Combining Genetic Analysis and Multivariate Modeling to Evaluate Spectral Reflectance Indices as Indirect Selection Tools in Wheat Breeding under Water Deficit Stress Conditions
REMOTE SENSING
Authors: El-Hendawy, Salah; Al-Suhaibani, Nasser; Al-Ashkar, Ibrahim; Alotaibi, Majed; Tahir, Muhammad Usman; Solieman, Talaat; Hassan, Wael M.
Abstract
Progress in high-throughput tools has enabled plant breeders to increase the rate of genetic gain through multidimensional assessment of previously intractable traits in a fast and nondestructive manner. This study investigates the potential use of spectral reflectance indices (SRIs; 15 vegetation-SRIs; 15 water-SRIs) as alternative selection tools for destructively measured traits in wheat breeding programs. The genetic variability, heritability (h(2)), genetic gain (GG), and expected genetic advances (GA) of these indices were compared with those of destructively measured traits in 43 F7-8 recombinant inbred lines (RILs) grown under limited water conditions. The performance of SRIs to estimate the destructively measured traits directly was also evaluated using the partial least squares regression (PLSR) and stepwise multiple linear regression (SMLR) models. Most vegetation-SRIs exhibited high genotypic variation, similar to the measured traits, and phenotypic correlations with these traits, compared with the water-SRIs. Most vegetation-SRIs presented comparable values for h(2) (>60%) and GG (>20%) as intermediate traits, while about half of water-SRIs exhibited a high h(2) (>60%), but low GG (<20%). Principle component analysis revealed that most vegetation-SRIs and seven of 15 water-SRIs were grouped together in a positive direction, had a moderate to strong relationship with measured traits, and could identify the drought-tolerant parent Sakha 93 and several RILs. The PLSR model based on all SRIs as a single index showed moderate to high R-2 in calibration (0.53-0.75) and validation (0.46-0.72) datasets, with strong relationships between observed and predicted values of measured traits. The SMLR models identified four and three SRIs from vegetation-SRIs and water-SRIs, respectively, to explain 63-86% of the total variability in measured traits among genotypes. These results demonstrated that vegetation-SRIs can be used individually or combined with water-SRIs as alternative breeding tools to increase genetic gains and selection accuracy in spring wheat breeding.
The effects of chitosan- and polycaprolactone-based bilayer films incorporated with grape seed extract and nanocellulose on the quality of chicken breast fillets
LWT-FOOD SCIENCE AND TECHNOLOGY
Authors: Sogut, Ece; Seydim, Atif Can
Abstract
Chitosan (CH)- and polycaprolactone (PCL)-based films containing nanocellulose (NC) (2% w/w) and grape seed extract (GSE) (15% w/w) were prepared in monolayer form (F1, F2, F5, F6) and bilayer form (F3, F4, F7, F8). Chicken breast fillets packaged with these films were analyzed for physicochemical (change in pH, color and thiobarbituric acid reactive substances-TBARS), and microbiological characteristics (total mesophilic aerobic bacteria (TMAB) and total coliform bacteria (TCB)) during 15 days under refrigerated conditions. The bilayer films with GSE kept the pH of the chicken breast fillets stable during storage. The resulting total color change (SE) was higher for the samples packaged with bilayer films, and chicken breast fillets packaged with bilayer films including GSE showed the highest SE values (p < 0.05). Samples packaged with GSE, and active bilayer films with GSE and NC had lower TBARS values than those of the control (p < 0.05). Film samples combined with GSE and NC led to a significant reduction in TMAB and TCB in chicken breast fillets (p < 0.05) during storage when compared with the control samples. The results indicated that CH-and PCL-based bilayer films could be a promising material to transfer functional compounds as active packaging material layers in food packaging applications.