scholarly journals Energy-Dispersive X-ray Fluorescence Spectrometry for Cost-Effective and Rapid Screening of Pearl Millet Germplasm and Breeding Lines for Grain Iron and Zinc Density

2016 ◽  
Vol 47 (18) ◽  
pp. 2126-2134 ◽  
Author(s):  
Mahalingam Govindaraj ◽  
Kedar N. Rai ◽  
Wolfgang H. Pfeiffer ◽  
Anand Kanatti ◽  
Harshad Shivade
2014 ◽  
Vol 13 (1) ◽  
pp. 75-82 ◽  
Author(s):  
K. N. Rai ◽  
G. Velu ◽  
M. Govindaraj ◽  
H. D. Upadhyaya ◽  
A. S. Rao ◽  
...  

Crop biofortification is increasingly being recognized as a cost-effective and sustainable approach to address the widespread micronutrient malnutrition arising from Fe and Zn deficiencies. Pearl millet as a cereal crop species has higher Fe density than all other major cereals. Earlier studies in pearl millet have shown that breeding lines, hybrid parents, improved populations and composites having high Fe and Zn densities were often based largely or entirely on iniadi pearl millet germplasm. In an attempt to identify additional sources of high Fe density in this group of germplasm, 297 accessions were screened using Perl's Prussian Blue staining, of which 191 accessions (118 from Togo, 62 from Ghana and 11 from Burkina Faso) were re-evaluated during the 2010 rainy and 2012 summer seasons using the inductively coupled plasma atomic emission spectroscopy method. On the basis of the mean performance over the two seasons (environments), large variability was observed for both Fe (51–121 mg/kg) and Zn (46–87 mg/kg) densities. There was a highly significant and positive correlation between the two micronutrients (r= 0.77, P< 0.01). Of these re-evaluated accessions, 49% had higher Fe density than the high-Fe control commercial cultivar ICTP 8203 (81 mg/kg), and most of these accessions also had Zn density ≥ 61 mg/kg (59 mg/kg for ICTP 8203). A total of 27 accessions (20 from Togo and seven from Ghana) having a Fe density of 95–121 mg/kg (1 standard error of difference above that for ICTP 8203) and a Zn density of 59–87 mg/kg were selected as a valuable germplasm resource for genetic improvement of these two micronutrients in pearl millet.


2014 ◽  
Vol 43 (2) ◽  
pp. 47-53 ◽  
Author(s):  
Toshio MIYAZAKI ◽  
Shin-ichi YAMASAKI ◽  
Noriyoshi TSUCHIYA ◽  
Satoshi OKUMURA ◽  
Ryoichi YAMADA ◽  
...  

2021 ◽  
Author(s):  
Maame Croffie ◽  
Paul N. Williams ◽  
Owen Fenton ◽  
Anna Fenelon ◽  
Karen Daly

&lt;p&gt;Soil texture is an essential factor for effective land management in agricultural production. Knowledge of soil texture and particle size at field scale can aid with on-going soil management decisions. Standard soil physical and gravimetric methods for particle size analysis are time-consuming and X-ray fluorescence spectrometry (XRF) provides a rapid and cost-effective alternative. The objective of this study was to explore the use of XRF as a predictor for particle size. An extensive archive of Irish soils with particle size and soil texture data was used to select samples for XRF analysis. Regression and correlation analyses on XRF determined results showed that the relationship between Rb and % clay varied with soil type and was dependent on the parent material. There was a strong relationship (R &gt; 0.62, R&lt;sup&gt;2&lt;/sup&gt;&gt;0.30, p&lt;0.05) between Rb and clay for soils originating from bedrock such as limestones and slate. Contrastingly, no significant relationship (R&lt;0.03, R&lt;sup&gt;2&lt;/sup&gt;=0.00, p&gt;0.05) exists between Rb and % clay for soils originating from granite and gneiss. Furthermore, there was a significant negative correlation (p&lt;0.05) between Rb and % sand. The XRF is a useful technique for rough screening of particle size distribution in soils originating from certain parent materials. Thus, this may contribute to the rapid prediction of soil texture based on knowledge of the particle size distribution.&lt;/p&gt;&lt;p&gt;&amp;#160;&lt;/p&gt;


2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Tong Chen ◽  
Xingpu Qi ◽  
Zaiyong Si ◽  
Qianwei Cheng ◽  
Hui Chen

Abstract In this work, a method was established for discriminating geographical origins of wheat flour based on energy dispersive X-ray fluorescence spectrometry (ED-XRF) and chemometrics. 68 wheat flour samples from three different origins were collected and analyzed using ED-XRF technology. Firstly, the principal component analysis method was applied to analyze the feasibility of discrimination and reduce data dimensionality. Then, Competitive Adaptive Reweighted Sampling (CARS) was used to further extract feature variables, and 12 energy variables (corresponding to mineral elements) were identified and selected to characterize the geographical attributes of wheat flour samples. Finally, a non-linear model was constructed using principal component analysis and quadratic discriminant analysis (QDA). The CARS-PCA-QDA model showed that the accuracy of five-fold cross-validation was 84.25%. The results showed that the established method was able to select important energy channel variables effectively and wheat flour could be classified based on geographical origins with chemometrics, which could provide a theoretical basis for unveiling the relationship between mineral element composition and wheat origin.


1977 ◽  
Vol 49 (12) ◽  
pp. 1734-1737 ◽  
Author(s):  
John A. Boslett ◽  
Robert L. R. Towns ◽  
Robert G. Megargle ◽  
Karl H. Pearson ◽  
Thomas C. Furnas

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