Varieties Of Seeds Research Articles

Identification of varieties of wheat seeds based on multispectral imaging combined with improved YOLOv5

The identification of seed variety is important in wheat production because the growth and yield are highly related with its variety. Traditional identification methods for wheat seed varieties were suffered with time consuming and contamination. This study proposed a method for convenient identification of wheat seed varieties by using improved YOLOv5 combined with multispectral images. Three optimal spectral bands images including 405nm, 570nm and 890nm were selected to fuse new image from all 19 bands using Genetic algorithm and confusion matrix. The YOLOv5s model for wheat seed variety identification was improved by adding a convolutional block attention module (CBAM) and the identification model was developed with the fusion images. The identification performance of proposed method achieved an accuracy of 99.38% in testing set, which was better than traditional VOLOv5 with RGB images or with the multispectral images. Meanwhile, the evaluation indexes of the model such as P/%, R/%, F1/% and mAP/% were all higher than 90%, which showed that the method was suitable for identification of wheat seeds variety rapidly and non-destructively.

Research on variety identification of common bean seeds based on hyperspectral and deep learning

Accurate, fast and non-destructive identification of varieties of common bean seeds is important for the cultivation and efficient utilization of common beans. This study is based on hyperspectral and deep learning to identify the varieties of common bean seeds non-destructively. In this study, the average spectrum of 3078 hyperspectral images from 500 varieties was obtained after image segmentation and sensitive region extraction, and the Synthetic Minority Over-sampling Technique (SMOTE) was used to achieve the equilibrium of the samples of various varieties. A one-dimensional convolutional neural network model (IResCNN) incorporating Inception module and residual structure was proposed to identify seed varieties, and Support Vector Machine (SVM), K-Nearest Neighbor (KNN), VGG19, AlexNet, ResNet50 were established to compare the identification effect. After analyzing the effects of multiple spectral preprocessing methods on the model, the study selected Savitzky-Golay smoothing correction (SG) for spectral preprocessing and extracted 66 characteristic wavelengths using Successive Projections Algorithm (SPA) as inputs to the discriminative model. Ultimately, the IResCNN model achieved the highest accuracy of 93.06 % on the test set, indicating that hyperspectral technology can accurately identify bean varieties, and the study provides a correct method of thinking for the non-destructive classification of multi-species small-sample bean varieties.

Evaluation of Proximate Composition, Multielement, and Bioactive Phenolics Contents of Different Coix Seed Varieties using Multivariate Analysis Techniques

Coix lacryma-jobi L. is a plant that serves as a source of food, medicine, cosmetics, and forage in Asian countries. Due to the distinct geographic environments, Coix seed germplasm resources are extremely diverse. In this study, we evaluated the proximate composition, multi-elemental content by ICP-OES, and phenolic bioactives by UPLC-QTOF/MS of five varieties of Coix seeds from different Asian countries, including China, Thailand, Indonesia, and Malaysia. Principal component analysis (PCA) and hierarchical clustering analysis (HCA) were used to classify the different varieties of Coix seeds. The C. lacryma-jobi var. ma-yuen seeds from Origin 1 (China) and Origin 2 (Thailand) contained high levels of energy, total fat, and calcium, while C. lacryma-jobi var. agrotis (Indonesia) and C. lacryma-jobi var. lacryma-jobi (Malaysia) had high levels of crude fiber and carbohydrates. Twenty-three phenolic compounds were identified. Protein, carbohydrate, crude fiber, magnesium, zinc, meliadanoside, and 3,4-dihydroxyphenethyl-3-O-β-D-glucopyranoside were the dominant variables and contributed the most to data variability in PCA. The HCA results were consistent with the PCA, classifying the samples into three groups: those rich in nutrients, those rich in phenolics, and those with a mixture of nutrients and phenolics. This comprehensive analysis provides valuable insights into the nutritional and bioactive composition of Coix seed varieties, with potential applications in nutrition, food science, and pharmaceuticals.

Hemp Seed (Cannabis sativa L.) Varieties: Lipids Profile and Antioxidant Capacity for Monogastric Nutrition.

The present research aimed to study the proximate composition, fatty acid profile, antiox-idant activity, total phenolic and N-trans-Caffeoyltyramine content of three distinct varieties of hemp seeds (Carmaenecta, Enectaliana and Enectarol, grown in a Mediterranean area (Central Italy), as feed in the diet of farm animals. Proximate composition was determined using the official methods of analyses; the fatty acid profile was determined by gas chromatography, total phenolic content (TPC) and the scavenging activity (DPPH• and ABTS•+) by the colorimetric method, and N-trans-Caffeoyltyramine content by HPLC analysis. The hemp seed Enectarol showed the highest total lipid content and the best antioxidant activity with the highest TPC, N-trans-Caffeoyltyramine content, and ABTS•+, and the lowest peroxidation index and DPPH•; Carmaenecta showed the best fatty acid profile and nutritional indices (atherogenic and thrombogenic indices and hypocholesterolemic/hypercholesterolemic ratio), and Enectaliana showed the highest crude protein and dietary fiber content. The differences observed in the chemical composition, fatty acid profile and antioxidant activity are because of the varieties, considering that all other growing conditions were the same. The results obtained suggest that hemp seed can be used as a source of lipid and protein in animal diets due to their valuable antioxidant activity and as a rich source of essential fatty acids.

Assessment of the phenolic profile and biological activities of aqueous date seed extracts: A comparative analysis

Date palm fruit (Phoenix dactylifera L.) is a well-known fruit that has become increasingly popular among consumers due to its pleasant flavor, nutrient-dense content, and nutraceutical characteristics. Date seeds are the main by-product of date fruit consumption and processing. Date seeds are usually incorporated in animal feed; however, their application in human contexts, such as food products, remains minimal. Nonetheless, they contain significant amounts of bioactive phenolic compounds, primarily flavonoids, which possess potential health benefits. The current study investigated and compared the phenolic profile, antioxidant, and antibacterial activities of aqueous extracts of nine different date seeds varieties. The phenolic profile, analyzed using high-performance liquid chromatography (HPLC-DAD-ESI-MS), showed that total phenolic compounds ranged from 1.05 to 1.24 mg/g in Reziz and Naghal varieties, respectively, with flavan-3-ols predominating in all varieties. Results of the ABTS and DPPH assays revealed that the antioxidant activities against free radicals were directly correlated with the overall phenolic content, particularly for caffeic acid. Indeed, all date seeds possessed antibacterial capabilities, with a stronger effect observed on Listeria monocytogenes than Escherichia coli. Additionally, date seeds demonstrated a promising source of oil rich in oleic and lauric acids, both of which are considered beneficial for health. According to our findings, date seeds are a significant source of bioactive compounds, which renders them ideal candidates for potential inclusion in human diets as food additives and nutraceuticals.

Effect of germination on the nutritional properties of three pumpkin seeds varieties

Effect of germination on the nutritional properties of three pumpkin seeds varieties

Upcycling of melon seed (Cucumis melo L.) oil processing by-product: evaluation of functional properties and nutritional components as novel ingredient

BackgroundDefatted melon seed, a major by-product from melon oil processing chain, is scarcely utilsed. However, it has high potential value and can be used as novel ingredient in food products production. In line with zero waste policy and food sustainability, exploring and utilisation of this oil processing by-product can reduce food waste, and is key to moving towards a more sustainable food system. Therefore, this study aimed to assess the nutritional profile and functional properties of three varieties of defatted melon seeds (Galia, Cantaloupe, and Honeydew), and then compare them with defatted pumpkin seeds (as control group).ResultsIn this study, three varieties of melon seeds (Galia, Cantaloupe, and Honeydew) and pumpkin seeds (as control group) were defatted using Soxhlet extraction with petroleum ether; subsequently, their functional properties and nutritional components were assessed. The defatted melon seeds contained high level of protein (51.1–54.2%, w/w), dietary fibre (29.4–33.2%, w/w), potassium (1181.0–2373.1 mg/100 g), and GABA (γ-aminobutyric acid, 1.4–4.3 mmol/kg), whereas in terms of anti-nutritional compounds, they contained a relatively high amount of phytic acid (5.0%—5.8%, w/w). They also exhibited good in water/oil absorption capacity and emulsifying capacity. The phenolics were mainly free phenolics (FP) fraction (75%–77%), followed by the conjugated phenolics (CP) fraction (15%–16%), and the bound phenolics (BP) fraction (about 8%); the antioxidant capacity of each fraction followed the same sequence (FP > CP > BP).ConclusionConsidering the nutritional composition, functional properties, and the presence of potentially bioactive compounds, defatted melon seeds have considerable potential to be used as a functional food ingredient for the reformulation of foods.Graphical

Методические подходы (гипотезы) к оценке пригодности сортов винограда к возделыванию в корнесобственной культуре

Abstract. One of the ways to reduce the cost of grapes and intensify the industry is to preserve and expand the own-root culture of phylloxera-tolerant grape varieties. Currently, there are all the prerequisites for expanding the own-root grape culture – a number of varieties have been obtained that are resistant to phylloxera and root rot with good quality of grape berries and their processed products. To extend the life of plantings and increase their profitability, it is important to identify grape varieties for cultivation in ownroot culture. However, comparative pairwise studies of varieties in own-rooted and grafted culture are lengthy and costly. The purpose of the research is to search for criteria for the accelerated assessment of Vitis vinifera L. varieties for suitability for cultivation in own-root culture using the example of genotypes of the DBESV&VG breeding. The research was carried out at the experimental base and the Ampelographic Collection of DBESV&VG in 2017-2023. The object of research is model and fruit-bearing rooted and grafted plants of different grape varieties with different resistance to phylloxera, 47 seed varieties of the Ampelographic Collection of DBESV&VG, 16 varieties and hybrid forms of DBESV&VG breeding. It has been assumed and experimentally confirmed that the higher the seed productivity of a grape variety (high proportion (mass) of seeds in a bunch, low seed index of the berry), the higher the tolerance of the variety to root phylloxera. Grape varieties, the reaction of which is expressed in an increase in seed progeny (“mass of seeds in a bunch”) with hormonal regulation of the development of rooted plants, can be cultivated in a rooted culture against the background of phylloxera. Keywords: grapes, phylloxera, root culture, phylloxera tolerance, seed productivity, phylloxera resistance criteria, hormone regulation

Secondary metabolites of soybean seeds variety locus and their spatial arrangement, represented by laser microscopy

The purpose of this study is a detailed metabolomic analysis using tandem mass spectrometry of the soybean variety Locus, selected from the collection of the Federal Scientific Center for Agrobiotechnologies of the Far East named after A. K. Chaika», to identify both the polyphenolic composition of seeds and the determination of other chemical groups in the composition of the seed. Tandem mass spectrometry studies were further supported by visual data obtained for the first time using laser microscopy. The object of the study is the seeds of the soybean variety Locus, grown in 2022 at the field site of the soybean breeding laboratory of the Federal Scientific Center for Agrobiotechnologies of the Far East named after A. K. Chaika», located in the village of Timiryazevsky (near the city of Ussuriysk). Experiments were carried out on a CLSM-800 laser confocal microscope and mass spectrometry of biologically active substances on an amaZon SL ion trap. Laser microscopy made it possible to clarify in detail the spatial distribution of the content of phenolic acids, flavonols and anthocyanins in soybean seeds. The studies were able to convincingly show that soybean polyphenolic substances and, in particular, anthocyanins are spatially localized mainly in the soybean seed coat. High-performance liquid chromatography coupled with ion trap (tandem mass spectrometry) was used to identify target analytes in soybean seed extracts. Using tandem mass spectrometry, the presence of 59 compounds was identified, of which 35 compounds represent the group of polyphenolic compounds. 15 compounds were identified for the first time in soybean extracts of the Locus variety. These are flavones: apigenin, acacetin, cirsimaritin; tetrahydroxyflavone aromadendrin 7-O-rhamnoside; lignan medioresinol; coumarin tomentin and other polyphenolic compounds. The data obtained will help intensify future research on the development and production of new drugs, dietary supplements, food additives and various functional and specialized products containing targeted soybean extracts.

Investigating the Endophyte Actinomycetota sp. JW0824 Strain as a Potential Bioinoculant to Enhance the Yield, Nutritive Value, and Chemical Composition of Different Cultivars of Anise (Pimpinella anisum L.) Seeds.

Anise (Pimpinella anisum L.) seeds have various nutritional and therapeutic benefits and are thus considered a valuable addition to animal and human health. Hence, in this study, we aimed to induce the nutritive and biological value of anise seeds. To this end, the potential biofortification effect of the endophytic Actinomycetota sp. JW0824 strain, isolated during the fall of 2023 from the medicinal plant Achyranthes aspera, exhibiting natural distribution in the Jazan region of Saudi Arabia, was investigated in four varieties of anise seeds from Egypt, Tunisia, Syria, and Morocco. Results revealed significant increments (p < 0.05) in the seed dry weight percentage (DW%) and oil yields. In line with increased biomass accumulation, the metabolism of the primary and secondary metabolites was increased. There were differential increases in proteins, sugars, flavonoids, alkaloids, phenols, vitamins (e.g., β-carotene, ascorbic acid), and essential oil components (e.g., phenylpropanoids and monoterpenes), along with their precursor phenylalanine. Consistently, the activity of L-phenylalanine aminolyase (PAL) was increased in the Egyptian and Tunisian varieties at 83.88% and 77.19%, respectively, while 3-deoxy-D-arabino-heptulosonate-7-phosphate synthase (DAHPS) activity increased in all varieties, with a significant 179.31% rise in the Egyptian variety. These findings highlight the beneficial effects of Actinomycetota sp. JW0824 as a bioinoculant for anise seeds, suggesting its potential application in agricultural practices to improve seed yield and quality. Further field trials are recommended to assess the commercial viability of this endophyte for enhancing anise seed production and potentially benefiting other plant species.

Pollination Efficiency of Apis mellifera L. (Hymenoptera: Apidae) on Flowers of Phaseolus vulgaris L. (Fabaceae) at Doyaba (Sarh, Chad)

To evaluate the impact of single visit of Apis mellifera on pod and seed yields of Phaseolus vulgaris Large White Seeds variety, the foraging and pollinating activities of the honey bee were studied in Sarh, during 2021 and 2022 rainy seasons. Treatments included unlimited flowers access by all visitors, bagged flowers, flowers limited visits by A. mellifera only and flowers bagged, opened and closed without insect or other organism visits. The foraging behavior of A. mellifera on flowers and its pollination efficiency were recorded. Apis mellifera was the most frequent visitor and it intensely and exclusively collected nectar. The fruiting rate of unprotected flowers is significantly higher than that of protected flowers. Through its pollination efficiency, A. mellifera had increase significally the fruiting rate by 52.27%, the number of seeds/pod by 30.79% and the percentage of normal seeds by 84.03%. The conservation strategies and installation of A. mellifera colony close to P. vulgaris fields is recommended to improve its pod production and seed quality in the province.

Nondestructive Identification of Wheat Seed Variety and Geographical Origin Using Near‐Infrared Hyperspectral Imagery and Deep Learning

ABSTRACTSeed purity assurance is an important aspect of maintaining the quality standards of wheat seeds. It relies significantly on quality parameters, like varietal classification and geographical origin identification. Hyperspectral imaging (HSI) has emerged as an advanced nondestructive technique to determine various quality parameters. In recent years, several studies have utilized HSI for varietal classification, although a limited number of varieties were considered. Additionally, no attention has been paid to determining the geographical origin of wheat seeds. To address these gaps, two separate experiments were performed for varietal classification and geographical origin identification. The seeds from 96 varieties grown across 5 different agricultural regions in India were collected. Hyperspectral images of wheat seeds were acquired in the wavelength ranging 900–1700 nm. The spectral reflectance values were obtained from the region of interest (ROI) corresponding to each seed. Subsequently, the deep learning models (convolutional neural networks [CNNs]) were established and compared with two conventional algorithms, including support vector machines (SVMs) and K‐nearest neighbors (KNNs). The experimental results indicated that the proposed CNN models outperformed the SVM and KNN models, achieving an overall accuracy of 94.88% and 99.02% for varietal classification and geographical origin identification, respectively. These results demonstrate that HSI combined with deep learning has the potential to accurately classify a large number of wheat varieties. Moreover, HSI can be used to precisely identify the geographical origins of wheat seeds. This study provides an accurate and nondestructive method that can assist in breeding, quality evaluation, and the development of high‐quality wheat seeds.

Climate-Smart Agriculture as an Adaptation Measure to Climate Change in Togo: Determinants of Choices and Its Impact on Rural Households’ Food Security

Climate-smart agriculture is one of the most important actions for agricultural climate change adaptation, especially in Togo, a sub-Saharan African country with a fragile ecology and where agriculture is profoundly impacted by climate change. Using a multinomial endogenous switching regression (MESR) and a multinomial endogenous treatment effect (METE) approach, we conducted empirical research to identify the factors influencing the adoption decisions of climate-smart agricultural practices (CSAPs) and their impact on household food security among smallholder farmers in Togo. The findings of this study revealed that the adoption of CSAPs by farmers is influenced by a range of factors, such as age, marital status, the household head’s gender, engagement in off-farm activities, level of education, farm size, agroecological zone, regional location, land ownership, distance between homestead and farm, access to credit, the presence of agricultural associations and cooperatives, and access to extension agents. On the one hand, the MESR analysis demonstrated a positive correlation between the number of adopted CSAPs and households’ food consumption score. Similarly, greater adoption of CSAPs resulted in a significant reduction in the food insecurity experience scale. On the other hand, the METE model portrayed an increase in acceptable food consumption when households adopted up to three CSAPs. Likewise, it significantly alleviated severe food insecurity. Further results based on the propensity score matching technique showed that the adoption of a crop rotation system, utilization of improved varieties of seeds, plant protection products, inorganic fertilizer, organic fertilizer, and irrigation improved adopters’ food consumption scores while reducing their level of food insecurity.

Multi-level data fusion strategy based on spectral and image information for identifying varieties of soybean seeds

Rapid identification of soybean seed varieties is crucial for agricultural production and seed quality. Identifying varieties of soybean seed using conventional chemical methods is time-consuming, destructive, and inappropriate for seed quality evaluation. This study utilized hyperspectral imaging technology (HSI) to identify four varieties of soybean seeds. The hyperspectral images of soybean seeds were collected in the spectral range of 400–1000 nm. A multi-level data fusion strategy based on spectral and image information was proposed to improve the accuracy of model. Subsequently, the multi-level data fusion strategy based on partial least squares discriminant analysis (PLS-DA) was used to establish the classification models of soybean seeds. Compared with the models using individual analytical sources, the results demonstrated that the models with multi-level data fusion strategy obtained better prediction performance. The high-level data fusion (HLDF) based on Bayesian consensus provided the optimal results with an accuracy (Acc) and F1-score of 93.13 % and 93.70 % in the prediction phase, respectively. Therefore, the multi-level data fusion strategy can be used as an identification method for soybean seed varieties and an effective approach to enhance the discriminatory capability of models.

Structure Characteristics, Variation of Main Quantitative Traits, and Probability Grading of Chinese Olive (Canarium album) Seeds

In order to comprehensively describe and evaluate Chinese olive seeds, this study examined 33 varieties (strains) of Chinese olive seeds to address the limitations of previous research on quantitative trait variation and grading among Chinese olive seed varieties (strains). The research specifically focused on evaluating the morphological characteristics, seed locule structure, embryo composition, and phenotypic quantitative traits of Chinese olive seeds. The results indicated that Chinese olive seeds consisted of a core, seed coat, and embryo. Typically, the core contained two to four locules, with each locule containing zero to one embryos. Eight distinct structural variations were identified, with the number of locules per seed ranging from two to four and the number of embryos ranging from one to four. The most common structural types were ‘3-locule 1-embryo’ and ‘3-locule 2-embryo’, each occurring in 100% of the varieties (strains) studied. These two structural types also had a high average proportion within each variety (line), accounting for 50.17% and 42.06%, respectively. The average dimensions of a seed were 31.20 mm in length and 10.89 mm in width, with a shape index of 2.89 and weighing 1.55 g. These quantitative traits displayed significant variation, with the coefficient of variation being highest for single seed weight (19.35%) and lowest for seed length (9.39%). Normality tests revealed that seed width, seed length, and single seed weight followed a normal distribution. These traits were categorized into five levels based on specific points, with probabilities of occurrence approximately 10%, 20%, 40%, 20%, and 10%, respectively. The findings of this study are crucial for understanding and utilizing Chinese olive seed traits and provide valuable insights for the establishment of seed trait standards and data normalization.

Cell wall permeability in relation to in vitro starch digestion of pea cotyledon cells

The role of cell wall permeability and rate of starch digestibility in intact cotyledon cells from four different varieties of pea seeds was studied. Pulsed-field gradient nuclear magnetic resonance (PFG NMR) coupled with light and confocal microscopy were employed to evaluate the cotyledon cells' diffusion coefficients and cell wall permeability. The cotyledon cells' diffusion coefficients and cell wall permeability followed a decreasing trend: White/yellow pea > Marrowfat pea > Maple pea > Blue pea. The varying size of internal cavities in the microstructure in the cotyledon cells, as observed by the light and confocal micrographs, may be responsible for this trend. The extent of starch hydrolysis recorded from the cotyledon cells followed the same trend of the cell wall permeability except for Blue pea cotyledon cells. Thus, indicating that the more permeable the cotyledon cell to the starch-degrading enzymes, the higher the extent of intracellular starch hydrolysis. The microstructure changes in the cotyledon cells during digestion also confirmed this observation.

Research on nondestructive detection of sweet-waxy corn seed varieties and mildew based on stacked ensemble learning and hyperspectral feature fusion technology

The variety and quality of corn seeds are crucial factors affecting crop yield and farmers’ economic benefits. This study adopts an innovative method based on a hyperspectral imaging system combined with stacked ensemble learning, aiming to achieve varieties classification and mildew detection of sweet-waxy corn seeds. First, data interference is eliminated by extracting the spectral and texture information of each corn sample and preprocessing the data. Secondly, a stacked ensemble learning model (Stack) was constructed by stacking base models and meta-models. Its results were compared with those of the base models, including Gradient Boosting Decision Tree (GBDT), Extreme Gradient Boosting (XGBoost), Light Gradient Boosting Machine (LightGBM), and Random Forest (RF).Finally, the overall performance of the model is improved through the information fusion strategy of hyperspectral data and texture information. The research results indicate that the GBDT-Stack model, which integrates spectral and texture data, demonstrated optimal performance in the comprehensive classification of both corn seed varieties and mold detection. On the test set, the model achieved an average prediction accuracy of 97.01%. Specifically, the model achieved a test set accuracy ranging from 94.49% to 97.58% for different corn seed varieties and a test set accuracy of 98.89% for mildew detection. This model not only classifies corn seed varieties but also accurately detects mildew, demonstrating its wide applicability. The method has huge potential and is of great significance for improving crop yield and quality.

The Hygroscopic Properties and Sorption Isosteric Heat of Coix Seeds

Coix seeds are one of the most difficult-to-store cereal foods, and in order to maintain their quality during storage, the present study was conducted to determine the moisture adsorption and desorption isotherms of five varieties of coix seeds in the ranges of 10-35 °C and 11.3%-96.0% equilibrium relative humidity (ERH) using a static gravimetric method. The isotherms showed sigmoidal curves, and there was a hysteresis between adsorption and desorption isotherms. Six equilibrium moisture equations were used to fit the isotherms, and the Modified Chung-Pfost (MCPE), Modified Guggenheim-Anderson-deBoer (MGAB), Modified Henderson (MHE), Modified Oswin (MOE) and our developed modified Caurie (MCaurie) equations were suitable for fitting the data, among which MCPE was the best fitting equation. The monolayer water content decreased with increasing temperature, and the content of monolayer water, the density and layer number of adsorbed water, and the content of bound water for desorption were significantly higher than those of adsorption. The absolutely (ERH 65%) and relatively (ERH 70%) safe moisture contents (MC, wet basis, w.b.) of coix seeds were respectively 12.45%-12.82% and 13.15%-13.69% at 25 ℃. At equilibrium moisture content (EMC) less than 14.9% w.b., the desorption isosteric heats of coix seed were greater than the adsorption isosteric heats, and both decreased sharply in a hyperbolic form, approaching the latent heat of pure water at 14.9% w.b. The sorption isosteric heat of large-grain coix seed was slightly less than that of small-grain seed due to more cracks in the kernel back surface and more micropores in starch granular surface and resultantly more moisture sorption capacity. These results suggest that the desorptive and adsorptive behaviors of coix seeds should be differentiated for cooldown aeration, demoisturizing and remoisturizing operation, and the average isotherm can be used for common storage management.

Effect of processing methods on the phytochemical content of melon seeds (Cucumis melo L.)

This study aimed to investigate and evaluate the effect of processing (soaking, boiling, and roasting) on the phytochemical content of melon seeds. Two varieties of melon seeds (Galia and Cantaloupe) were processed by three processing methods including soaking, boiling, and roasting, and analysed in terms of their proximate composition, mineral content, anti-nutritional compounds, as well as fatty acid and amino acid contents. Soaking and boiling reduced the tannins content by 13 % - 20 %, 10 % - 26 %, respectively. Boiling had a positive effect on the extractability of lipid, while it resulted in a slight decrease in protein content (by approximately 6 %) and a significant potassium loss (up to 36 % decrease; p < 0.05). Roasting enhanced mineral content (especially in zinc and iron), but increased tannins by 40 % - 114 % and phytic acid contents by 3 % - 5 %. Of the three processing methods, roasting was most effective in remaining the nutritional value of melon seeds, and boiling was most effective in reducing tannins content. Overall, this study could guide the development of appropriate melon seed processing method to retain high nutritional value.

Understanding the efficiency of Shodhana, a classical drug detoxification technique that may increase safety in using three varieties of Abrus precatorius L. seeds-a toxic Schedule E1 drug used in various herbal formulations

BackgroundAbrus precatorius L. is a noxious vein native to south east asia and popularly called as Gunja in Ayurveda. The seeds of this plant are considered as a potent raw drug used in various herbal formulations such as Gunjadi tailam, Gunjagarbha rasa etc. and used to treat various ailments such as dermal disorders, cysts, snake poisoning and may other conditions. Before utilizing for the herbal formulations, the seeds are classically processed due to the presence of well reported toxic protalbumin named Abrin with the human fatal dose of 0.1–1 µg/kg. MethodsIn this work three varieties of Abrus precatorius L. seeds (Red, White and Black) were collected from the southern part of India and subjected for the detoxification process in order to analyze the efficiency of technique on different varieties of seeds. For processing the seeds, the classically fermented supernatant of rice gruel named kanjika was prepared and the pH was analyzed. Before and after processing, the seeds were analyzed for phytoconstituents with histochemistry technique and the hydroalcoholic extracts were prepared and qualitatively estimated for phytochemicals. The detoxification efficiency was analysed using HPTLC method by qualitative and quantitative estimation of Abrin levels by comparing with standard marker. Following that, cytotoxicity study was conducted against Vero (Healthy kidney) cell lines to ensure reduced toxicity in in-vitro conditions. ResultsThe process of Shodhana has changed the phytochemical levels in the processed seeds in comparison with unprocessed seeds in all three varieties. In connection to that, the extracts prepared with processed seeds have expressed lesser cytotoxicity and can be used as a drug with lesser side effects in whatever indications applicable. ConclusionIt is concluded that Shodhana with kanjika is efficient in processing all three varieties of Abrus precatorius seeds and is more effective in processing white seeds than the red and black varieties.