Thermosensitive textiles made from silver nanoparticle-filled brown cotton fibers.

Filling fibers with nanomaterials can create new functions or modify the existing properties. However, as nanocomposite formation for natural cellulosic fibers has been challenging, little information is available on how the embedded nanomaterials alter the properties of cellulosic fibers. Here we filled brown cotton fibers with silver nanoparticles (Ag NPs) to examine their thermosensitive properties. Using naturally present tannins in brown cotton fibers as a reducing agent, Ag NP-filled brown cotton fibers (nanoparticle diameter of about 28 nm, weight fraction of 12 500 mg kg-1) were produced through a one-step process without using any external agents. The in situ formation of Ag NPs was uniform across the nonwoven cotton fabric and was concentrated in the lumen of the fibers. The insertion of Ag NPs into the fibers shifted the thermal decomposition of cellulose to lower temperatures with increased activation energy and promoted heat release during combustion. Ag NPs lowered the thermal effusivity of the fabric, causing the fabric to feel warmer than the control brown cotton. Ag NP-filled brown cotton was more effectively heated to higher temperatures than control brown cotton under the same heating treatments.

Optimal fluorescence waveband determination for detecting defective cherry tomatoes using a fluorescence excitation-emission matrix.

A multi-spectral fluorescence imaging technique was used to detect defective cherry tomatoes. The fluorescence excitation and emission matrix was used to measure for defects, sound surface and stem areas to determine the optimal fluorescence excitation and emission wavelengths for discrimination. Two-way ANOVA revealed the optimal excitation wavelength for detecting defect areas was 410 nm. Principal component analysis (PCA) was applied to the fluorescence emission spectra of all regions at 410 nm excitation to determine the emission wavelengths for defect detection. The major emission wavelengths were 688 nm and 506 nm for the detection. Fluorescence images combined with the determined emission wavebands demonstrated the feasibility of detecting defective cherry tomatoes with >98% accuracy. Multi-spectral fluorescence imaging has potential utility in non-destructive quality sorting of cherry tomatoes.