Affiliation:
1. Instituto Nacional de Tecnología Agropecuaria (INTA), Estación Experimental de Reconquista Santa Fe Argentina
2. Asociación para la Promoción de la Producción Algodonera (APPA) San Martin N° 774 Avellaneda Santa Fe Argentina
3. Consejo Nacional de Investigaciones Científicas y Tecnológicas (CONICET) Santa Fe Argentina
4. Universidad Católica de Santa Fe (UCSF), Facultad de Ciencias Agropecuarias Santa Fe Argentina
Abstract
AbstractCotton (Gossypium hirsutum L.) is the most widely used natural fiber worldwide in the textile industry; thus, maintaining or even improving fiber quality is essential to produce the best quality yarn and uniform fabrics. Final fiber quality properties are determined not only by genotypes or environmental conditions during crop development but can also be affected by other postmaturity factors, such as harvesting and ginning methods, and harvest time (HT). The aim of this study is to associate the different environmental factors that affect specific lint quality traits produced by a delay in HT, also assessing cultivar effect. This field study included four cotton cultivars evaluated at seven different HTs (manual harvested) for different quality parameters. Results indicate that prolonged exposure of cotton fiber to the environment affects lint percentage (LP), strength (Str), reflectance (Rd), and yellowness (+b). Str showed a decrease of 0.02 g tex−1 day−1 from defoliant application, whereas LP, Rd, and +b presented different rates according to the season. No differences were obtained neither for length nor for fineness and maturity (micronaire) traits. In addition, the analysis of the results together with the climatic data recorded during the experiments indicated a negative correlation among Str, Rd, and +b with the number of rainy days, accumulated precipitation, and frost temperatures. Overall, this study establishes specific relationships between certain fiber characteristics and environmental conditions, being an important tool for crop management with regards to climate predictions that could help to make estimates of economic losses when the harvest is delayed.
Funder
Instituto Nacional de Tecnología Agropecuaria
Subject
Agronomy and Crop Science
Cited by
1 articles.
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