Search Results (23)

Rapid and accurate detection of protein content is essential for ensuring the quality of maize. Near-infrared spectroscopy (NIR) technology faces limitations due to surface effects and sample homogeneity issues when measuring the protein content of whole maize grains. Focusing on maize grain powder can significantly improve the quality of data and the accuracy of model predictions. This study aims to explore a rapid detection method for protein content in maize grain powder based on near-infrared spectroscopy. A method for determining protein content in maize grain powder was established using near-infrared (NIR) reflectance spectra in the 940–1660 nm range. Various preprocessing techniques, including Savitzky−Golay (S−G), multiplicative scatter correction (MSC), standard normal variate (SNV), and the first derivative (1D), were employed to preprocess the raw spectral data. Near-infrared spectral data from different varieties of maize grain powder were collected, and quantitative analysis of protein content was conducted using Partial Least Squares Regression (PLSR), Support Vector Machine (SVM), and Extreme Learning Machine (ELM) models. Feature wavelengths were selected to enhance model accuracy further using the Successive Projections Algorithm (SPA) and Uninformative Variable Elimination (UVE). Experimental results indicated that the PLSR model, preprocessed with 1D + MSC, yielded the best performance, achieving a root mean square error of prediction (RMSEP) of 0.3 g/kg, a correlation coefficient (R_p) of 0.93, and a residual predictive deviation (RPD) of 3. The associated methods and theoretical foundation provide a scientific basis for the quality control and processing of maize. Full article

Grain and flour quality traits affect marketing potential and milling and baking properties. Trait means varied in fourteen wheat grain and flour quality traits for a population of 188 diverse soft winter wheat varieties harvested from 2020 to 2023 at the same location. Significant weather differences occurred yearly. This created a challenge for the detection of chromosome locations affecting these traits through genome-wide association studies (GWAS). Mean normalization using standard deviation to transform raw data to Z scores has been used successfully in other statistical analyses of biological systems with mean differences. Mean normalization was applied to a GWAS, improving detection power for thirteen grain and flour quality traits with high broad-sense heritability. It did not improve the lone trait with low heritability. Improvement was measured as the reduction in the p-value of mean normalized data compared with raw data for the same significant marker using the same GWAS model in the same trait. Improvement varied by trait and marker, but the average p-value of 135 common significant marker/GWAS model combinations was reduced 27 times with mean normalization over raw averaged data. Mean normalization reduced p-values ~1800 times when compared with a GWAS using best linear unbiased predictors. However, the best linear unbiased predictors led to only 15 common marker/GWAS model combinations with mean normalization, limiting the ability for direct marker comparison. Test weight, kernel protein, kernel weight, sodium carbonate solvent retention capacity, and sucrose solvent retention capacity showed the greatest increased detection power. Full article

Food texture is an important factor in the liking and choice of food. Food neophobia, the avoidance of unfamiliar foods, has been linked with sensitivity to textural properties of food. The objective of this study was to investigate the associations between food neophobia, pickiness to food textures and the liking of food items with diverse textural properties among Finnish consumers. Finnish adults aged 18−45 years were recruited. The level of food neophobia was assessed with Food Neophobia Scale (FNS). Participant’s agreement to a statement “I’m very picky regarding food textures” was measured by a 7-point Likert scale, and the degree of liking of various food items, including vegetables, fruits and berries (e.g., mushroom, cloudberry), grain products (e.g., rye bread, oatmeal), dairy (e.g., ‘squeaky cheese’, smoothie) and other foods (e.g., tofu, other plant-based proteins, shrimp) by using a 9-point hedonic liking scale. Participants were divided into three groups based on the mean (M) and standard deviation (SD) of the FNS scores: individuals with FNS scores < M − 0.5 × SD were considered ‘neophilic’, those with scores between M ± 0.5 × SD were ‘neutral’ and those with scores > M + 0.5 × SD were ‘neophobic’. Results: Consumers (N = 135, of which 88% were females) responded to the questionnaires. Of the respondents, 32% were neophobic, 34% neutral and 34% neophilic. Neophobia was associated with self-reported pickiness to food texture; neophobics were pickier compared to neophilics and neutrals (p < 0.001). Neophobics showed lower liking of tofu (p = 0.015), other plant-based proteins (p = 0.008), ‘squeaky cheese’ (p = 0.024) and shrimps (p = 0.004) compared to neophilics. Furthermore, the neutral group had a lower liking of smoothies (p = 0.046) and tofu (p = 0.004) compared to neophilics. No other differences in food liking were shown between the groups. Neophobics were less likely to have a university-level education than neutrals and neophilics (p = 0.003); age and sex did not differ between the groups. Adult consumers with food neophobia showed pickiness to food textures and lower liking of several food items with textural properties that are known to be challenging and can be described as spongy. The textural properties of foods should be considered more frequently when developing new foods to ensure more enjoyable food experiences for consumers. Full article

Background: In the context of global shifts in food systems, this paper explores the unique dietary practices of the Santal tribe, an indigenous group in eastern India, to understand the health, nutrition, and sustainability aspects of their traditional food systems. This study evaluates the nutritional content of the Santal diet in comparison to the EAT-Lancet Commission’s 2019 dietary guidelines for healthy and sustainable diets. Methods: The University of East Anglia, in collaboration with the NNEdPro Global Institute for Food, Nutrition and Health in Cambridge, PRADAN; colleagues in India and local Santal youth, conducted nutritional analyses of traditional Santal recipes. Two menu templates, Kanhu Thali and Jhano Thali, were selected for comparative analysis based on their representation of diverse dietary practices within the Santal community. Nutritional data, including energy as well as the distribution of macronutrients and micronutrients, were compiled and compared with the EAT-Lancet guidelines. Results: The Santal menu templates (nutritionally complete meals) demonstrated alignment with EAT-Lancet recommendations in aspects such as whole grains, starchy vegetables, vegetables, plant-based protein sources, unsaturated fats, and limited added sugars. However, notable deviations included the absence of animal-based protein sources and dairy. The Santal diet showed high protein intake, largely from plant-based sources, and emphasised the importance of whole grains. Seasonal variations in nutritional content were observed between the two templates. Conclusions: While the Santal diet aligns with some aspects of global dietary guidelines, there are notable deviations that underscore the complexity of aligning traditional diets with universal recommendations. The findings emphasise the need for culturally sensitive dietary recommendations that respect traditional diets while promoting sustainability. Research needs to support tailored global guidelines enshrining core principles of nutritional adequacy which are inter-culturally operable in order to accommodate cultural diversity, local practices, and seasonal variations, crucial for fostering sustainable and healthy eating habits in diverse sociodemographic contexts. Full article

Wheat is an important food crop in China. The quality of wheat affects the development of the agricultural economy. However, the high-quality wheat produced in China cannot meet the demand, so it would be an important direction for research to develop high-quality wheat. Grain protein content (GPC) is an important criterion for the quality of winter wheat and its content directly affects the quality of wheat. Studying the spatial heterogeneity of wheat grain proteins is beneficial to the prediction of wheat quality, and it plays a guiding role in the identification, grading, and processing of wheat quality. Due to the complexity and variability of wheat quality, conventional evaluation methods have shortcomings such as low accuracy and poor applicability. To better predict the GPC, geographically weighted regression (GWR) models, multiple linear regression, random forest (RF), BP neural networks, support vector machine, and long-and-short-term memory algorithms were used to analyze the meteorological data and soil data of Jiangsu Province from March to May in 2019–2022. It was found that the winter wheat GPC rises by 0.17% with every 0.1° increase in north latitude at the county level in Jiangsu. Comparison of the prediction accuracy of the coefficient of determination, mean deviation error, root mean square error, and mean absolute error by analyzing multiple algorithms showed that the GWR model was the most accurate, followed by the RF model. The regression coefficient of precipitation in April showed the smallest range of variation among all factors, indicating that precipitation in April had a more stable effect on GPC in the study area than the other meteorological factors. Therefore, consideration of spatial information might be beneficial in predicting county-level winter wheat GPC. GWR models based on meteorological and soil factors enrich the studies regarding the prediction of wheat GPC based on environmental data. It might be applied to predict winter wheat GPC and improve wheat quality to better guide large-scale production and processing. Full article

Near infrared (NIR) spectroscopy is widely used for evaluating quality traits of cereal grains. For evaluating protein content of intact sorghum grains, parallel NIR calibrations were developed using an established benchtop instrumentation (Perten DA-7250) as a baseline to test the efficacy of an adaptive handheld instrument (VIAVI MicroNIR OnSite-W). Spectra were collected from 59 grain samples using both instruments at the same time. Cross-validated calibration models were validated with 33 test samples. The selected calibration model for DA-7250 with a coefficient of determination (R²) = 0.98 and a root mean square error of cross validation (RMSECV) = 0.41% predicted the protein content of a test set with R² = 0.94, root mean square error of prediction (RMSEP) = 0.52% with a ratio of performance to deviation (RPD) of 4.13. The selected model for the MicroNIR with R² = 0.95 and RMSECV = 0.62% predicted the protein content of the test set with R² = 0.87, RMSEP = 0.76% with an RPD of 2.74. In comparison, the performance of the DA-7250 was better than the MicroNIR, however, the performance of the MicroNIR was also acceptable for screening intact sorghum grain protein levels. Therefore, the MicroNIR instrument may be used as a potential tool for screening sorghum samples where benchtop instruments are not appropriate such as for screening samples in the field or as a less expensive option compared with benchtop instruments. Full article

To improve the yield and quality of wheat is of great importance for food security worldwide. One of the most effective and significant approaches to achieve this goal is to enhance the nitrogen use efficiency (NUE) in wheat. In this review, a comprehensive understanding of the factors involved in the process of the wheat nitrogen uptake, assimilation and remobilization of nitrogen in wheat were introduced. An appropriate definition of NUE is vital prior to its precise evaluation for the following gene identification and breeding process. Apart from grain yield (GY) and grain protein content (GPC), the commonly recognized major indicators of NUE, grain protein deviation (GPD) could also be considered as a potential trait for NUE evaluation. As a complex quantitative trait, NUE is affected by transporter proteins, kinases, transcription factors (TFs) and micro RNAs (miRNAs), which participate in the nitrogen uptake process, as well as key enzymes, circadian regulators, cross-talks between carbon metabolism, which are associated with nitrogen assimilation and remobilization. A series of quantitative genetic loci (QTLs) and linking markers were compiled in the hope to help discover more efficient and useful genetic resources for breeding program. For future NUE improvement, an exploration for other criteria during selection process that incorporates morphological, physiological and biochemical traits is needed. Applying new technologies from phenomics will allow high-throughput NUE phenotyping and accelerate the breeding process. A combination of multi-omics techniques and the previously verified QTLs and molecular markers will facilitate the NUE QTL-mapping and novel gene identification. Full article

White lupin is a high-protein crop requiring drought tolerance improvement. This study focused on a genetically-broad population of 138 lines to investigate the phenotypic variation and genotype × environment interaction (GEI) for grain yield and other traits across drought-prone and moisture-favourable managed environments, the trait genetic architecture and relevant genomic regions by a GWAS using 9828 mapped SNP markers, and the predictive ability of genomic selection (GS) models. Water treatments across two late cropping months implied max. available soil water content of 60–80% for favourable conditions and from wilting point to 15% for severe drought. Line yield responses across environments featured a genetic correlation of 0.84. Relatively better line yield under drought was associated with an increased harvest index. Two significant QTLs emerged for yield in each condition that differed across conditions. Line yield under stress displayed an inverse linear relationship with the onset of flowering, confirmed genomically by a common major QTL. An adjusted grain yield computed as deviation from phenology-predicted yield acted as an indicator of intrinsic drought tolerance. On the whole, the yield in both conditions and the adjusted yield were polygenic, heritable, and exploitable by GS with a high predictive ability (0.62–0.78). Our results can support selection for climatically different drought-prone regions. Full article

Crop breeding must achieve higher rates of genetic gain in grain yield (GY) and yield stability to meet future food demands in a changing climate. Optimal contributions selection (OCS) based on an index of key economic traits should increase the rate of genetic gain while minimising population inbreeding. Here we apply OCS in a global spring oilseed rape (canola) breeding program during three cycles of S_0,1 family selection in 2016, 2018, and 2020, with several field trials per cycle in Australia and Canada. Economic weights in the index promoted high GY, seed oil, protein in meal, and Phoma stem canker (blackleg) disease resistance while maintaining plant height, flowering time, oleic acid, and seed size and decreasing glucosinolate content. After factor analytic modelling of the genotype-by-environment interaction for the additive effects, the linear rate of genetic gain in GY across cycles was 0.059 or 0.087 t ha⁻¹ y⁻¹ (2.9% or 4.3% y⁻¹) based on genotype scores for the first factor (f₁) expressed in trait units or average predicted breeding values across environments, respectively. Both GY and yield stability, defined as the root-mean-square deviation from the regression line associated with f₁, were predicted to improve in the next cycle with a low achieved mean parental coancestry (0.087). These methods achieved rapid genetic gain in GY and other traits and are predicted to improve yield stability across global spring canola environments. Full article

The quality of diet can be measured using diet quality indices, based on knowledge of associations between diet and health. The objective of this work was to evaluate whether the International Diet Quality Index is suitable for use as a diet quality index in populations of Mexican university girls. A cross-sectional nutritional survey was conducted at the University of Chihuahua (Mexico), collecting semi-quantitative nutritional information and socio-economic and lifestyle data from a representative sample of 400 women. Mean (Standard Deviation (SD)) age was 21.43 years (SD: 3.72); 59.1% were normal weight, 26.6% overweight, 15.3% obesity. The Diet Quality Index-International (DQI-I) was developed according to the method of Kim et al. (2003) and focused on major aspects of a high-quality diet (variety, adequacy, moderation and overall balance). The total score of Diet Quality Index-International reached 53.86% (SD: 11.43), indicating that the general diet of Mexican women a poor-quality diet. Adequacy scored highest, followed by moderation and variety. Overall balance scored the lowest. Variety: 26.3 % consumed less than 4 food groups daily, only 12.8% take more than 1 serving from each food group, and 50.6% consumed only one source of protein daily. Regarding adequacy, a large proportion of the population reported an intake of proteins, vitamin C, calcium, iron, and fruit greater than 50% of recommendation; the vegetables, fiber and grain groups were less 50%. Poor scores were obtained for total fat and SFA consumption (moderation). No statistically significant differences are observed for any of the variables under study and score of the Diet Quality Index-International: body mass index, weight, physical activity level, education level of father and mother, location of lunch, breakfast considered important, knowledge of nutrition, which allows us to consider a relatively uniform population in its eating habits. These people are close to a Westernized diet, and an intervention in nutritional education would be advisable to improve the intake of unprocessed foods, consume a greater variety of protein sources and significantly reduce consumption of sugary foods and soft drinks. Due to different methodological and cultural factors, the proposed Diet Quality Index-International dietary assessment method does not seem to be useful in the assessment of diet quality in the Mexican university population, so further research is needed to develop a diet quality index adapted to the Mexican population. Full article

The variations in temperature and rainfall patterns under climate change are threatening crop production systems, and optimizing fertilization practices is a prerequisite for sustainable cereal production. This two-year field study investigated the effects of eight treatments (T1: P₆₀K₆₀; T2: P₆₀K₆₀ + N_{min spring}; T3: P₆₀K₆₀ + N_40autumn + N_{min spring}; T4: P₆₀K₆₀ + N_60spring; T5: P₆₀K₆₀ + N_100spring; T6: P₆₀K₆₀ + N_40autumn + N_60spring + Zn; T7: P₆₀K₆₀ + _N60autumn + N_80spring + Zn; and T8: P₆₀K₆₀ + N_160spring + Zn) on the grain yield and quality of four divergent maize cultivars (NS-4023, NS-640, NS-6010 and NS-6030). The observations on climatic data showed substantial variations in monthly and cumulative rainfall only, which was 174 and 226 mm for 2011 and 2012, respectively, and much less than the historical cumulative rainfall of 339 mm. However, temperature during growth years showed little deviation from the historical data. The data showed that treatment and maize cultivar significantly influenced grain yield; however, grain yield remained lower in 2012 than in 2011 for each treatment and cultivar. Applying N as split doses in combination with Zn, resulted in higher grain yields than adding at once. However, the treatments and cultivars affected grain quality variables differently, including oil, thiol SH, phytate, inorganic P, soluble protein, starch, total phenol, protein, total sugars and tryptophan contents. Despite the pronounced difference in grain yields between 2011 and 2012 for each treatment and cultivar, grain quality did not always vary significantly between cultivars. Principal component analysis (PCA) revealed that the relationships between grain yield and grain quality varied significantly during 2011 and 2012. The changes in rainfall patterns at critical growth maize stages seemed to be a more important factor than temperature in regulating the response of maize cultivars in terms of grain yield and quality to various fertilization regimes in this study. Full article

Improving milling and baking properties is important during wheat breeding. To determine changes in milling and baking quality of hard winter wheat, 23 adapted cultivars released in the Great Plains between 1870 and 2013 were grown in triplicate in a single location (Mead, NE, USA) over two crop years (2018 and 2019). Grain yield and kernel hardness index increased by release year (p < 0.05). The observed increase in hardness index was accompanied by a decrease in percent soft kernels (p < 0.05). Diameter and weight decreased with release year in 2019 (p < 0.05), and their standard deviation increased with the release year (p < 0.05). Flour protein content decreased with release year (p < 0.05) and dough mixing quality increased (p < 0.05). No significant relationship was found for baking property variables, but bran water retention capacity (BWRC), which is correlated with whole wheat bread quality, increased with release year (p < 0.05). In conclusion, wheat kernels have become harder but more variable in shape over a century of breeding. Mixing quality showed significant improvements, and loaf volume and firmness remained constant, even in the presence of a decrease in protein concentration. Bran quality decreased across release year, which may have implications for whole grain baking quality and milling productivity. Full article

In this paper, we show, discuss, and compare the effects of symmetrization in two calculation subroutines of the Fuzzy Oil Drop model, a coarse-grained model of density of hydrophobicity in proteins. In the FOD model, an input structure is enclosed in an axis-aligned ellipsoid called a drop. Two profiles of hydrophobicity are then calculated for its residues: theoretical (based on the 3D Gauss function) and observed (based on pairwise hydrophobic interactions). Condition of the hydrophobic core is revealed by comparing those profiles through relative entropy, while analysis of their local differences allows, in particular, determination of the starting location for the search for protein–protein and protein–ligand interaction areas. Here, we improve the baseline workflow of the FOD model by introducing symmetry to the hydrophobicity profile comparison and ellipsoid bounding procedures. In the first modification (FOD–JS), Kullback–Leibler divergence is enhanced with its Jensen–Shannon variant. In the second modification (FOD-PCA), the molecule is optimally aligned with the axes of the coordinate system via principal component analysis, and the size of its drop is determined by the standard deviation of all its effective atoms, making it less susceptible to structural outliers. Tests on several molecules with various shapes and functions confirm that the proposed modifications improve the accuracy, robustness, speed, and usability of Gauss function-based modeling of the density of hydrophobicity in protein structures. Full article

The chemical composition of individual hybrid rice (F2) varieties varies owing to genetic differences between parental lines, and the effects of these differences on eating quality are unclear. In this study, based on a self-developed near-infrared spectroscopy platform, we explored these effects among a set of 143 hybrid indica rice varieties with different eating qualities. The single-grain amylose content (SGAC) and single-grain protein content (SGPC) models were established with coefficients of determination (R²) of 0.9064 and 0.8847, respectively, and the dispersion indicators (standard deviation, variance, extreme deviation, quartile deviation, and coefficient of variation) were proposed to analyze the variations in the SGAC and SGPC based on the predicted results. Our correlation analysis found that the higher the variation in the SGAC and SGPC, the lower the eating quality of the hybrid indica rice. Moreover, the addition of the dispersion indicators of the SGAC and SGPC improved the R² of the eating quality model constructed using the composition-related physicochemical indicators (amylose content, protein content, alkali-spreading value, and gel consistency) from 0.657 to 0.850. Therefore, this new method proved to be useful for identifying high-eating-quality hybrid indica rice based on single near-infrared spectroscopy prior to processing and cooking. Full article

Grain protein content (GPC) is one of the most important criteria to determine the quality of common wheat (Triticum aestivum). One of the major obstacles for bread wheat production is the negative correlation between GPC and grain yield (GY). Previous studies demonstrated that the deviation from this inverse relationship is highly heritable. However, little is known about the genetics controlling these deviations in common wheat. To fill this gap, we performed quantitative trait locus (QTL) analysis for GY, GPC, and four derived GY-GPC indices using an eight-way multiparent advanced generation intercross population comprising 394 lines. Interval mapping was conducted using phenotypic data from up to nine environments and genotypic data from a 20k single-nucleotide polymorphism array. The four indices were highly heritable (0.76–0.88) and showed distinct correlations to GY and GPC. Interval mapping revealed that GY, GPC, and GY-GPC indices were controlled by 6, 12, and 12 unique QTL, of which each explained only a small amount of phenotypic variance (R² ≤ 10%). Ten of the 12 index QTL were independent of loci affecting GY and GPC. QTL regions harboured several candidate genes, including Rht-1, WAPO-A1, TaTEF-7A, and NRT2.6-7A. The study confirmed the usefulness of indices to mitigate the inverse GY-GPC relationship in breeding, though the selection method should reflect their polygenic inheritance. Full article