is plastic from the module wrap used to wrap cotton modules produced by the new John Deere round module harvesters. Despite diligent efforts by cotton ginning personnel to remove all plastic encountered during unwrapping of the seed cotton modules, plastic still finds a way into the cotton gin’s processing system. To help mitigate plastic contamination at the gin; an inspection system was developed that utilized low-cost color cameras to see plastic on the module feeder’s dispersing cylinders, that are normally hidden from view by the incoming feed of cotton modules. This technical note presents the design of an automated intelligent machine-vision guided cotton module-feeder inspection system. The system includes a machine-learning program that automatically detects plastic contamination in order to alert the cotton gin personnel as to the presence of plastic contamination on the module feeder’s dispersing cylinders. The system was tested throughout the entire 2019 cotton ginning season at two commercial cotton gins and at one gin in the 2018 ginning season. This note describes the over-all system and mechanical design and provides an over-view and coverage of key relevant issues. Included as an attachment to this technical note are all the mechanical engineering design files as well as the bill-of-materials part source list. A discussion of the observational impact the system had on reduction of plastic contamination is also addressed.