Genetic Diversity Analysis of Indonesian Aromatic Rice Varieties (Oryza sativa L.) Using RAPD

Journal of Crop Science and Biotechnology - In this research, we investigated genetic diversity of 21 rice genotypes (Oryza sativa L.) assessed using 38 decamer RAPD primers. A total of 405 bands...     

Classification of Dry-Milled Maize Grit Yield Groups Using Quadratic Discriminant Analysis and Decision Tree Algorithm

A genetically and environmentally diverse collection of maize (Zea maize L.) samples was evaluated for physical properties and grit yield to help develop a standard set of criteria to identify grain best suited for dry-milling. Application of principal component analysis (PCA) reduced a set of approximately 500 samples collected from six states to 154 maize hybrids. Selected maize hybrids were placed into seven groups according to their dry-milled grit yields. Regression analysis explained only 50% of the variability in dry-milling grit yield. Patterns of differences in the physical properties for the seven grit yield groups implied that the seven yield groups could be placed into two or three groups. Using two pattern recognition techniques for improving classification accuracy, quadratic discriminant analysis and the classification and regression tree (CART) model, dry-milled grit yield groups were predicted. The estimated correct classification rates were 69–80% when the samples were divided into three yield groups and 81–90% when samples were divided into two yield groups. The results indicated the comparable success of both techniques and the superiority of the decision tree algorithm to quadratic discriminant analysis by offering higher accuracy and clearer classification rules in differentiating among dry-milled grit yield groups.     

Corroborative study on maize quality, dry-milling and wet-milling properties of selected maize hybrids

A corroborative study was conducted on the maize quality properties of test weight, pycnometer density, tangential abrasive dehulling device (TADD), time-to-grind on the Stenvert hardness tester (SHT), 100-kernel weight, kernel size distribution, and proximate composition as well as maize dry- and wet-millability by six participating laboratories. Suggested operating procedures were given to compare their measurements and provide the variance structure within and between laboratories and hybrids. Partial correlation coefficient among maize quality properties varied among laboratories. The repeatability and reproducibility precision values were acceptably low for the physical quality tests, except for TADD and SHT time-to-grind measurements. The yields of dry- and wet-milled products and their correlation with maize quality properties were dependent on the collaborating laboratory. This paper highlights the importance of laboratory variation when considering which maize hybrids are best suited for dry-milling and wet-milling.     

Comparison and Analysis of QTLs,Epistatic Effects and QTL×Environment Interactions for Yield Traits Using DH and RILs Populations in Rice

Two genetic linkage maps, constructed by DH and RILs populations derived from the same parents, were carried out for the identification and comparison of QTLs controlling yield traits across different years in rice (Oryza sativa L.). A total of 194 SSR and STS markers were used in two maps, of which 114 markers were same. The distribution of Samgang allele was higher in RILs population than it in DH population. Comparing with DH population, RILs population has more lines with higher yield and wider phenotypic transgressive segression for yield traits. Although most of QTLs for the same trait were different in two populations across different years, 8 QTLs (including gwp11.1, spp5.1, spp10.1, spp11.2, ssr1.1, ssr11.1, tgw9.1 and tgw11.1) were detected over 2 yr. It is important to note that ppp10.1, spp10.1 and tgw9.1 were identified in two populations, while spp10.1 and tgw9.1 were simultaneity observed across different years. Epistatic effects were more important than additive effects for PPP, SPP, yield in DH population and TGW, yield in RILs population. Epistatic effects of DH and RILs populations were different on the same genetic background in the present study, which illuminated the QE interaction played an important role on epistatic effect. Identification and comparison of QTLs for yield traits in DH and RILs populations should provide various and more precise information. The QTLs identified in present study would be valuable in marker-assisted selection program for improving rice yield.     

Comparison and Analysis of QTLs,Epistatic Effects and QTLx Environment Interactions for Yield Traits Using DH and RILs Populations in Rice

Two genetic linkage maps, constructed by DH and RILs populations derived from the same parents, were carried out for the identification and comparison of QTLs controlling yield traits across different years in rice (Oryza sativa L.). A total of 194 SSR and STS markers were used in two maps, of which 114 markers were same. The distribution of Samgang allele was higher in RILs population than it in DH population. Comparing with DH population, RILs population has more lines with higher yield and wider phenotypic transgressive segression for yield traits. Although most of QTLs for the same trait were different in two populations across different years, 8 QTLs (including gwp11.1, spp5.1, spp10.1, spp11.2, ssr1.1, ssr11.1, tgw9.1 and tgw11.1) were detected over 2 yr. It is important to note that ppp10.1, spp10.1 and tgw9.1 were identified in two populations, while spp10.1 and tgw9.1 were simultaneity observed across different years. Epistatic effects were more important than additive effects for PPP, SPP, yield in DH population and TGW, yield in RILs population. Epistatic effects of DH and RILs populations were different on the same genetic background in the present study, which illuminated the QE interaction played an important role on epistatic effect. Identification and comparison of QTLs for yield traits in DH and RILs populations should provide various and more precise information. The QTLs identified in present study would be valuable in marker-assisted selection program for improving rice yield.     

Construction of risk assessment manual for genetically modified rice (Oryza sativa L.)

Journal of Crop Science and Biotechnology - Worldwide, grain consumption is increased and grain prices are rising. This has led to a steady increase in the production of highly productive and more...     

Relationship between chicken cellular immunity and endotoxin levels in dust from chicken housing environments

Hazardous biochemical agents in animal husbandry indoor environments are known to promote the occurrence of various illnesses among workers and animals. The relationship between endotoxin levels in dust collected from chicken farms and various immunological markers was investigated. Peripheral blood was obtained from 20 broiler chickens and 20 laying hens from four different chicken farms in Korea. Concentrations of total or respirable dust in the inside the chicken farm buildings were measured using a polyvinyl chloride membrane filter and mini volume sampler. Endotoxin levels in the dust were determined by the Limulus Amebocyte Lysate Kinetic method. Interferon-γ production by peripheral blood mononuclear cells stimulated with concanavalin A was significantly lower in broilers or layers from the farms with higher endotoxin concentrations than the chickens from the farms with lower endotoxin levels. An opposite pattern was observed for plasma cortisol concentrations with higher cortisol levels found in chickens from the farms with higher endotoxin levels. When peripheral lymphocytes were examined, the percentage of CD3^-Ia⁺ B cells was lower in layers from farms with higher endotoxin levels than those from locations with lower endotoxin levels. Overall, these results suggest a probable negative association between dust endotoxin levels and cell-mediated immunity in chickens.     

Application of Raman spectroscopy for qualitative and quantitative analysis of aflatoxins in ground maize samples

The applicability of Raman spectroscopy combined with chemometrics using different preprocessed spectra data was examined to develop fast, low-cost, and non-destructive spectroscopic methods for classification and quantification of aflatoxin-contaminated maize samples within the aflatoxin concentration range of 0–1206 μg/kg. This technique will find useful application in evaluating large numbers (e.g. >2000) of samples from maize hybrid performance trials and breeding programs. The best discriminant models were obtained from the linear discriminant analysis (LDA). The LDA models on validation samples showed correct classification rates in the range of 94–100% and did not misclassify any aflatoxin contaminated samples as aflatoxin negative. Of the models for predicting aflatoxin concentration, the partial least squares regression (PLSR) models showed the best quality of regression (slopes of 0.939–0.990) and highest coefficient of determination (r² = 0.941–0.957). The models provide limited applicability to quantify aflatoxin concentration below 20 μg/kg. No significant difference was observed between predicted values using Raman spectroscopy and reference values using high-performance liquid chromatography (HPLC) (p > 0.05), indicating the suitability of Raman spectroscopy to rapidly screen large numbers of maize samples for aflatoxin contamination.     

Development of a Core Collection Based on EST-SSR Markers and Phenotypic Traits in Foxtail Millet [Setaria italica (L.) P. Beauv.]

Journal of Crop Science and Biotechnology - The germplasm resources of foxtail millet reserve diverse genes for crop improvement which needs to be explored. To comprehend the maximum genetic...