ASPRS Annual Conference Proceedings May 2004 * Denver, Colorado ASPRS – 70 years of service to the profession DETERMINATION OF THE SPATIAL VARIABILITY OF COTTON FIBER QUALITY AND YIELD Gretchen F. Sassenrath, Lead Scientist J. Ray Williford, Research Leader USDA Agricultural Research Service Application and Production Technology Research Unit Stoneville, MS 38776 gsassenrath@ars.usda.gov rwilliford@ars.usda.gov ABSTRACT The introduction of accurate, reliable cotton yield monitors has increased the value of spatial information pertaining to cotton (Gossypium hirsutum, L. sps.) growth and yield potential, and contributed to the development and incorporation of site-specific methodologies in cotton production. While this knowledge is important for developing precision management strategies, cotton quality also contributes to the profitability. Cotton fiber is graded for a variety of properties based on physiological maturity, from which the price is determined. Variability in cotton yield contributes to differences in profitability of various regions within fields. Variability in fiber quality will contribute additional alterations in the profitability of field regions. Currently, the determination of spatial patterns of fiber quality is performed by hand harvesting. However, hand harvesting is tedious, time consuming, and error prone. Hand-harvested cotton displays distinct differences in fiber properties from that harvested mechanically. Moreover, the time and labor commitment to adequately sample a large production field makes hand harvesting untenable for rapid and accurate determination of spatial patterns of fiber quality. Our research examines the spatial variability of fiber quality and quantity, with an end to delineating the underlying parameters contributing to that variability. To adequately address the variability of fiber production, we developed an accurate, rapid method of spatially sampling cotton lint as the cotton is mechanically harvested. The sampling system allows rapid subsampling of the harvested cotton in a spatially registered location. The analysis of the spatially registered cotton properties will be discussed in conjunction with its use in development of profitability maps and site-specific management. INTRODUCTION Advances in engineering systems have introduced cotton producers to the value of spatial information. Particular emphasis has been focused on systems to enhance production, through a combination of increased crop value and decreased production expense. Identification of areas of superior or limited yields has been made possible with the cotton yield monitor (Wilkerson and Moody, 2000). This automated system spatially measures the volume of cotton from a given area during the harvest process, giving a measure of the variability at the end of the season. In cotton, the quality of the crop is an additional important determinant of profit margin, as the price paid to farmers is reduced by discount points. The quality, and hence the lint value, is dependent on several factors, including length, strength, maturity (color), and secondary cell wall development (micronaire). Each of these factors, as well as the ginning efficiency, contributes to the price paid for the cotton. The overall profitability, then, is a combination of the cotton yield and quality, less the input costs of production. With increased knowledge of cotton yield variability, there is greater interest in identifying within-field variability during the growing season, and delineating the underlying factors contributing to the observed variances in crop performance and yield. Identification of reduced crop performance within season could allow for amelioration of detrimental conditions, potentially improving production. Moreover, knowledge of underlying factors reducing production can allow development of management zones, with production scenarios optimized for individual zone conditions. Remote sampling methods are being explored for their utility in monitoring crops for detection of growth anomalies. Other methods, such as discrete soil and plant sampling and continuous soil sampling (such as electrical conductivity), are being explored for monitoring crop performance during the growing season.