Table_1_Biophysical and textural attributes as selection indices for replacing the adopted cassava variety with the improved genotype to produce fufu.DOCX

The use of the biophysical and textural qualities of fufu to choose the possible substitution of an adopted cassava variety (TMEB419-V1) with improved genotypes from the breeding program was assessed in this study. Standard methods were used for the biophysical and textural attributes of the fufu produced from different cassava roots. The outcomes portray that the means of the biophysical attributes of the fufu flour from different cassava genotypes are swelling power (SWP) of 13.59%, solubility index (SI) of 3.41%, dispersibility of 26.77%, bulk density (BD) of 54.46%, water absorption capacity (WAC) of 149.44%, peak viscosity of 693.97 RVU, trough viscosity of 319.76 RVU, breakdown viscosity of 374.21 RVU, final viscosity of 433.84 RVU, setback viscosity of 114.08 RVU, peak time of 4.49 min, and pasting temperature of 78.52°C, as well as moisture content of 4.92%, ash content of 0.52%, sugar content of 2.85%, starch content of 76.24%, amylose content of 31.68%, and cyanogenic potential content (CNP) of 3.03 mg HCN/kg. The sensory texture attributes depict that the cooked fufu dough was stretchable, slightly hard, sticky, and mouldable. The instrumental texture attribute of the cooked fufu dough is hardness 27.18 N/m2, adhesiveness −62.04 N/m2, moldability 0.93, stretchability 0.89, and gumminess 25.26 N/m2. Similar functional (BD) and pasting (peak and breakdown viscosities) properties and chemical composition (amylose content) to that of the control sample (V1 variety) were produced from the V6 genotype. However, the cooked fufu dough prepared from the V7 and V8 genotypes was comparable to that of the V1 variety in terms of the sensory (stretchability) and instrumental (moldability) texture attributes; therefore, most of the genotypes may be suitable for producing fufu flour like the control sample (V1 variety) based on attributes preferred by the consumers.</p

Total usual mean intake of cassava and red palm oil expressed in grams per day among pre-school aged children 6–59 months and women of childbearing age in Akwa Ibom State, Nigeria, 2011.

<p>Total usual mean intake of cassava and red palm oil expressed in grams per day among pre-school aged children 6–59 months and women of childbearing age in Akwa Ibom State, Nigeria, 2011.</p

Vitamin A, iron and infection status among pre-school aged children aged 6–59 months and women of childbearing age in Akwa Ibom State, Nigeria, 2011.

<p>¹CRP, C-reactive protein; AGP, α-1-acid glycoprotein; Infection status at the individual level was defined as 1) no infection: CRP < 10 and AGP < 1; 2) incubation: CRP ≥ 10 and AGP < 1; 3) early convalescence: CRP ≥ 10 and AGP ≥ 1; and 4) late convalescence: CRP < 10 and AGP ≥ 1.</p><p>² < 12 μg/L indicates depleted iron stores in children less than 5 years of age, < 15 μg/L indicates depleted iron stores in individuals 5 years of age or older.</p><p>³ < 30 μg/L indicates depleted iron stores in the presence of infection for children less than 5 years of age.</p><p>Vitamin A, iron and infection status among pre-school aged children aged 6–59 months and women of childbearing age in Akwa Ibom State, Nigeria, 2011.</p

Frequency of consumption of cassava dishes (A) and frequency of consumption of dishes containing red palm oil—conditioned to red palm oil consumption (B) among pre-school children aged 6–59 months and women of childbearing age, Akwa Ibom State, Nigeria 2011.

<p>Frequency of consumption of cassava dishes (A) and frequency of consumption of dishes containing red palm oil—conditioned to red palm oil consumption (B) among pre-school children aged 6–59 months and women of childbearing age, Akwa Ibom State, Nigeria 2011.</p

Characteristics of selected households and nutritional status of pre-school children 6–59 months and women of childbearing age from rural areas in Akwa Ibom State, Nigeria, 2011.

<p>Characteristics of selected households and nutritional status of pre-school children 6–59 months and women of childbearing age from rural areas in Akwa Ibom State, Nigeria, 2011.</p

Usual daily intakes of selected macro and micronutrients by age group.

<p>¹EAR—the estimated average requirements are for children 1–3 and 4–8 years old. Estimates were calculated for each age group and an average value for all children weighted by age group, n = 506, 0.5–3 years old; and n = 78, 4–5 years old. The EAR are from IOM (2006) [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0129436#pone.0129436.ref025" target="_blank">25</a>] except zinc is from IZiNCG (2004) [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0129436#pone.0129436.ref026" target="_blank">26</a>] based on unrefined cereal based diet.</p><p>²EAR—the estimated average requirements are based on recommendations for women 19–30 years old (n = 579).</p><p>³ Vitamin A RAE, Retinol Activity Equivalents</p><p>⁴ Folate DFE, Dietary Folate Equivalents</p><p>^aBased on mean weight of 27.8 kg for children (data not shown).</p><p>^bBased on mean weight of 67.5 kg for women (data not shown).</p><p>Usual daily intakes of selected macro and micronutrients by age group.</p

Contribution of food groups to total vitamin A intake as expressed in retinol activity equivalent among (A) women of childbearing age and (B) pre-school children aged 6–59 months, Akwa Ibom State, Nigeria 2011.

<p>Contribution of food groups to total vitamin A intake as expressed in retinol activity equivalent among (A) women of childbearing age and (B) pre-school children aged 6–59 months, Akwa Ibom State, Nigeria 2011.</p

Image_10_Predicting starch content in cassava fresh roots using near-infrared spectroscopy.jpeg

The cassava starch market is promising in sub-Saharan Africa and increasing rapidly due to the numerous uses of starch in food industries. More accurate, high-throughput, and cost-effective phenotyping approaches could hasten the development of cassava varieties with high starch content to meet the growing market demand. This study investigated the effectiveness of a pocket-sized SCiO™ molecular sensor (SCiO) (740−1070 nm) to predict starch content in freshly ground cassava roots. A set of 344 unique genotypes from 11 field trials were evaluated. The predictive ability of individual trials was compared using partial least squares regression (PLSR). The 11 trials were aggregated to capture more variability, and the performance of the combined data was evaluated using two additional algorithms, random forest (RF) and support vector machine (SVM). The effect of pretreatment on model performance was examined. The predictive ability of SCiO was compared to that of two commercially available near-infrared (NIR) spectrometers, the portable ASD QualitySpec® Trek (QST) (350−2500 nm) and the benchtop FOSS XDS Rapid Content™ Analyzer (BT) (400−2490 nm). The heritability of NIR spectra was investigated, and important spectral wavelengths were identified. Model performance varied across trials and was related to the amount of genetic diversity captured in the trial. Regardless of the chemometric approach, a satisfactory and consistent estimate of starch content was obtained across pretreatments with the SCiO (correlation between the predicted and the observed test set, (R2P): 0.84−0.90; ratio of performance deviation (RPD): 2.49−3.11, ratio of performance to interquartile distance (RPIQ): 3.24−4.08, concordance correlation coefficient (CCC): 0.91−0.94). While PLSR and SVM showed comparable prediction abilities, the RF model yielded the lowest performance. The heritability of the 331 NIRS spectra varied across trials and spectral regions but was highest (H2 > 0.5) between 871−1070 nm in most trials. Important wavelengths corresponding to absorption bands associated with starch and water were identified from 815 to 980 nm. Despite its limited spectral range, SCiO provided satisfactory prediction, as did BT, whereas QST showed less optimal calibration models. The SCiO spectrometer may be a cost-effective solution for phenotyping the starch content of fresh roots in resource-limited cassava breeding programs.</p

Image_7_Predicting starch content in cassava fresh roots using near-infrared spectroscopy.jpeg

The cassava starch market is promising in sub-Saharan Africa and increasing rapidly due to the numerous uses of starch in food industries. More accurate, high-throughput, and cost-effective phenotyping approaches could hasten the development of cassava varieties with high starch content to meet the growing market demand. This study investigated the effectiveness of a pocket-sized SCiO™ molecular sensor (SCiO) (740−1070 nm) to predict starch content in freshly ground cassava roots. A set of 344 unique genotypes from 11 field trials were evaluated. The predictive ability of individual trials was compared using partial least squares regression (PLSR). The 11 trials were aggregated to capture more variability, and the performance of the combined data was evaluated using two additional algorithms, random forest (RF) and support vector machine (SVM). The effect of pretreatment on model performance was examined. The predictive ability of SCiO was compared to that of two commercially available near-infrared (NIR) spectrometers, the portable ASD QualitySpec® Trek (QST) (350−2500 nm) and the benchtop FOSS XDS Rapid Content™ Analyzer (BT) (400−2490 nm). The heritability of NIR spectra was investigated, and important spectral wavelengths were identified. Model performance varied across trials and was related to the amount of genetic diversity captured in the trial. Regardless of the chemometric approach, a satisfactory and consistent estimate of starch content was obtained across pretreatments with the SCiO (correlation between the predicted and the observed test set, (R2P): 0.84−0.90; ratio of performance deviation (RPD): 2.49−3.11, ratio of performance to interquartile distance (RPIQ): 3.24−4.08, concordance correlation coefficient (CCC): 0.91−0.94). While PLSR and SVM showed comparable prediction abilities, the RF model yielded the lowest performance. The heritability of the 331 NIRS spectra varied across trials and spectral regions but was highest (H2 > 0.5) between 871−1070 nm in most trials. Important wavelengths corresponding to absorption bands associated with starch and water were identified from 815 to 980 nm. Despite its limited spectral range, SCiO provided satisfactory prediction, as did BT, whereas QST showed less optimal calibration models. The SCiO spectrometer may be a cost-effective solution for phenotyping the starch content of fresh roots in resource-limited cassava breeding programs.</p

Image_8_Predicting starch content in cassava fresh roots using near-infrared spectroscopy.jpeg

The cassava starch market is promising in sub-Saharan Africa and increasing rapidly due to the numerous uses of starch in food industries. More accurate, high-throughput, and cost-effective phenotyping approaches could hasten the development of cassava varieties with high starch content to meet the growing market demand. This study investigated the effectiveness of a pocket-sized SCiO™ molecular sensor (SCiO) (740−1070 nm) to predict starch content in freshly ground cassava roots. A set of 344 unique genotypes from 11 field trials were evaluated. The predictive ability of individual trials was compared using partial least squares regression (PLSR). The 11 trials were aggregated to capture more variability, and the performance of the combined data was evaluated using two additional algorithms, random forest (RF) and support vector machine (SVM). The effect of pretreatment on model performance was examined. The predictive ability of SCiO was compared to that of two commercially available near-infrared (NIR) spectrometers, the portable ASD QualitySpec® Trek (QST) (350−2500 nm) and the benchtop FOSS XDS Rapid Content™ Analyzer (BT) (400−2490 nm). The heritability of NIR spectra was investigated, and important spectral wavelengths were identified. Model performance varied across trials and was related to the amount of genetic diversity captured in the trial. Regardless of the chemometric approach, a satisfactory and consistent estimate of starch content was obtained across pretreatments with the SCiO (correlation between the predicted and the observed test set, (R2P): 0.84−0.90; ratio of performance deviation (RPD): 2.49−3.11, ratio of performance to interquartile distance (RPIQ): 3.24−4.08, concordance correlation coefficient (CCC): 0.91−0.94). While PLSR and SVM showed comparable prediction abilities, the RF model yielded the lowest performance. The heritability of the 331 NIRS spectra varied across trials and spectral regions but was highest (H2 > 0.5) between 871−1070 nm in most trials. Important wavelengths corresponding to absorption bands associated with starch and water were identified from 815 to 980 nm. Despite its limited spectral range, SCiO provided satisfactory prediction, as did BT, whereas QST showed less optimal calibration models. The SCiO spectrometer may be a cost-effective solution for phenotyping the starch content of fresh roots in resource-limited cassava breeding programs.</p