- 标题
- 摘要
- 关键词
- 实验方案
- 产品
-
Cold plasma treatment and laser irradiation of <i>Triticum</i> spp. seeds for sterilization and germination
摘要： In this research work, plasma and laser-based treatments have been applied on wheat seeds to improve their growth and development. Plasma treatment modi?ed the surface morphology of seed which enhanced the germination rate and also exhibited great immunity against fungus; only 20% seeds are a?ected by fungus as compared to the untreated sample. In addition, an increase in protein concentration in plasma treated seeds has also been observed. In the laser treatment, laser pulses have been exercised on wheat seeds, while seeds were also exposed in argon plasma generated at di?erent applied voltages and exposure times. This laser treatment lessens germination time, increases water absorption, and abolishes disease development from seed borne fungi that are present on or within seeds. Thus, it is observed that the use of plasma and laser radiation on the seeds made productive e?ects on the growth parameters and may be the alternative source for the presowing seed treatment.
关键词： microbial inactivation,food chemistry,wheat seeds,plasma chemistry,plant biotechnology,cold plasma,germination
更新于2025-09-19 17:13:59
-
Determination of the superficial citral content on microparticles: An application of NIR spectroscopy coupled with chemometric tools
摘要： This work evaluates near-infrared (NIR) spectroscopy coupled with chemometric tools for determining the superficial content of citral (????????) on microparticles. To perform this evaluation, using spray drying, citral was encapsulated in a matrix of dextrin using twelve combinations of citral:dextrin ratios (CDR) and inlet air temperatures (IAT). From each treatment, six samples were extracted, and their ???????? and NIR absorption spectral profiles were measured. Then, the spectral profiles, pretreated and randomly divided into modeling and validation datasets, were used to build the following prediction models: principal component analysis-multilinear regression (PCA-MLR), principal component analysis-artificial neural network (PCA-ANN), partial least squares regression (PLSR) and an artificial neural network (ANN). During the validation stage, the models showed ??2 values from 0.73 to 0.96 and a root mean squared error (RMSE) range of [0.061–0.140]. Moreover, when the models were compared, the full and optimized ANN models showed the best fits. According to this study, NIR coupled with chemometric tools has the potential for application in determining ???????? on microparticles, particularly when using ANN models.
关键词： Food composition,Food science,Spectroscopy,Food chemistry,MLR,PCA,PLSR,Prediction,Chemometrics,Food analysis,ANN
更新于2025-09-12 10:27:22