Search Results (47)

This study investigated the nutritional composition, antinutritional factors, oxidative stability, microbiological safety, and sensory characteristics of hempseed cake (HC) derived from Cannabis sativa L. cv. ‘Henola’. The effects of dehulling and storage (1, 3, and 6 months) on dehulled (DHC) and hulled (HHC) hemp cake were systematically assessed. DHC exhibited significantly higher crude protein (up to 42.2%) and residual oil content (up to 37.5%), while HHC was richer in dietary fiber (up to 41.3%) and total carbohydrates (up to 48.2%). Despite comparable PUFA contents (63–72%) and favorable n-6/n-3 ratios (~3.1:1), DHC showed greater energy concentration and reduced levels of indigestible carbohydrates and phytates. Oxidative stability tests revealed increased acid and peroxide values in both HHC and DHC after six months, indicating quality deterioration (Totox index > 15). Microbiological analyses confirmed hygienic safety across all samples, with slightly higher microbial counts in HHC linked to hull-associated contamination. Sensory evaluations revealed stable color, odor, and texture during storage, with DHC rated more aromatic. These findings confirm that processing conditions—particularly dehulling—strongly affect the functional and nutritional profile of hempseed by-products. DHC emerges as a promising, shelf-stable, protein-rich ingredient for functional food and feed applications. Full article

High-throughput image analysis is a key tool for the efficient assessment of quantitative plant phenotypes. A typical approach to the computation of quantitative plant traits from image data consists of two major steps including (i) image segmentation followed by (ii) calculation of quantitative traits of segmented plant structures. Despite substantial advancements in deep learning-based segmentation techniques, minor artifacts of image segmentation cannot be completely avoided. For several commonly used traits including plant width, height, convex hull, etc., even small inaccuracies in image segmentation can lead to large errors. Ad hoc approaches to cleaning ’small noisy structures’ are, in general, data-dependent and may lead to substantial loss of relevant small plant structures and, consequently, falsified phenotypic traits. Here, we present a straightforward end-to-end approach to direct computation of phenotypic traits from image data using a deep learning regression model. Our experimental results show that image-to-trait regression models outperform a conventional segmentation-based approach for a number of commonly sought plant traits of plant morphology and health including shoot area, linear dimensions and color fingerprints. Since segmentation is missing in predictions of regression models, visualization of activation layer maps can still be used as a blueprint to model explainability. Although end-to-end models have a number of limitations compared to more complex network architectures, they can still be of interest for multiple phenotyping scenarios with fixed optical setups (such as high-throughput greenhouse screenings), where the accuracy of routine trait predictions and not necessarily the generalizability is the primary goal. Full article

Intercropping is a key cultivation strategy for safeguarding national food and oil security. Accurate early-stage yield prediction of intercropped soybeans is essential for the rapid screening and breeding of high-yield soybean varieties. As a widely used technique for crop yield estimation, the accuracy of 3D reconstruction models directly affects the reliability of yield predictions. This study focuses on optimizing the 3D reconstruction process for intercropped soybeans to efficiently extract canopy structural parameters throughout the entire growth cycle, thereby enhancing the accuracy of early yield prediction. To achieve this, we optimized image acquisition protocols by testing four imaging angles (15°, 30°, 45°, and 60°), four plant rotation speeds (0.8 rpm, 1.0 rpm, 1.2 rpm, and 1.4 rpm), and four image acquisition counts (24, 36, 48, and 72 images). Point cloud preprocessing was refined through the application of secondary transformation matrices, color thresholding, statistical filtering, and scaling. Key algorithms—including the convex hull algorithm, voxel method, and 3D α-shape algorithm—were optimized using MATLAB, enabling the extraction of multi-dimensional canopy parameters. Subsequently, a stepwise regression model was developed to achieve precise early-stage yield prediction for soybeans. The study identified optimal image acquisition settings: a 30° imaging angle, a plant rotation speed of 1.2 rpm, and the collection of 36 images during the vegetative stage and 48 images during the reproductive stage. With these improvements, a high-precision 3D canopy point-cloud model of soybeans covering the entire growth period was successfully constructed. The optimized pipeline enabled batch extraction of 23 canopy structural parameters, achieving high accuracy, with linear fitting R² values of 0.990 for plant height and 0.950 for plant width. Furthermore, the voxel volume-based prediction approach yielded a maximum yield prediction accuracy of R² = 0.788. This study presents an integrated 3D reconstruction framework, spanning image acquisition, point cloud generation, and structural parameter extraction, effectively enabling early and precise yield prediction for intercropped soybeans. The proposed method offers an efficient and reliable technical reference for acquiring 3D structural information of soybeans in strip intercropping systems and contributes to the accurate identification of soybean germplasm resources, providing substantial theoretical and practical value. Full article

The foxtail millet exhibits a diverse range of hull colors, which are crucial indicators for assessing its nutritional and economic value. However, the molecular regulatory mechanisms that govern the hull color of foxtail millet are largely unknown at present. This gap in knowledge significantly impedes efforts to enhance the quality traits of foxtail millet. This study utilized a population of 250 F₆ recombinant inbred lines (RILs) generated from a cross between two foxtail millet varieties: Yugu18 (with light yellow seeds) and Hongjiugu19 (with red seeds). Four methods, the visual grouping method (I), the visual colorimetric method (II), the Lab determination method (III), and the RGB determination method (IV), were employed to determine the hull color of each line across four environments and QTL identification were conducted subsequently. It showed that there were 10, 12, 69 and 56 QTLs were detected for hull color through four methods, and these QTLs were integrated into 4, 6, 27 and 25 unique QTLs, respectively. There were three, four, four and four major QTLs. Of which, three major QTLs (qHC1.1, qHC1.2 and qHC9.3) on chromosomes 1 and 9 could be detected by all 4 methods. qHC9.1 was detected by all four methods except for method I. There were also one, one, seven and four minor identity QTLs identified across the 4 methods. Four minor QTLs (qHC3.1, qHC3.3, qHC4.1 and qHC5.1) can be stably detected only in method III, and two minor QTLs (qHC8.2 and qHC9.2) can be stably detected only in method IV. Generally, method I is fast, efficient and cost-effective, which is suitable for the rapid detection of hull color. Method II is also low-cost; however, it can detect more QTL for hull color, making it suitable for identifying major QTL loci in large populations. Methods III and IV can map more minor QTL and are more accurate in hull color characterization. This study identified four important hull color QTL for foxtail millet, which largely align with those reported in previous research. These findings establish a foundation for characterizing hull color indices and further advancing QTL mapping for grain color. Full article

The walnut (Juglans regia) is a woody oilseed crop with high economic and food value as its kernels are edible and its hulls can be widely used in oil extraction and plugging, chemical raw materials, and water purification. Currently, red walnut varieties have emerged, attracting consumer interest due to their high nutritional values as they are rich in anthocyanins. WD40 is a widespread superfamily in eukaryotes that play roles in plant color regulation and resistance to stresses. In order to screen for JrWD40 associated with walnut color, we identified 265 JrWD40s in walnuts by genome-wide identification, which were unevenly distributed on 16 chromosomes. According to the phylogenetic tree, all JrWD40s were classified into six clades. WGD (Whole genome duplication) is the main reason for the expansion of the JrWD40 gene family. JrWD40s were relatively conserved during evolution, but their gene structures were highly varied; lower sequence similarity may be the main reason for the functional diversity of JrWD40s. Some JrWD40s were highly expressed only in red or green walnuts. In addition, we screened 16 unique JrWD40s to walnuts based on collinearity analysis. By qRT-PCR, we found that JrWD40-133, JrWD40-150, JrWD40-155, and JrWD40-206 may regulate anthocyanin synthesis through positive regulation, whereas JrWD40-65, JrWD40-172, JrWD40-191, JrWD40-224, and JrWD40-254 may inhibit anthocyanin synthesis, suggesting that these JrWD40s are key genes affecting walnut color variation. Full article

Incorporating extruded pea hulls (EPH) into wheat bread increases its nutritional value by increasing dietary fiber content, which in turn influences the physicochemical properties and sensory attributes of bread. This study aimed to assess the effect of varying EPH levels on the rheological properties of wheat dough, as well as on the physical and sensory attributes of wheat bread, providing insight into the optimal EPH inclusion level. Farinograph analysis indicated that the inclusion of extruded pea hulls progressively increased the water absorption capacity. At higher EPH replacement levels, bread exhibited decreased specific volume, increased hardness, reduced porosity, darker color, and pronounced sensory attributes of pea aroma and pea taste. Bread with 5–15% EPH retained physical qualities comparable to bread without EPH, with 5% EPH replacement particularly improving specific volume, porosity, and texture. However, 20–30% EPH significantly impaired bread quality, resulting in denser crumb, darker crumb color, and intensified pea aroma. These findings suggest that moderate EPH inclusion (up to 15%) is optimal for enhancing fiber content without compromising bread quality, while higher levels (20% and more) may negatively affect both physical and sensory attributes. Full article

Studies on the phenotypic traits and their associations in Chinese cabbage lack precise and objective digital evaluation metrics. Traditional assessment methods often rely on subjective evaluations and experience, compromising accuracy and reliability. This study develops an innovative, comprehensive trait evaluation method based on 3D point cloud technology, with the aim of enhancing the precision, reliability, and standardization of the comprehensive phenotypic traits of Chinese cabbage. By using multi-view image sequences and structure-from-motion algorithms, 3D point clouds of 50 plants from each of the 17 Chinese cabbage varieties were reconstructed. Color-based region growing and 3D convex hull techniques were employed to measure 30 agronomic traits. Comparisons between 3D point cloud-based measurements of the plant spread, plant height, leaf area, and leaf ball volume and traditional methods yielded R² values greater than 0.97, with root mean square errors of 1.27 cm, 1.16 cm, 839.77 cm³, and 59.15 cm², respectively. Based on the plant spread and plant height, a linear regression prediction of Chinese cabbage weights was conducted, yielding an R² value of 0.76. Integrated optimization algorithms were used to test the parameters, reducing the measurement time from 55 min when using traditional methods to 3.2 min. Furthermore, in-depth analyses including variation, correlation, principal component analysis, and clustering analyses were conducted. Variation analysis revealed significant trait variability, with correlation analysis indicating 21 pairs of traits with highly significant positive correlations and 2 pairs with highly significant negative correlations. The top six principal components accounted for 90% of the total variance. Using the elbow method, k-means clustering determined that the optimal number of clusters was four, thus classifying the 17 cabbage varieties into four distinct groups. This study provides new theoretical and methodological insights for exploring phenotypic trait associations in Chinese cabbage and facilitates the breeding and identification of high-quality varieties. Compared with traditional methods, this system provides significant advantages in terms of accuracy, speed, and comprehensiveness, with its low cost and ease of use making it an ideal replacement for manual methods, being particularly suited for large-scale monitoring and high-throughput phenotyping. Full article

Seed aging is a complex process that involves various physiological and biochemical changes leading to a decline in seed viability during storage. However, the specific biomarkers for assessing the degree of seed aging in rice remain elusive. In this study, we isolated a golden hull mutant, gh15, from the indica rice Z15 by employing a radiation mutagenesis technique. Compared with the wild type (WT) Z15, the mutant gh15 displayed a golden hue in the hull, stem, and internodes, while no significant differences were observed in the key agronomic traits. A genetic analysis showed that the gh15 phenotype is regulated by a single recessive gene, which possibly encodes cinnamyl alcohol dehydrogenase OsCAD2. Significant differences of seed aging tolerance were observed between gh15 and WT after six months of natural storage and artificial aging treatment, with gh15 exhibiting a markedly lower aging tolerance compared to the WT. Haplotype assays indicated that the Hap2 of OsCAD2 was significantly associated with the dark coloration of the hull and lower seed aging tolerance. The molecular marker of OsCAD2 associated with seed color was explored in rice. These findings demonstrate that the golden hull serves as a potential biomarker for the rapid assessment of seed aging tolerance in rice. Full article

Barley is rich in phenolic compounds, providing health benefits and making it a valuable addition to a balanced diet. However, most studies focus on these compounds at barley’s final maturity, neglecting their synthesis during grain development and its impact on barley quality for food applications. This study investigates phenolic profiles during grain development in four hull-less barley genotypes with different grain colors, specifically bred for food applications. The objectives were to determine the phenolic profile and identify the optimal maturity stage for maximum phenolic content and antioxidant capacity. Using UPLC-MS/MS and in vitro antioxidant capacity assays, results show that total phenolic compounds decrease as grain matures due to increased synthesis of reserve components. Flavan-3-ols, phenolic acids, and flavone glycosides peaked at immature stages, while anthocyanins peaked at physiological maturity. The harvest stage had the lowest phenolic content, with a gradient from black to yellow, purple, and blue genotypes. Antioxidant capacity fluctuated during maturation, correlating positively with phenolic compounds, specially bound phenolic acids and anthocyanins. These findings suggest that early harvesting of immature grain can help retain bioactive compounds, promoting the use of immature barley grains in foods. To support this market, incentives should offset costs associated with decreased grain weight. Full article

The PlantEye multispectral scanner is an optoelectrical sensor automatically applied to a mechatronic platform that allows the non-destructive, accurate, and high-throughput detection of morphological and physiological plant parameters. In this study, we describe how the advanced phenotyping platform precisely assesses changes in plant architecture and growth parameters of wild rocket salad (Diplotaxis tenuifolia L. [DC.]) under drought stress conditions. Four different irrigation supply levels from moderate to severe, required to keep 100, 70, 50, and 30% of the water-holding capacity, were adopted. Growth rate and plant architecture were recorded through the digital measure of biomass, leaf area, Canopy Light Penetration Depth, five convex hull traits, plant height, Surface Angle Average, and Voxel Volume Total. Vegetation color assessments included hue, lightness, and saturation. Vegetation and senescence indices were calculated from canopy reflectance in the red (620–645 nm), green (530–540 nm), blue (peak wavelength 460–485 nm), near-infrared (820–850 nm), and 3D laser (940 nm) ranges. The temperature, relative humidity, and solar radiation of the environment were also recorded. Overall, morphological parameters, color, multispectral data, and vegetation indices provided over 7200 data points through daily scans over three weeks of cultivation. Although a general decrease in growth parameters with increasing stress severity was observed, plants were able to maintain the same morpho-physiological performances as the control during the early growth stages, keeping both 70% and 50% of the total water-holding capacity. Among indices, the Normalized Differential Vegetation Index (NDVI) contributed the most to the differentiation between different stress levels during the cultivation cycle. Across the 3 weeks of growth, statistically significant differences were observed for all traits except for the Saturation Average. Comparisons with respect to the control highlighted the strong impact of drought stress on morphological plant traits. This study provided meaningful insights into the health status of wild rocket salad under increasing drought stress. Full article

There is a growing interest in exploring new natural sources of colorants. This study aimed to extract anthocyanins from broken black bean hulls (Phaseolus vulgaris L.) by modifying water with a eutectic mixture (choline chloride:citric acid (ChCl:Ca)). Ultrasound-assisted extraction (UAE) was employed and optimized in terms of temperature (30–70 °C), ultrasound power (150–450 W), and eutectic mixture concentration in water (1–9% (w/v)), resulting in an optimal condition of 66 °C, 420 W, and 8.2% (w/v), respectively. The main quantified anthocyanins were delphinidin-3-O-glycoside, petunidin-3-O-glycoside, and malvidin-3-O-glycoside. The half-life of the anthocyanins at 60 °C increased twelvefold in the eutectic mixture extract compared to the control, and when exposed to light, the half-life was 10 times longer, indicating greater resistance of anthocyanins in the extracted eutectic mixture. Additionally, the extracts were concentrated through centrifuge-assisted cryoconcentration, with the initial cycle almost double the extract value, making this result more favorable regarding green metrics. The first concentration cycle, which showed vibrant colors of anthocyanins, was selected to analyze the color change at different pH levels. In general, the technology that uses eutectic mixtures as water modifiers followed by cryoconcentration proved to be efficient for use as indicators in packaging, both in quantity and quality of anthocyanins. Full article

The technological and nutritional traits of food-grade sorghum hybrids, hulled/naked oat varieties and maize genotypes of different colors were studied for novel and healthier gluten-free foods. Oat genotypes showed the highest protein content, followed by maize and sorghum. The total starch and the total dietary fiber content were quite similar among the three species. Great variation was found in the amylose content, and the highest was in sorghum (27.12%), followed by oat 16.71% and maize 10.59%. Regarding the pasting profile, the rank of Peak Viscosity was sorghum (742.8 Brabender Unit, BU), followed by maize (729.3 BU) and oat (685.9 BU). Oat and sorghum genotypes had similar average breakdown (407.7 and 419.9 BU, respectively) and setback (690.7 and 682.1 BU, respectively), whereas maize showed lower values for both parameters (384.1 BU and 616.2 BU, respectively). The total antioxidant capacity, only in maize, significantly correlated with total flavonoid, phenolic and proanthocyanidin contents, indicating that all the measured compounds contributed to antioxidant capacity. The study indicated the importance of sounding out the nutritional and technological characteristics of gluten-free cereals in order to select suitable cultivars to be processed in different gluten-free foods with better and healthier quality. Full article

Almond processing generates a high quantity of by-products, presenting the untapped potential for alternative applications and improved sustainability in production. This study aimed to evaluate whether the incorporation of almond by-products (hulls/shells) can improve the biochemical characteristics of green bean pods when used as an alternative to traditional growing media in green bean plants. Four substrates were prepared: the Control substrate (C): 70% peat + 30% perlite; substrate (AS): 70% peat + 30% shells; substrate (AH): 70% peat + 30% perlite + 1 cm hulls as mulch; substrate (MIX): 70% peat + 15% shells + 15% hulls. Plants were grown in each of these substrates and subjected to two irrigation levels, 100% and 50% of their water-holding capacity. Biochemical parameters (photosynthetic pigments, total phenolics, flavonoids, ortho-diphenols, soluble proteins, antioxidant capacity) and color were evaluated in the harvested pods. Results showed that pods from plants growing in AH substrate presented statistically significant higher values in their total phenolic content, while AS and MIX substrates did not reveal significant benefits. Summarily, this study highlights the potential of almond hulls as a promising medium for green bean cultivation, particularly when employed as mulch. Further research is recommended to gain a more comprehensive understanding of the application of almond by-products as natural fertilizers/mulch. Full article

The quality of radish roots depends largely on its cultivar, production environment, and postharvest management along the supply chain. Quality monitoring of fresh products is of utmost importance during the postharvest period. The purpose of this study is to nondestructively estimate the weight of a radish using random forests based on color and shape information obtained from images, as well as volumetric information obtained by analyzing a point cloud obtained by combining multiple forms of shape information. The explanatory variables were color and shape information obtained through an image analysis of still images of radishes captured in a constructed photographic environment. The volume information was calculated from the bounding box and convex hull applied to the point cloud by combining the shape information obtained from the image analysis. We then applied random forests to relate the radish weight to the explanatory variables. The experimental results showed that the models using color, shape, or volume information all exhibited good performance with a Pearson’s correlation coefficient (COR) ≥ 0.80, suggesting the potential of nondestructive monitoring of radish weight based on color, shape, and volume information. Specifically, the model using volume information showed very high performance, with a COR of 0.95 or higher. Full article

The whole-grain, hulled Tartary buckwheat flour (HTBF) with outstanding bioactive functions was prepared, and the effects of partial substitution ratios (0, 30%, 51% and 70%) of wheat flour with HTBF on the characteristics of TB noodles (TBNs) were investigated, mainly including the cooking characteristics, sensory analysis, internal structure, bioactive components, and in vitro starch digestibility. With an increasing replacement level of HTBF, the water absorption index of the noodles decreased, whereas the cooking loss increased. A sensory analysis indicated that there were no off-flavors in all TBN samples. The scanning electron microscope images presented that the wheat noodles, 30% TBNs and 70% TBNs had dense and uniform cross sections. Meanwhile, the deepest color, V-type complexes, and lowest crystallinity (13.26%) could be observed in the 70% TBNs. A HTBF substitution increased the rutin content and the total phenolic and flavonoid contents in the TBNs, and higher values were found in the 70% TBNs. Furthermore, the lowest rapidly digestible starch content (16%) and highest resistant starch content (66%) were obtained in the 70% TBNs. Results demonstrated that HTBF could be successfully applied to make TBNs, and a 70% substitution level was suggested. This study provides consumers with a good option in the realm of special noodle-type products. Full article