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Distribution of Elements in Durum Wheat Seed and Milling Products, Discrimination of Cultivation Methods by Multivariate Data Treatment

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19 January 2024

Posted:

22 January 2024

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Abstract
Durum wheat is an important staple food used to obtain several products. At first the wheat is milled to obtain different products: bran, semolina and flour. These products are the base of several artifacts with varying properties both from a nutritional point of view and flavoring characteristics. It is known that most elements concentrate in the outer layers of the wheat seed (pericarp and aleurone) so that the content of the elements vary a lot in the ground products. The present study investigates the characterizing elements of the milled products and the effect of cultivation protocol applied. We measured, by ICP-OES, the concentration of 28 elements in the whole seed and in any grinding products; the results show that only few elements characterize each product. Few elements, but different for each product, permit to disclose the kind of agri-cultural method used: organic or conventional protocol. Five elements: B, Cd, Cu, K, Se, are the most important to distinguish between organic and conventional agriculture by PCA and PLS analysis; these elements also permit some differentiation of products.
Keywords: 
cereals
;  
wheat
;  
ICP-OES
;  
spectroscopy
;  
chemometry
;  
classification
Subject: 
Chemistry and Materials Science  -   Analytical Chemistry

1. Introduction

Cereals are among the most important staple food crops; they are cheap source of calories, protein and elements for the inhabitants worldwide. Among the cereals, Durum wheat (Triticum durum) is the base of many largely used foods like pasta [1]. Durum wheat production, the tenth most important crop worldwide, has important impact on the economy and the environment, it was assessed [2] that these impacts could improve by organic cultivation practice. The cultivation method affects the final products, but high quality pasta has been obtained from organic wheat, in Southern Italy, using selected varieties of wheat[3]. Foods derived from wheat contribute to the body's need for essential elements, however, when polluted [4], they can contribute significantly to overexposure to some elements. Wheat plants exploit the elements [5] present in the soil for their biological needs but the concentration of these elements and their solubility changes in the different soils making their uptake by the plants more or less favored [6]. The available content of the elements is related to the content of clay [7] as shown for Saskatchewan agricultural soils. Another important source of some elements is both atmospheric [8] and soil pollution [9], furthermore in agricultural practices there is extensive use of substances containing potentially toxic elements for humans. Wheat plants will accumulate the elements, therefore, influenced by the species and based on the different exposure to the aforementioned sources. It is important to understand, since the cereal seeds are used for food purposes, how many and which elements are accumulated in the seeds.
The elemental distribution in the kernel is important because going from the outer to the inner of the seed, during the grinding process, we can obtain bran, semolina and flour that are used for different kind of food products. The knowledge of their elemental affinity can help to produce food of special characteristic or reduce the impact of environmental pollution on the final food products.
The accumulation of the elements in the seed[1] also depends on the plant genotype, the environment, the yearly rain amount.
The correlation between the genotypes of common wheat (Triticum aestivum) cultivated in Cina and the Mineral element concentrations of grain was investigated [10] with the goal of selecting those genotypes having the higher content of Fe and Zn. Brizio et al. studied the correlation of the metals with cereals species in Italy [11] paying attention to micronutrient and toxic elements. A study on French soft-wheat showed a tie between the topsoil characteristics and the content of metals of the common wheat seeds [6]. A comparison of the elements measured in several varieties of bread and durum wheats grown in Turkey [12] showed a high variability of the concentrations.
Geographical traceability of durum wheat was studied combining the elemental analysis with the Sr isotopic ratio in an Italy versus world study [13] and to characterize the Tyrol cereals[14] by 87Sr/86Sr ratio.
Multivariate analysis applies to several food materials in order to easy their authentication and fraud prevention [15], some studies involve cereals for which infrared spectroscopy [16] coupled to calibration methods permit to measure chemical composition (e.g. protein, moisture, oil) but the same spectroscopic techniques combined with pattern recognition and/or discriminant techniques were used for the authentication and traceability of cereals. Some works consider the volatiles substances, chromatographically determined, as the base of the multivariate methods for classification on the base of wheat cultivation area and species [17] or authenticate the Italian pasta [18] or even correlate the characteristics to the cultivation altitude [19]. There are studies in which the chemometric methods are coupled to the measured elemental contents for authentication purpose [20][21].
The present work aims to broaden the knowledge about the content of the elements contained in different products obtained from the milling process of the durum wheat seed. The study includes many varieties cultivated under organic or conventional protocol so we will check if a difference exists, at grinding product level, between these two cultivation protocols. To the goal some chemometric methods will need to analyze the measurements database.

2. Materials and Methods

2.1. The samples

The seeds of different varieties of durum wheat were sampled after their harvesting in July 2022, they were stored in a refrigerator till their grinding. The wheats were cultivated in the experimental fields of the AMAP in Jesi, two fields not far each other devoted one to the organic cultures the other for conventional agricultural procedure. These are clay soils; each field is divided into parcels of 7x1.4 m in each of which a different variety of wheat is grown; every variety is triplicate on three parcels. The seed harvest is carried out by keeping the seeds of each plot divided. The seeds were milled to obtain 4 products of each variety: whole seed, bran, semolina, flour as below detailed. There are some additional samples of seed that were not milled, Table 1 details the samples.
In the following every product sample is coded with the following syntax: CC_ntt where CC is the code indicated in the second column of Table 1, n indicate the agricultural method: 1 means conventional, 2 stands for organic. The two characters tt are absent in codes of seeds while they are: Cr for bran, Se for semolina, Fa for flour.

2.2. Milling

The durum wheat seed samples were conditioned in order to reach 17% humidity by adding water in two stages 16 h and 3 h before grinding. The seeds are then milled with a CD2 Chopin Technologies mill then passed through the Chopin purifier to get three fractions:
flour: ≤ 160 microns
semolina: 160 < semolina ≤ 560 micron
bran: > 560 microns

2.3. Mineralization

The samples of whole seed, bran, semolina and flour were dried in an oven at 60 °C for 24 hours; seeds were washed with ultrapure 18.2 MΩ water from a Milli-Q (Millipore, USA) before drying. About one gram of each dry sample (whole seed, bran, semolina, flour) was added with 8 ml ultrapure HNO3 65% and 2 ml ultrapure HCl 37% then digested by a microwave assisted instrument (ultraWAVE, Milestone Srl, Sorisole (BG), Italy) for 40 minutes. The digested were recovered with ultrapure water and diluted to 50 ml. All the reagents are high purity Merck products for Inductively Coupled Plasma Spectroscopy (ICP).

2.4. ICP analysis

The mineralized solutions were analyzed by a ThermoFisher Scientific iCAP PRO X Duo ICP-OES for the elements in Table 2. Quantification occurred with the use of calibration lines from 0.001 to 10 mg/L, in decadic steps. Calibrations were obtained by means of the Multi Element Standards Ultra Scientific IQC-026 except for P (Sigma Aldrich 207357) and Sn (Merck 43922907). LOD and LOQ were automatically computed from the calibration lines by the instrumental software. Samples outside the calibration range were suitably diluted to fall within the calibration.
Complementary analysis on soil samples were executed as described in the appendix A.

3. Results

Table 2 shows the average, standard deviation and range of each element in the whole of samples (seed, bran, semolina and flour used as a unique set) both considered all together and grouped by cultivation protocol. T-tests were used to compare the mean values of each element in the organic and conventional samples. The elements that test significant are indicated, in the table, with a double asterisk. Similar analysis were performed on each product, the results are summarized in Table 3 for seeds, Table 4 for bran, Table 5 semolina and Table 6 flour.
The elements were measured on four products for each wheat: whole seed, bran, semolina and flour. The Sb has values ≤LOD in 93% of the samples, 97% of them are ≤LOQ. The Tl is not present in semolina and flour (~93% of samples <LOD). Tl has values >LOD in 50% of seed samples and 58% of the bran samples but most of the positive samples have concentration close to LOD. Co was under the detection limit (43%<LOD, 58%<LOQ) especially due to the absence in the most of semolina (96%<LOD) and flour (81%<LOD) samples; most of the organic samples contain a bit less than the conventional ones. Be was not detected on 67% of the whole seed samples but trace of it are present in bran, semolina and flour. B is not detectable in half of the organic semolina (46%<LOD) and in some of the organic flour (~8%<LOD) but it is measurable in organic seeds, bran and even in all conventional samples. Ag, when detectable, has values close to its LOQ; it is present in bran, in some samples of seeds (39% of seeds <LOQ) and in few samples of semolina (43%<LOD) and flour (46%<LOD); this element has no statistically meaningful difference between organic and conventional products. The measurement of V are <LOD in about 15% of bran and semolina samples. All other elements were determined in all the samples. Comparing by a t-test the organic products versus the conventional ones give poor information; most of the elements show no difference, some of them test positively for some product as highlighted in Table 3 to Table 6 where the main parameters are also reported. Ba, Be, Co, Cr, Mn, Ni and Zn that are significantly different in soils (Table A1 in Appendix A) have no difference in the products while V that has significant test in soil has significant difference only in Semolina. The other elements: Al, Cd, Cu, Fe that give significant test for soil have significant difference also in most of the products.
As shown in Table 2 there are low difference between values obtained from organic samples and those from the conventional cultivation. As, in our samples, is a little bit higher than the values reported by Cubadda et other [22]. B content is similar to what measured on Austrian wheats [23] but lower than the measured values on wheat grown in Saskatchewan [7]. The range of values we obtained for Cd, Cu and Zn are similar to those reported for wheats grown in Marche [24].
Table 7, shows the correlation existing between elements within the products. Strong correlations are evaluated for Zn, Mg, Mn, P, K and other elements some of which connected to one or more products.
The comparisons of the content of the various elements reported in Table 2 to Table 6 show that some difference exists between grains grown with conventional or organic cultivation methods. However, the difference of the amount of the elements, also if present, confound with the high variability of the values so that univariate analysis of the data does not permit a clear differentiation both of the materials: seed, bran, semolina and flour neither of the cultivation method: organic and conventional. A multivariate approach, therefore, could simplify the interpretation of the results.
To this goal the measured values were log10 transformed because of the high concentration difference among the elements, then autoscaled before applying PCA, some comparison of data treatment without the logarithmic transform was performed that had similar or worst results. Since Sb and Tl are not present in most of the samples, they were not included in the data treatment.
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Figure 1. Scores projection of the first two components computed on log10 transformed and autoscaled data.
Figure 1. Scores projection of the first two components computed on log10 transformed and autoscaled data.
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The PCA analysis on the obtained values, even if these are very similar, highlight on the first component the partitioning of two groups due to seed and bran at high values of PC1 and another one for semolina and flour with low values in PC1. With the help of the second PC seed and bran are separated while the distance between semolina and flour is low. We can expect these results because semolina and flour both come from the kernel of the seed and are mainly starch. Bran is the outer layer of the seed where we expect a different elemental content because of the differences in composition with the seed kernel [1]. The PCA evidence that most of the elemental content in bran is very similar to that of the whole seeds, the accumulation of most elements in the bran is widely documented [1].
Figure 2 highlights the cultivation protocol on the same PCA projection of Figure 1. The figure shows that it exists a difference between samples from organic agricultural protocol and those from the conventional method of cultivation. It seems that the difference is more evident in the milled portions: bran, semolina, flour and less evident in the whole seed.
The Unscrambler® X software (version 10.2, CAMO Software, Oslo, Norway), Matlab® (version R2023a, The MathWorks inc.) and Microsoft Office® Excel softwares were used for data treatment.
Classification methods were used to verify the possibility of discriminating between products from conventional and organic cultivations. The trials consider all the product samples as a whole at the beginning and then we analyzed every single product. For each analysis we optimized the variable selection, Table 8 shows the percentage of variance explained (R2) by the PLS model and the analogous value predicted (Q2) with 5 groups cross-validation moreover an X, in the corresponding row of Table 3, marks the selected elements in each dataset necessary to obtain the optimized classification. The accuracy and precision values are evaluated with the classification toolbox for Matlab [25]. The dependent variables, for PLS-DA, are two dummy variables coded, 0 and 1 as usual, to indicate the belonging or not of the samples to the class associated to the focused dummy variable [26]. The analyses used the data matrix where every column contains the concentration values of a different element, every row the concentrations of the elements in a sample. The PLS-DA analysis uses the log transformed and autoscaled values of the element as predictors, but very good results are obtained also with the measured values simply autoscaled.
Analysing the data by PLS-DA we were able to classify well enough the products with respect to the cultivation methods as shown in Table 8.
We performed the selection of the variables with The Unscrambler [27], that apply the Martens’s uncertainty test [28]. Table 8 shows the results of the analysis with the optimized number of variables.
Table 8 highlights that the worst dataset for the classification is that of seeds, especially because it seems to give a less stable model, on the contrary Bran, Semolina and Flour show good differentiation between organic and non; semolina is excellent with its R2 0.91 and Q2 0.89. Both bran and semolina have 100% accuracy and precision while in flour the accuracy in prediction in 96%; in this last case the use of the data without log transform has a worst classification ability. Considering all the samples together an average result is obtained anyway good. Most data treatments need one latent variable for the classification model; only some needs two or more. Comparable discrimination results take place using other discriminant methods. Few elements contribute to the discrimination, but they vary on the base of the product, only B, Cd and Se were always retained, they are enough to differentiate flour with good accuracy and precision and similarly when all the samples are treated together. Cu is always selected except in flour with log transformation.
Table 8. Comparison of PLS-DA applied on different sets. Precision and accuracy[29] were evaluated by classification toolbox class_gui. The model Row details the pretreatment applied and the elements used in the model. Precision and accuracy were always reported for the two groups, that of conventional samples and that of organic samples. Prediction parameters were estimated by cross-validation.
Table 8. Comparison of PLS-DA applied on different sets. Precision and accuracy[29] were evaluated by classification toolbox class_gui. The model Row details the pretreatment applied and the elements used in the model. Precision and accuracy were always reported for the two groups, that of conventional samples and that of organic samples. Prediction parameters were estimated by cross-validation.
All samples together All samples together Seed Seed Bran Bran Semolina Semolina Flour Flour Flour Flour
model Log10 transform, autoscaled
Elements: B, Cd, Cu, Fe, Se 		autoscaled
Elements: B, Cd, Cu, Se, Si 		Log10 transform, autoscaled
Elements: B, Cd, Cu, Fe, Mg, Se 		autoscaled
Elements: B, Cd, Cu, Fe, Mg, Se 		Log10 transform, autoscaled
Elements: B, Cd, Co, Cu, Fe, K, Na, Pb, Se, Sn 		autoscaled
Elements: B, Cd, Co, Cu, Fe, K, Mo, Na, P, Pb, Se, Si, Sn 		Log10 transform, autoscaled
Elements: Ag, B, Cd, Cu, K, Se, Si 		autoscaled
Elements: Ag, B, Cd, Cu, K, Se 		Log10 transform, autoscaled
Elements: B, K, Se 		Log10 transform, autoscaled
Elements: Al, B, Cd, Cr, Fe, K, Se, Si, V 		autoscaled
Elements: B, K, Se 		autoscaled
Elements: Al, B, Cd, Co, Cr, Cu, Fe, K, Na, Se, Si, V
Number of elements 5 5 6 6 10 13 7 6 3 9 3 12
Number of LV (computed; optimal) 4; 4 3; 2 2; 1 6; 1 3; 2 2; 2 2; 1 2; 1 3; 1 3; 2 3; 1 12; 1
R2 0.78 0.74 0.62 0.63 0.89 0.91 0.91 0.89 0.80 0.84 0.81 0.79
Q2 0.76 0.72 0.59 0.59 0.83 0.86 0.89 0.87 0.73 0.71 0.75 0.75
Precision (conve; org) 0.98; 0.97 0.93; 0.93 1;0.95 1; 0.95 1; 1 1; 1 1; 1 1; 1 0.92; 0.92 1; 1 0.92; 0.92 1; 1
Accuracy 0.97 0.93 0.97 0.97 1 1 1 1 0.92 1 0.92 1
Pred. Precision (Conv; org) 0.96; 0.95 0.93; 0.92 0.88; 0.89 0.88; 0.85 1; 1 1; 1 1; 1 1; 1 0.85; 0.95 1; 0.93 0.92; 0.92 0.93; 1
Pred. accuracy 096 092 0.89 0.86 1 1 1 1 0.85 0.96 0.92 0.96
Ag X X
Al X X X
B X X X X X X X X X X X X
Cd X X X X X X X X X X
Co X X X
Cr X X X
Cu X X X X X X X X X
Fe X X X X X X X X
K X X X X X X X X
Mg X X
Mo X
Na X X X
P X
Pb X X
Se X X X X X X X X X X X X
Si X X X X X
Sn X X
V X X X
Some elements: As, Ba, Be, Ca, Mn, Ni, Ti and Zn never entered the selected variables, that indicate they are unaffected by the cultivation method, moreover Sb and Tl didn’t take part of the analysis as previously written. Mg is selected only when we analyze the seeds without log transform while V and Al enter the selected variables only with flour if treated without log transform also Si enter the group in this condition, but it is selected even when all the samples untransformed are analyzed. The selection of Ag happens only treating semolina without transform. Co, Na, Pb, Sn are tied to bran with the addition of Mo and P if only autoscaling is applied. K is important in all the grinded products.
Few elements, B, Cd, Cu, K, Se are the most meaningful, permit to differentiate the products on the base of the cultivation protocol. PCA with these five elements also reveal a good grouping on the base of the products. Even if the metals are more abundant in the outer layer (pericarp and aleurone) of the seed [30] some are differently absorbed in the kernel of the seed so that it is possible to discriminate even semolina and flour for the cultivation protocol. The large difference of elemental content due to the phenotypes does not affect the discrimination ability with respect to the kind of cultivation protocol.

4. Discussion

The present study focuses on the possibility to recognize, by means of simple analysis and multivariate treatment, the cultivation protocol used for the wheats under investigation. The study used several varieties of wheats cultivated under controlled conditions in a restricted experimental area, this means that some sources of variability are not considered as the season effect, humidity, soils. The study develops a method for protecting foodstuff, but it needs further validation with wide database including the variability sources here not considered.

5. Conclusions

ICP-OES instrumentation is largely available in the analytical laboratory permitting cheap measurements that, despite the sensitivity of the technique, are useful for advanced data treatment.
This study is devoted to characterize the elemental content of milled products of durum wheats grown in Italy. The elemental measurements are also used to verify the possibility of discriminating the ground product of durum wheat versus the cultivation protocol of the cereal. This work permits to define a data treatment methodology for obtaining the discrimination; the results are very good especially for semolina and bran but even flour can be classified with optimal precision and very high accuracy.
An important result is that the discriminations are due to few elements, three at minimum but even the products that need a few more elements can be classified with a lower number of them if we accept a little bit worse classification; in this context B, Cd, Cu, K and Se are the most effective elements.

Author Contributions

Conceptualization, P. C. and M. B.; methodology, P. C., M. F.; software, P. C.; validation, R. E. R., F. L. and M. F.; formal analysis, P. C. and M. F.; investigation, S. N., C. G., R. E. R., F. L. and M. F.; resources, M. F., P. C.; F. L. and R. E. R.; data curation, P. C., F. L. and M. F.; writing—original draft preparation, P. C.; F. L. and M. F.; writing—review and editing, M. B., S. Z., P. C.,S. N., C. G., R. E. R.; visualization, F. L., P. C.; R. E. R. and M. F.; supervision, M. B.; project administration, S. Z.; funding acquisition, M. B., S. Z. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Data Availability Statement

Data is contained within the article.

Conflicts of Interest

The authors declare no conflicts of interest.

Appendix

Soils were randomly sampled during the year obtaining 40 samples of which 16 from conventional and 24 from organic cultivated parcels. Their pH is about 8.0, table a1 shows the values of the elements measured on these soil samples. The mineralization and quantification procedure adopted was the same as the one previously described.
It is remarkable the very low content, less than LOD, of Ag, Sb and Se in the soil, even Tl is minimally present. Relatively high values of Al, Cr, Fe, Cu can be due to some pollution because of the closeness of the field both to railway tracks and mechanical industrial plants. The basic pH can prevent the high amount of Al and Mn from carrying out their toxic effect on wheat plants [31][32]. Comparison, by means of monovariate t-test, of organic and conventional soils shows meaningful difference, at 0.05 significance level, for: Ba, Be, Cd, Cr, Cu, Fe, Mn, Ni, V and Zn.
Table A1. soil elemental content. (**) indicates the elements that give a significant t-test comparison (α=0.05) between the average values of soil samples for organic cultivation and those for conventional cultivation.
Table A1. soil elemental content. (**) indicates the elements that give a significant t-test comparison (α=0.05) between the average values of soil samples for organic cultivation and those for conventional cultivation.
All soil samples Soils from organic cultivation Soils from conventional cultivation
LOD mg/Kg LOQ mg/Kg min-max mg/Kg Median ± std mg/Kg min-max mg/Kg median+std mg/Kg min-max mg/Kg median+std mg/Kg
Ag 4E-4 0.001 LOQ - LOQ LOQ ± 0.000 LOQ - LOQ LOQ ± 0.000 LOQ - LOQ LOQ ± 0.000
Al (**) 0.001 0.003 1488.550 - 4140.450 1888.480 ± 670.361 1488.550 - 4140.450 1937.785 ± 778.174 0.0 - 3189.510 1841.800 ± 466.345
As 0.001 0.004 1.000 - 3.343 2.363 ± 0.612 1.366 - 3.073 2.337 ± 0.536 0.0 - 3.343 2.483 ± 0.701
B 0.830 2.767 66.027 - 144.156 88.371 ± 18.454 66.027 - 125.625 82.289 ± 17.341 0.0 - 144.156 93.565 ± 18.515
Ba (**) 8E-5 3E-4 140.287 - 233.653 190.821 ± 21.746 140.287 - 228.053 180.543 ± 22.576 0.0 - 233.653 195.709 ± 17.175
Be (**) 3E-5 1E-4 1.249 - 2.093 1.728 ± 0.236 1.249 - 2.003 1.500 ± 0.198 0.0 - 2.093 1.898 ± 0.144
Ca 0.009 0.029 2231.142 - 2993.378 2390.573 ± 176.779 2231.142 - 2993.378 2402.166 ± 185.982 0.0 - 2840.278 2375.122 ± 167.641
Cd(**) 2E-4 6E-4 0.132 - 0.304 0.224 ± 0.041 0.167 - 0.304 0.228 ± 0.033 0.0 - 0.291 0.205 ± 0.047
Cr(**) 4E-4 0.001 53.245 - 96.209 77.855 ± 11.511 53.245 - 93.176 67.709 ± 10.415 0.0 - 96.209 86.225 ± 6.785
Cu(**) 4E-4 0.001 26.933 - 48.164 35.741 ± 4.645 26.933 - 41.021 33.282 ± 3.543 0.0 - 48.164 39.052 ± 4.470
Fe(**) 2E-4 6E-4 13698.050 - 21144.190 17175.520 ± 2128.555 13698.050 - 20820.220 16656.250 ± 1924.222 0.0 - 21144.190 18653.635 ± 1596.296
K 2E-4 8E-4 755.832 - 1222.931 952.072 ± 85.755 755.832 - 1118.040 946.518 ± 67.215 0.0 - 1222.931 982.099 ± 105.488
Mg 0.001 0.005 1990.411 - 2677.165 2234.520 ± 175.033 1990.411 - 2612.228 2191.945 ± 175.439 0.0 - 2677.165 2255.959 ± 170.404
Mn (**) 5E-5 2E-4 693.361 - 1277.959 906.261 ± 147.022 693.361 - 1277.959 829.216 ± 162.902 0.0 - 1147.556 1010.177 ± 84.972
Mo 6E-4 0.002 0.660 - 5.678 0.932 ± 1.012 0.660 - 5.678 0.882 ± 1.058 0.0 - 4.693 1.036 ± 0.968
Na 0.001 0.004 334.815 - 802.104 517.985 ± 95.093 456.723 - 712.040 506.350 ± 74.249 0.0 - 802.104 538.205 ± 121.713
Ni (**) 5E-4 0.002 39.274 - 76.972 52.226 ± 10.004 39.274 - 76.972 46.123 ± 9.669 0.0 - 74.643 59.991 ± 6.668
P 0.004 0.012 98.932 - 871.575 711.963 ± 159.183 103.282 - 871.575 735.635 ± 146.974 0.0 - 786.637 664.361 ± 167.303
Pb 7E-4 0.002 13.623 - 43.143 18.716 ± 4.417 13.623 - 43.143 17.615 ± 5.504 0.0 - 23.817 19.788 ± 1.959
Sb 0.003 0.010 LOQ - LOQ LOQ ± 0.001 LOQ - LOQ LOQ ± 0.001 LOQ - LOQ LOQ ± 0.001
Se 0.003 0.010 LOQ - LOQ LOQ ± 0.001 LOQ - LOQ LOQ ± 0.001 LOQ - LOQ LOQ ± 0.001
Si 0.018 0.060 197.230 - 2826.853 606.368 ± 830.102 218.109 - 2588.145 611.525 ± 796.059 0.0 - 2826.853 606.368 ± 902.656
Sn 0.007 0.023 0.962 - 655.190 2.133 ± 136.265 1.161 - 655.190 2.133 ± 133.045 0.0 - 584.401 2.365 ± 145.189
Tl 0.001 0.003 LOQ - 1.239 0.529 ± 0.338 LOQ - 1.239 0.488 ± 0.361 LOQ - 0.890 0.600 ± 0.307
V(**) 2E-4 5E-4 42.138 - 76.322 58.994 ± 6.575 42.138 - 63.256 54.908 ± 5.130 0.0 - 76.322 62.949 ± 5.165
Zn(**) 7E-5 2E-4 64.296 - 96.585 79.922 ± 9.031 64.296 - 94.897 75.560 ± 8.185 0.0 - 96.585 86.713 ± 6.163

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Preprints 96850 g002
Figure 2. Scores projection of the first two components computed on log10 transformed and autoscaled data, colors highlight the cultivation methods.
Figure 2. Scores projection of the first two components computed on log10 transformed and autoscaled data, colors highlight the cultivation methods.
Preprints 96850 g002
Table 1. Details of the samples.
Table 1. Details of the samples.
Wheat variety Code of the variety Code of the Organic samples Code of the Conventional samples seed bran semolina Flour
Saragolla new 01 01_2 01_1 Yes NO NO NO
San Carlo 02 NO 02_1 Yes NO NO NO
Fuego grown in a large plot 03 03_2 03_1 Yes NO NO NO
EVOLDUR evolutionary population harvest 2021 04 04_2 NO Yes NO NO NO
Evoldur grown in a large plot 04 NO 04_1 Yes NO NO NO
Senatore Cappelli 05 05_2 NO Yes NO NO NO
Saragolla old 06 06_2 NO Yes NO NO NO
Fuego grown in the edge near the railway. 07 07_2 NO Yes NO NO NO
Antalis 08 08_2 08_1 Yes Yes Yes Yes
Bering 09 09_2 09_1 Yes Yes Yes Yes
Casteldoux 10 10_2 10_1 Yes Yes Yes Yes
Claudio 11 11_2 11_1 Yes Yes Yes Yes
Fuego 12 12_2 12_1 Yes Yes Yes Yes
Idefix 13 13_2 13_1 Yes Yes Yes Yes
Iride 14 14_2 14_1 Yes Yes Yes Yes
Marakas 15 15_2 15_1 Yes Yes Yes Yes
Marco Aurelio 16 16_2 16_1 Yes Yes Yes Yes
Monastir 17 17_2 17_1 Yes Yes Yes Yes
Platone 18 18_2 18_1 Yes Yes Yes Yes
RGT Natur 19 19_2 19_1 Yes Yes Yes Yes
Tito Flavio 20 20_2 20_1 Yes Yes Yes Yes
Table 2. Elements determined and wavelengths used for their quantification. The parameters are computed on all the product samples as a whole: seed, bran, semolina and flour in a unique set. (**) indicates the elements, whose means, give a significant t-test comparison (α=0.05) between organic products and the conventional ones.
Table 2. Elements determined and wavelengths used for their quantification. The parameters are computed on all the product samples as a whole: seed, bran, semolina and flour in a unique set. (**) indicates the elements, whose means, give a significant t-test comparison (α=0.05) between organic products and the conventional ones.
All together Organic Conventional
Element Wavelength (nm) LOD (mg/Kg) LOQ (mg/Kg) Mean±StdDev Median Min - Max Mean±StdDev Median Min - Max Mean±StdDev Median Min - Max
Ag (**) 328.068 7E-4 0.002 0.003 ± 0.003 0.003 LOD - 0.013 0.003 ± 0.002 LOQ LOD - 0.007 0.004 ± 0.003 0.003 LOD - 0.013
Al (**) 396.152 3E-4 0.001 5.514 ± 4.505 4.701 1.447 - 44.802 6.940 ± 5.875 5.311 1.788 - 44.802 4.089 ± 1.517 4.117 1.447 - 7.705
As 189.042 0.002 0.007 0.078 ± 0.051 0.066 0.020 - 0.363 0.069 ± 0.029 0.067 0.021 - 0.182 0.086 ± 0.066 0.065 0.020 - 0.363
B (**) 249.773 8E-4 0.003 1.538 ± 0.845 1.589 LOD - 3.185 1.182 ± 0.890 1.250 LOD - 2.502 1.894 ± 0.624 1.844 1.109 - 3.185
Ba 493.409 3E-5 1E-4 0.718 ± 0.385 0.600 0.266 - 2.057 0.748 ± 0.367 0.626 0.285 - 1.953 0.688 ± 0.403 0.584 0.266 - 2.057
Be 313.042 2E-5 6E-5 0.001 ± 0.001 0.001 LOD - 0.006 0.001 ± 0.001 0.001 LOD - 0.006 0.001 ± 0.001 0.001 LOD - 0.003
Ca 393.366 0.007 0.024 458.658 ± 34.798 459.547 372.960 - 531.502 460.897 ± 31.085 460.871 391.647 - 519.332 456.418 ± 38.296 457.874 372.960 - 531.502
Cd (**) 214.438 1E-4 4E-4 0.021 ± 0.010 0.019 0.008 - 0.053 0.024 ± 0.011 0.021 0.010 - 0.053 0.018 ± 0.008 0.017 0.008 - 0.036
Co 228.616 0.001 0.003 LOQ ± 0.003 LOQ LOD - 0.012 LOQ ± 0.003 LOQ LOD - 0.011 LOQ ± 0.003 LOQ LOD - 0.012
Cr 267.716 7E-4 0.002 0.086 ± 0.067 0.076 0.024 - 0.615 0.090 ± 0.054 0.083 0.034 - 0.382 0.081 ± 0.077 0.072 0.024 - 0.615
Cu (**) 327.396 8E-4 0.003 3.822 ± 1.335 3.604 2.000 - 7.457 3.579 ± 1.131 3.535 2.000 - 5.848 4.065 ± 1.481 3.964 2.138 - 7.457
Fe 259.940 4E-4 0.001 23.056 ± 10.306 24.206 7.844 - 48.132 24.698 ± 10.022 25.202 9.983 - 48.132 21.413 ± 10.410 22.031 7.844 - 41.784
K 769.896 0.003 0.011 2756.460 ± 926.361 3009.755 1377.052 - 4540.521 2679.148 ± 882.771 2968.295 1377.052 - 4242.568 2833.772 ± 969.482 3072.834 1623.165 - 4540.521
Mg 279.553 1E-4 4E-4 458.369 ± 93.674 494.552 300.566 - 603.480 463.610 ± 91.025 504.347 300.566 - 603.480 453.129 ± 96.758 488.754 314.100 - 603.324
Mn 259.373 1E-4 3E-4 26.592 ± 18.062 28.919 6.734 - 73.585 26.278 ± 16.906 29.341 6.734 - 61.671 26.906 ± 19.292 28.613 7.456 - 73.585
Mo 202.030 7E-4 0.002 0.974 ± 0.398 0.889 0.539 - 4.341 0.953 ± 0.502 0.852 0.539 - 4.341 0.994 ± 0.260 0.935 0.659 - 1.644
Na (**) 588.995 0.001 0.004 32.454 ± 19.676 25.360 15.214 - 141.929 28.037 ± 10.448 25.428 16.225 - 74.832 36.871 ± 25.143 25.317 15.214 - 141.929
Ni 231.604 0.001 0.004 0.161 ± 0.119 0.141 0.027 - 0.920 0.161 ± 0.138 0.139 0.027 - 0.920 0.161 ± 0.098 0.143 0.041 - 0.580
P 177.495 0.001 0.004 2764.478 ± 1136.910 3082.185 1286.050 - 4985.480 2725.118 ± 1078.984 3082.185 1286.050 - 4748.610 2803.837 ± 1200.185 3065.615 1337.920 - 4985.480
Pb 220.353 0.004 0.012 0.073 ± 0.032 0.067 0.026 - 0.263 0.076 ± 0.027 0.072 0.036 - 0.148 0.070 ± 0.036 0.066 0.026 - 0.263
Sb 217.581 0.005 0.015 LOD ± 0.003 LOD LOD - 0.020 LOD ± 0.004 LOD LOD - 0.019 LOD ± 0.003 LOD LOD - 0.020
Se (**) 196.090 0.001 0.005 0.182 ± 0.051 0.182 0.077 - 0.290 0.217 ± 0.038 0.217 0.151 - 0.290 0.148 ± 0.039 0.155 0.077 - 0.222
Si 251.611 8E-5 3E-4 21.539 ± 13.823 18.368 4.997 - 85.435 23.961 ± 14.109 21.451 6.314 - 85.435 19.116 ± 13.210 15.465 4.997 - 69.089
Sn 189.989 3E-4 9E-4 0.008 ± 0.007 0.006 0.002 - 0.059 0.007 ± 0.003 0.006 0.003 - 0.016 0.008 ± 0.010 0.005 0.002 - 0.059
Ti (**) 323.452 4E-4 0.001 0.041 ± 0.051 0.028 0.007 - 0.484 0.051 ± 0.068 0.032 0.007 - 0.484 0.031 ± 0.019 0.025 0.007 - 0.099
Tl 190.856 5E-4 0.002 0.004 ± 0.008 LOD LOD - 0.043 0.003 ± 0.007 LOD LOD - 0.033 0.004 ± 0.009 LOD LOD - 0.043
V (**) 292.402 6E-4 0.002 0.023 ± 0.058 0.010 LOQ - 0.520 0.012 ± 0.011 0.010 LOQ - 0.075 0.035 ± 0.080 0.010 LOQ - 0.520
Zn 202.548 6E-4 0.002 23.597 ± 12.000 24.810 8.952 - 47.971 23.564 ± 11.829 25.262 8.952 - 45.948 23.629 ± 12.273 24.680 9.035 - 47.971
Table 3. Comparison of seeds. (**) indicates the elements, whose means, give a significant t-test comparison (α=0.05) between the organic product and the conventional one.
Table 3. Comparison of seeds. (**) indicates the elements, whose means, give a significant t-test comparison (α=0.05) between the organic product and the conventional one.
All seeds Organic seeds Conventional seeds
Element Mean±StdDev Median Min - Max Mean±StdDev Median Min - Max Mean±StdDev Median Min - Max
Ag 0.003 ± 0.002 0.003 LOD - 0.009 0.003 ± 0.002 0.003 LOD - 0.006 0.003 ± 0.002 0.003 LOD - 0.009
Al 4.530 ± 1.711 5.164 1.533 - 6.741 4.811 ± 1.522 5.235 1.788 - 6.583 4.216 ± 1.897 4.824 1.533 - 6.741
As 0.074 ± 0.037 0.070 0.020 - 0.218 0.073 ± 0.031 0.068 0.024 - 0.156 0.075 ± 0.043 0.071 0.020 - 0.218
B (**) 2.381 ± 0.514 2.285 0.526 - 3.185 2.107 ± 0.405 2.179 0.526 - 2.502 2.686 ± 0.453 2.916 1.999 - 3.185
Ba 0.801 ± 0.322 0.714 0.358 - 1.631 0.842 ± 0.357 0.790 0.358 - 1.631 0.756 ± 0.282 0.699 0.394 - 1.359
Be 0.000 ± 0.000 LOD LOD - 0.001 0.000 ± 0.001 LOD LOD - 0.001 0.000 ± 0.000 LOD LOD - 0.001
Ca 478.232 ± 30.116 480.896 392.386 - 531.502 482.951 ± 23.743 489.331 432.194 - 519.332 472.957 ± 35.970 469.289 392.386 - 531.502
Cd (**) 0.026 ± 0.009 0.023 0.013 - 0.045 0.029 ± 0.010 0.028 0.016 - 0.045 0.022 ± 0.007 0.022 0.013 - 0.036
Co 0.005 ± 0.003 0.005 LOD - 0.011 0.005 ± 0.003 0.005 LOD - 0.011 0.005 ± 0.003 0.005 LOQ - 0.009
Cr 0.096 ± 0.090 0.081 0.064 - 0.615 0.084 ± 0.010 0.083 0.072 - 0.115 0.109 ± 0.131 0.075 0.064 - 0.615
Cu (**) 4.336 ± 0.590 4.212 3.433 - 5.814 4.091 ± 0.534 4.040 3.433 - 5.226 4.610 ± 0.537 4.462 3.851 - 5.814
Fe (**) 26.857 ± 2.758 27.006 21.324 - 34.350 28.111 ± 2.702 28.021 23.929 - 34.350 25.455 ± 2.115 25.047 21.324 - 29.221
K 3243.369 ± 170.998 3253.807 2933.319 - 3697.111 3203.997 ± 176.816 3149.462 2933.319 - 3697.111 3287.373 ± 157.776 3270.450 3046.468 - 3587.377
Mg (**) 520.287 ± 19.505 522.190 481.189 - 558.077 526.603 ± 18.206 526.692 481.189 - 558.077 513.229 ± 18.949 509.408 484.819 - 553.452
Mn 35.138 ± 4.469 35.383 28.101 - 42.808 35.561 ± 4.322 35.409 28.101 - 42.808 34.665 ± 4.715 35.357 28.301 - 41.289
Mo 0.963 ± 0.255 0.881 0.566 - 1.644 0.929 ± 0.215 0.839 0.566 - 1.327 1.001 ± 0.296 0.903 0.659 - 1.644
Na 26.690 ± 6.451 25.109 18.349 - 48.180 27.683 ± 7.748 25.300 18.349 - 48.180 25.580 ± 4.584 24.914 20.586 - 37.991
Ni 0.187 ± 0.086 0.158 0.105 - 0.580 0.177 ± 0.059 0.155 0.111 - 0.327 0.198 ± 0.110 0.174 0.105 - 0.580
P 3358.290 ± 254.652 3289.515 2984.810 - 3903.900 3373.664 ± 268.498 3301.550 2984.810 - 3903.900 3341.108 ± 245.271 3257.150 3001.920 - 3889.520
Pb 0.056 ± 0.021 0.055 0.026 - 0.128 0.057 ± 0.018 0.050 0.036 - 0.092 0.054 ± 0.025 0.055 0.026 - 0.128
Sb LOD ± 0.005 LOD LOD - 0.020 LOQ ± 0.005 LOD LOD - 0.019 LOD ± 0.005 LOD LOD - 0.020
Se (**) 0.210 ± 0.044 0.208 0.131 - 0.290 0.238 ± 0.036 0.252 0.151 - 0.290 0.178 ± 0.029 0.165 0.131 - 0.222
Si 22.371 ± 6.684 21.451 13.517 - 48.981 22.694 ± 5.045 23.307 13.869 - 32.932 22.010 ± 8.297 20.815 13.517 - 48.981
Sn 0.005 ± 0.002 0.004 0.002 - 0.011 0.005 ± 0.002 0.004 0.003 - 0.009 0.005 ± 0.003 0.005 0.002 - 0.011
Ti 0.021 ± 0.012 0.019 0.007 - 0.064 0.021 ± 0.013 0.017 0.007 - 0.064 0.020 ± 0.011 0.021 0.007 - 0.039
Tl 0.007 ± 0.010 LOQ LOD - 0.043 0.004 ± 0.007 LOD LOD - 0.022 0.010 ± 0.013 0.005 LOD - 0.043
V 0.010 ± 0.002 0.010 0.006 - 0.015 0.009 ± 0.002 0.010 0.006 - 0.011 0.010 ± 0.002 0.010 0.006 - 0.015
Zn 29.532 ± 4.976 28.053 22.541 - 45.556 30.130 ± 5.757 27.744 22.541 - 45.556 28.863 ± 3.997 28.361 24.495 - 40.231
Table 4. Comparison of brans. (**) indicates the elements, whose means, give a significant t-test comparison (α=0.05) between the organic product and the conventional one.
Table 4. Comparison of brans. (**) indicates the elements, whose means, give a significant t-test comparison (α=0.05) between the organic product and the conventional one.
All brans Organic Brans Conventional Brans
Element Mean±StdDev Median Min - Max Mean±StdDev Median Min - Max Mean±StdDev Median Min - Max
Ag 0.006 ± 0.003 0.006 LOQ - 0.013 0.005 ± 0.002 0.005 LOQ - 0.007 0.007 ± 0.003 0.007 LOQ - 0.013
Al (**) 5.093 ± 2.009 4.460 2.579 - 12.263 5.916 ± 2.512 4.884 3.784 - 12.263 4.270 ± 0.797 4.214 2.579 - 5.757
As 0.079 ± 0.041 0.073 0.021 - 0.236 0.070 ± 0.025 0.071 0.021 - 0.118 0.088 ± 0.052 0.075 0.045 - 0.236
B (**) 1.712 ± 0.331 1.806 0.578 - 2.092 1.504 ± 0.340 1.593 0.578 - 1.890 1.919 ± 0.139 1.900 1.561 - 2.092
Ba 1.137 ± 0.405 1.096 0.587 - 2.057 1.093 ± 0.379 1.029 0.603 - 1.953 1.181 ± 0.440 1.172 0.587 - 2.057
Be 0.001 ± 0.000 0.001 0.001 - 0.003 0.001 ± 0 0.001 0.001 - 0.001 0.001 ± 0.001 0.001 0.001 - 0.003
Ca (**) 476.057 ± 26.534 476.740 412.787 - 525.940 465.731 ± 23.447 466.287 412.787 - 490.929 486.383 ± 26.193 479.765 447.286 - 525.940
Cd 0.028 ± 0.010 0.026 0.017 - 0.053 0.031 ± 0.012 0.027 0.017 - 0.053 0.024 ± 0.007 0.021 0.017 - 0.035
Co 0.005 ± 0.003 0.004 LOD - 0.012 0.004 ± 0.002 0.004 LOD - 0.008 0.006 ± 0.003 0.006 LOQ - 0.012
Cr 0.108 ± 0.018 0.109 0.072 - 0.140 0.104 ± 0.020 0.099 0.072 - 0.140 0.112 ± 0.015 0.113 0.087 - 0.137
Cu (**) 5.546 ± 0.962 5.486 3.456 - 7.457 4.925 ± 0.712 4.913 3.456 - 5.848 6.168 ± 0.763 6.012 5.078 - 7.457
Fe 36.678 ± 4.824 36.994 25.335 - 48.132 36.673 ± 6.217 37.872 25.335 - 48.132 36.684 ± 3.136 36.834 30.115 - 41.784
K (**) 3954.524 ± 482.432 4082.236 2561.379 - 4540.521 3702.171 ± 516.030 3912.625 2561.379 - 4242.568 4206.877 ± 283.921 4260.125 3511.909 - 4540.521
Mg 567.520 ± 28.755 571.690 462.179 - 603.480 558.948 ± 36.235 569.114 462.179 - 603.480 576.091 ± 15.827 581.517 547.554 - 603.324
Mn 50.742 ± 10.443 50.736 24.625 - 73.585 46.950 ± 9.574 49.176 24.625 - 61.671 54.534 ± 10.216 53.746 35.295 - 73.585
Mo (**) 1.122 ± 0.236 1.100 0.733 - 1.598 0.980 ± 0.166 0.898 0.733 - 1.258 1.264 ± 0.213 1.283 0.973 - 1.598
Na (**) 42.709 ± 16.512 39.489 24.952 - 97.760 35.491 ± 9.294 32.918 24.952 - 61.069 49.927 ± 19.203 41.321 34.075 - 97.760
Ni 0.232 ± 0.076 0.232 0.086 - 0.419 0.223 ± 0.090 0.218 0.086 - 0.419 0.241 ± 0.063 0.233 0.147 - 0.343
P (**) 4247.483 ± 558.857 4335.040 2544.200 - 4985.480 3974.312 ± 596.423 4099.390 2544.200 - 4748.610 4520.654 ± 365.057 4438.640 3664.670 - 4985.480
Pb (**) 0.089 ± 0.025 0.090 0.055 - 0.135 0.100 ± 0.027 0.108 0.055 - 0.135 0.077 ± 0.016 0.072 0.055 - 0.106
Sb LOD ± 0.001 LOD LOD - LOD LOD ± 0.001 LOD LOD - LOD LOD ± 0.001 LOD LOD - LOD
Se (**) 0.204 ± 0.044 0.193 0.141 - 0.275 0.242 ± 0.024 0.247 0.188 - 0.275 0.166 ± 0.015 0.164 0.141 - 0.195
Si 34.462 ± 13.098 32.302 14.746 - 69.089 33.757 ± 12.361 33.056 14.746 - 56.431 35.167 ± 14.267 32.148 19.242 - 69.089
Sn (**) 0.006 ± 0.003 0.005 0.003 - 0.016 0.007 ± 0.003 0.006 0.004 - 0.016 0.005 ± 0.001 0.005 0.003 - 0.009
Ti 0.053 ± 0.032 0.045 0.019 - 0.153 0.061 ± 0.040 0.048 0.019 - 0.153 0.046 ± 0.021 0.042 0.023 - 0.099
Tl 0.007 ± 0.009 0.004 LOD - 0.033 0.007 ± 0.010 LOQ LOD - 0.033 0.007 ± 0.007 0.005 LOD - 0.021
V 0.008 ± 0.006 0.007 LOQ - 0.021 0.009 ± 0.006 0.008 LOQ - 0.021 0.008 ± 0.006 0.005 LOQ - 0.018
Zn 39.233 ± 5.628 40.157 22.804 - 47.971 37.297 ± 6.372 38.188 22.804 - 45.948 41.169 ± 4.154 41.491 33.005 - 47.971
Table 5. Comparison of Semolina. (**) indicates the elements, whose means, give a significant t-test comparison (α=0.05) between the organic product and the conventional one.
Table 5. Comparison of Semolina. (**) indicates the elements, whose means, give a significant t-test comparison (α=0.05) between the organic product and the conventional one.
All Semolina Organic Semolina Conventional Semolina
Element Mean±StdDev Median Min - Max Mean±StdDev Median Min - Max Mean±StdDev Median Min - Max
Ag LOQ ± 0.002 LOQ LOD - 0.007 LOQ ± 0.001 LOQ LOD - 0.005 0.003 ± 0.002 LOQ LOD - 0.007
Al (**) 4.816 ± 2.592 4.343 1.447 - 13.392 6.147 ± 2.871 4.771 3.461 - 13.392 3.662 ± 1.678 3.821 1.447 - 7.705
As 0.077 ± 0.064 0.058 0.024 - 0.363 0.070 ± 0.038 0.059 0.027 - 0.182 0.083 ± 0.081 0.056 0.024 - 0.363
B (**) 0.855 ± 0.624 1.133 LOD - 1.851 0.288 ± 0.432 0.013 LOD - 0.951 1.346 ± 0.188 1.325 1.109 - 1.851
Ba 0.435 ± 0.123 0.412 0.279 - 0.767 0.482 ± 0.125 0.479 0.321 - 0.767 0.395 ± 0.109 0.359 0.279 - 0.635
Be 0.001 ± 0.000 0.001 0.001 - 0.002 0.001 ± 0 0.001 0.001 - 0.001 0.001 ± 0.000 0.001 0.001 - 0.002
Ca 434.047 ± 29.811 429.169 390.838 - 486.215 437.659 ± 28.502 425.796 404.677 - 486.215 430.917 ± 31.543 432.541 390.838 - 479.139
Cd (**) 0.014 ± 0.005 0.013 0.008 - 0.031 0.017 ± 0.006 0.015 0.010 - 0.031 0.012 ± 0.004 0.011 0.008 - 0.018
Co LOD ± 0.002 LOD LOD - 0.009 LOD ± 0.002 LOD LOD - 0.009 LOD ± 0.000 LOD LOD - LOD
Cr 0.049 ± 0.036 0.040 0.024 - 0.226 0.057 ± 0.051 0.041 0.034 - 0.226 0.042 ± 0.009 0.039 0.024 - 0.061
Cu (**) 2.487 ± 0.288 2.466 2.034 - 3.228 2.341 ± 0.226 2.297 2.034 - 2.745 2.614 ± 0.281 2.591 2.138 - 3.228
Fe (**) 11.859 ± 2.504 10.928 7.844 - 19.124 13.298 ± 2.761 12.756 9.983 - 19.124 10.612 ± 1.404 10.546 7.844 - 13.894
K (**) 1738.047 ± 142.878 1760.645 1377.052 - 2009.210 1657.293 ± 134.168 1655.897 1377.052 - 1864.274 1808.033 ± 112.416 1801.074 1623.165 - 2009.210
Mg 345.022 ± 19.921 345.146 300.566 - 383.394 349.486 ± 24.248 348.558 300.566 - 383.394 341.154 ± 15.061 342.398 314.100 - 365.416
Mn 9.156 ± 1.174 8.988 7.173 - 11.745 8.885 ± 0.868 8.853 7.173 - 10.532 9.391 ± 1.373 9.666 7.456 - 11.745
Mo 0.834 ± 0.170 0.818 0.539 - 1.249 0.810 ± 0.210 0.813 0.539 - 1.249 0.855 ± 0.131 0.862 0.702 - 1.101
Na 26.765 ± 17.695 20.731 15.214 - 95.377 21.091 ± 4.336 20.374 16.225 - 32.199 31.682 ± 23.065 21.728 15.214 - 95.377
Ni 0.082 ± 0.085 0.056 0.027 - 0.411 0.074 ± 0.102 0.049 0.027 - 0.411 0.088 ± 0.071 0.062 0.041 - 0.330
P 1544.900 ± 131.448 1583.585 1286.050 - 1710.380 1506.895 ± 135.215 1528.190 1286.050 - 1710.380 1577.838 ± 123.078 1623.870 1337.920 - 1710.160
Pb 0.073 ± 0.040 0.062 0.038 - 0.263 0.069 ± 0.014 0.063 0.054 - 0.102 0.077 ± 0.054 0.061 0.038 - 0.263
Sb LOD ± 0.002 LOD LOD - LOQ LOD ± 0.001 LOD LOD - LOD LOD ± 0.002 LOD LOD - LOQ
Se (**) 0.152 ± 0.047 0.156 0.077 - 0.240 0.191 ± 0.025 0.188 0.155 - 0.240 0.118 ± 0.032 0.114 0.077 - 0.212
Si (**) 8.985 ± 3.597 7.457 4.997 - 19.054 11.120 ± 3.979 10.245 6.314 - 19.054 7.135 ± 1.866 6.526 4.997 - 11.171
Sn 0.008 ± 0.010 0.006 0.004 - 0.059 0.007 ± 0.002 0.006 0.005 - 0.010 0.010 ± 0.014 0.005 0.004 - 0.059
Ti 0.030 ± 0.018 0.022 0.008 - 0.077 0.033 ± 0.018 0.024 0.016 - 0.077 0.028 ± 0.018 0.021 0.008 - 0.077
Tl LOD ± 0.001 LOD LOD - 0.003 LOD ± 0.000 LOD LOD - LOD LOQ ± 0.001 LOD LOD - 0.003
V 0.028 ± 0.097 0.007 LOQ - 0.520 0.008 ± 0.006 0.006 LOQ - 0.020 0.046 ± 0.132 0.007 LOQ - 0.520
Zn 11.213 ± 1.042 11.374 8.952 - 12.972 10.907 ± 0.955 11.075 8.952 - 12.198 11.478 ± 1.072 11.556 9.035 - 12.972
Table 6. Comparison of flour. (**) indicates the elements, whose means, give a significant t-test comparison (α=0.05) between the organic product and the conventional one.
Table 6. Comparison of flour. (**) indicates the elements, whose means, give a significant t-test comparison (α=0.05) between the organic product and the conventional one.
All flour samples Organic flours Conventional flours
Element Mean±StdDev Median Min - Max Mean±StdDev Median Min - Max Mean±StdDev Median Min - Max
Ag LOQ ± 0.002 LOQ LOD - 0.007 LOQ ± 0.002 LOD LOD - 0.006 LOQ ± 0.003 LOQ LOD - 0.007
Al (**) 8.051 ± 8.316 5.605 2.295 - 44.802 11.869 ± 10.517 7.930 5.225 - 44.802 4.233 ± 1.379 4.141 2.295 - 7.391
As 0.083 ± 0.063 0.062 0.036 - 0.305 0.063 ± 0.020 0.061 0.036 - 0.095 0.103 ± 0.084 0.065 0.036 - 0.305
B (**) 0.932 ± 0.651 1.149 LOD - 2.030 0.400 ± 0.467 0.071 LOD - 1.106 1.464 ± 0.230 1.381 1.192 - 2.030
Ba 0.488 ± 0.138 0.479 0.266 - 0.784 0.530 ± 0.142 0.531 0.285 - 0.784 0.446 ± 0.126 0.461 0.266 - 0.641
Be 0.001 ± 0.001 0.001 0.001 - 0.006 0.002 ± 0.001 0.001 0.001 - 0.006 0.001 ± Non un numero reale 0.001 0.001 - 0.001
Ca 440.659 ± 27.472 443.842 372.960 - 486.933 447.069 ± 28.188 452.268 391.647 - 486.933 434.249 ± 26.244 437.667 372.960 - 480.070
Cd 0.015 ± 0.005 0.014 0.008 - 0.030 0.017 ± 0.006 0.016 0.010 - 0.030 0.013 ± 0.004 0.012 0.008 - 0.020
Co LOD ± 0.002 LOD LOD - 0.010 LOQ ± 0.003 LOD LOD - 0.010 LOD ± 0.001 LOD LOD - 0.004
Cr 0.089 ± 0.073 0.063 0.037 - 0.382 0.117 ± 0.092 0.080 0.046 - 0.382 0.061 ± 0.029 0.051 0.037 - 0.149
Cu 2.824 ± 0.431 2.778 2.000 - 3.861 2.724 ± 0.509 2.739 2.000 - 3.861 2.924 ± 0.326 2.937 2.401 - 3.426
Fe (**) 16.227 ± 6.721 14.701 10.950 - 45.423 19.134 ± 8.469 17.476 11.067 - 45.423 13.320 ± 2.018 12.975 10.950 - 17.896
K (**) 1980.966 ± 174.635 1970.042 1664.408 - 2303.912 1910.892 ± 172.820 1879.192 1664.408 - 2246.599 2051.040 ± 151.758 2020.542 1832.890 - 2303.912
Mg 385.553 ± 27.592 389.810 329.942 - 426.213 390.328 ± 30.020 395.837 329.942 - 424.400 380.778 ± 25.209 376.573 343.350 - 426.213
Mn 9.388 ± 1.475 8.989 6.734 - 12.084 9.434 ± 1.645 8.885 6.734 - 11.814 9.343 ± 1.349 9.092 7.660 - 12.084
Mo 0.990 ± 0.712 0.832 0.551 - 4.341 1.105 ± 1.003 0.816 0.551 - 4.341 0.875 ± 0.144 0.873 0.666 - 1.180
Na 36.308 ± 30.047 24.581 17.774 - 141.929 28.049 ± 14.513 24.313 17.849 - 74.832 44.567 ± 39.018 24.848 17.774 - 141.929
Ni 0.139 ± 0.167 0.098 0.039 - 0.920 0.161 ± 0.234 0.092 0.039 - 0.920 0.117 ± 0.047 0.104 0.062 - 0.229
P 1772.662 ± 200.208 1791.390 1335.880 - 2159.440 1746.273 ± 213.606 1787.770 1335.880 - 2115.440 1799.051 ± 190.710 1795.010 1517.020 - 2159.440
Pb 0.081 ± 0.032 0.074 0.036 - 0.186 0.088 ± 0.025 0.081 0.062 - 0.148 0.074 ± 0.037 0.067 0.036 - 0.186
Sb LOD ± 0.001 LOD LOD - LOD LOD ± 0.001 LOD LOD - LOD LOD ± 0.001 LOD LOD - LOD
Se (**) 0.156 ± 0.042 0.164 0.091 - 0.230 0.186 ± 0.023 0.181 0.158 - 0.230 0.127 ± 0.036 0.108 0.091 - 0.200
Si (**) 20.982 ± 16.716 15.869 10.116 - 85.435 28.860 ± 20.680 18.165 15.683 - 85.435 13.105 ± 4.473 11.285 10.116 - 27.071
Sn 0.013 ± 0.008 0.011 0.005 - 0.035 0.011 ± 0.003 0.011 0.005 - 0.016 0.015 ± 0.011 0.010 0.006 - 0.035
Ti 0.069 ± 0.093 0.044 0.018 - 0.484 0.104 ± 0.122 0.063 0.027 - 0.484 0.034 ± 0.018 0.025 0.018 - 0.080
Tl LOQ ± 0.004 LOD LOD - 0.019 0.002 ± 0.005 LOD LOD - 0.019 LOD ± 0.000 LOD LOD - LOQ
V (**) 0.051 ± 0.064 0.021 0.003 - 0.235 0.021 ± 0.018 0.018 0.003 - 0.075 0.082 ± 0.079 0.045 0.007 - 0.235
Zn 13.078 ± 1.762 12.731 9.403 - 16.102 12.892 ± 1.982 12.796 9.403 - 16.102 13.264 ± 1.569 12.666 11.396 - 15.950
Table 7. Correlation coefficient of the elements in the different products used without distinction between organic and non-organic products. Letters close to the number stand for a=all samples together, s= Seeds, b=Brans, m=Semolina, f=Flours.
Table 7. Correlation coefficient of the elements in the different products used without distinction between organic and non-organic products. Letters close to the number stand for a=all samples together, s= Seeds, b=Brans, m=Semolina, f=Flours.
Ag Al As B Ba Be Ca Cd Co Cr Cu Fe K Mg Mn Mo Na Ni P Pb Sb Se Si Sn Ti Tl V Zn
Ag 1a; 1s; 1b; 1m; 1f
Al 1a; 1s; 1b; 1m; 1f 0.74f 0.91f 0.75m 0.89a;0.78b;0.97f 0.68b
As 1a; 1s; 1b; 1m; 1f 0.88m 0.63a;0.65s;0.89m 0.87m
B 1a; 1s; 1b; 1m; 1f 0.67b 0.63a;0.71b 0.61a;0.62b 0.71b 0.64b
Ba 1a; 1s; 1b; 1m; 1f 0.64a 0.65a 0.71a 0.68a 0.68a 0.7a 0.71a
Be 0.88m 1a; 1s; 1b; 1m; 1f 0.66s 0.68b 0.9f 0.67s 0.96m 1m 0.66s
Ca 1a; 1s; 1b; 1m; 1f 0.65a;0.61s 0.6a
Cd 1a; 1s; 1b; 1m; 1f 0.64a 0.64a 0.61a 0.65a
Co 0.74f 1a; 1s; 1b; 1m; 1f 0.98m 0.67a;0.68b 0.69a;0.73f 0.67a 0.68a 0.69a;0.62b 0.8m 0.68a 0.79f 0.68a
Cr 0.98m 1a; 1s; 1b; 1m; 1f 0.61b 0.79b 0.71b 0.72b 0.7b 0.82s;0.81m 0.74b 0.7b 0.81b
Cu 0.67b 0.64a 0.67a;0.68b 0.61b 1a; 1s; 1b; 1m; 1f 0.87a 0.94a;0.8b 0.9a;0.67b;0.64f 0.93a;0.73b;0.7m;0.73f 0.94a;0.8b;0.68f 0.93a;0.79b;0.63m;0.73f
Fe 0.91f 0.65a 0.69a;0.73f 0.79b 0.87a 1a; 1s; 1b; 1m; 1f 0.9a;0.64b 0.92a;0.76b 0.91a;0.71b 0.92a;0.74b 0.63m 0.7a;0.61b 0.93f 0.91a;0.84b
K 0.63a;0.71b 0.71a 0.67a 0.71b 0.94a;0.8b 0.9a;0.64b 1a; 1s; 1b; 1m; 1f 0.96a;0.86b;0.64f 0.97a;0.8b 0.99a;0.96b;0.73f 0.6b 0.96a;0.84b
Mg 0.61a;0.62b 0.68a 0.66s 0.65a;0.61s 0.64a 0.68a 0.72b 0.9a;0.67b;0.64f 0.92a;0.76b 0.96a;0.86b;0.64f 1a; 1s; 1b; 1m; 1f 0.95a;0.64s;0.77b;0.82f 0.97a;0.86b;0.73m;0.86f 0.96a;0.64s;0.83b;0.81f
Mn 0.68a 0.64a 0.69a;0.62b 0.7b 0.93a;0.73b;0.7m;0.73f 0.91a;0.71b 0.97a;0.8b 0.95a;0.64s;0.77b;0.82f 1a; 1s; 1b; 1m; 1f 0.98a;0.73s;0.86b;0.84f 0.97a;0.66s;0.87b;0.84f
Mo 1a; 1s; 1b; 1m; 1f 0.77f
Na 0.68b 1a; 1s; 1b; 1m; 1f 0.73m
Ni 0.9f 0.8m 0.82s;0.81m 1a; 1s; 1b; 1m; 1f
P 0.71b 0.7a 0.67s 0.6a 0.61a 0.68a 0.74b 0.94a;0.8b;0.68f 0.92a;0.74b 0.99a;0.96b;0.73f 0.97a;0.86b;0.73m;0.86f 0.98a;0.73s;0.86b;0.84f 1a; 1s; 1b; 1m; 1f 0.62b 0.98a;0.87s;0.92b;0.85f
Pb 0.73m 1a; 1s; 1b; 1m; 1f
Sb 1a; 1s; 1b; 1m; 1f
Se 0.63m 1a; 1s; 1b; 1m; 1f
Si 0.75m 0.7b 0.7a;0.61b 0.6b 0.77f 0.62b 1a; 1s; 1b; 1m; 1f
Sn 0.63a;0.65s;0.89m 0.96m 1a; 1s; 1b; 1m; 1f 0.8a;0.96m
Ti 0.89a;0.78b;0.97f 0.79f 0.93f 1a; 1s; 1b; 1m; 1f
Tl 1a; 1s; 1b; 1m; 1f
V 0.68b 0.87m 1m 0.8a;0.96m 1a; 1s; 1b; 1m; 1f
Zn 0.64b 0.71a 0.66s 0.65a 0.68a 0.81b 0.93a;0.79b;0.63m;0.73f 0.91a;0.84b 0.96a;0.84b 0.96a;0.64s;0.83b;0.81f 0.97a;0.66s;0.87b;0.84f 0.98a;0.87s;0.92b;0.85f 1a; 1s; 1b; 1m; 1f
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