Datasets on the variations of  minerals in biofortified cassava (Manihot esculenta Crantz)  as a function of storage root portion,  maturity and environment

Introduction

Biofortified cassava roots with yellow flesh colour could be a good source of essential minerals and micronutrients and potential functional food. The different values of minerals composition of cassava roots found in the literature have shown many discrepancies beyond those caused by genetic and environmental factors. However, this could be due to inaccurate laboratory measurements, especially errors due to the sample preparation method employed during the analysis. The documented data could help the analysts and processors choose the best sample preparation method to evaluate the mineral compositions of cassava roots. The accurate measurements of the mineral content of cassava roots are vital from a nutritional perspective, especially during the selection stages of the breeding program and for providing quality information on the mineral intake in sub-Saharan Africa. However, there is a shortage of data on the spatial distribution of biofortified cassava storage roots’ mineral contents. The datasets presented the spatial distribution of minerals in biofortified cassava root genotypes and established the sampling method’s effect and harvesting time on their mineral content.

The datasets provide information on the effect of clone and environment on the minerals in biofortified cassava root. Furthermore, they establish which of the two factors strongly influences the mineral contents. In addition, they provide information on the essential minerals in biofortified cassava roots and show any association between the mineral properties assessed. The information the datasets reveals is the distribution of the minerals and their concentrations within the cassava tuber (head, middle, and tail root portions) would primarily benefit cassava breeders, food scientists and nutritionists. Also, the datasets on the effect of clones and environment could help the cassava breeders and processors identify what cassava variety is suitable for growth in all the environments and contains optimum minerals.

Breeders could use the data in their biofortification cassava programs to investigate the distribution of minerals in the roots and identify the best promising pipelines. The data could also be used by food scientists, nutritionists, and processors to understand the parts of the roots with optimum minerals and understand those genotypes specific to different environments used for various nutrition intervention programs. The data could also contribute to Nigeria’s food composition databases.

Materials and methods

Preparation of cassava roots for analysis

Determination of macro- and microelement content

The samples for mineral analysis were carefully sub-sampled from the batch samples from the two described sample preparation methods. After sub-sampling, the samples were placed in an already cleaned petri dish using deionized water and dried in an uncorroded conventional oven (Memmert UN 55, GmbH) at 40°C for three days. The dried samples were transferred into well-labelled mineral-free paper envelopes for analysis. The mineral contents were analyzed according to the validated method using inductively coupled optical emission spectrometry (ICP-OES).^1,2,4 Specifically, a radial view Spectro Ciros CCD ICP-OES (Spectro Analytical Instruments, Kleve, Germany) model was used. Each of the dried samples were weighed (0.03 g) into 1 mg into 50 ml screw-cap polypropylene tubes, and initiation of sample digestion was achieved using 2 ml of HNO₃ and 0.5 ml of H₂O₂. The digestion was completed at 125°C for 120 min using 72-position DigiPrep digestion blocks (SCP Scientific, Baie D’Urf e, Quebec, Canada). An 18 MΩ.cm of water was used to make the final volume of 25 ml of the sample. The digested sample was injected at the flow rate was 2.0 ml/min, and the total analysis time per sample was approximately 2.5 min. The calibration curves for all elements were constructed using the mixtures of high-purity single-element standard solutions in a 4% (v/v) HNO₃ matrix. The software algorithms were used for the background correction of all wavelengths and spectral interferences, as described by Wheal et al.⁴

Dataset description and validation

The samples from the two trials (44 + 28 biofortified clones and check varieties) were run in duplicate at the laboratory level. However, for quality data collection, there was an analysis of a mixture of all elements in 4% HNO₃ (drift correction solution) at every 25 samples. It helped to account for within-run variation in the flows. Furthermore, the blank subtraction, drift correction, and mass and volume adjustments were made offline. The study used six different reference materials (RMs) for the data quality establishment purchased from the US National Institute of Standards and Technology (NIST, Gaithersburg, MD, USA).⁴ The macro elements of focus in the data include calcium (Ca), magnesium (Mg), sodium (Na), potassium (K), phosphorus (P), and sulphur (S). At the same time, the microelements were Iron (Fe), Manganese (Mn), Boron (B), Copper (Cu), Molybdenum (Mo), Cobalt (Co), Nickel (Ni), Zinc (Zn) and Aluminium (Al), respectively. They were measured on an mg/kg dry weight basis. The storage portions included the proximal (A), middle (B), distal (C), the average ABC (AV) and longitudinal (L).

Data availability