Varieties Of Seeds Research Articles

Fast Identification of Soybean Seed Varieties Using Laser-Induced Breakdown Spectroscopy Combined With Convolutional Neural Network.

Soybean seed purity is a critical factor in agricultural products, standardization of seed quality, and food processing. In this study, laser-induced breakdown spectroscopy (LIBS) as an effective technology was successfully used to identify ten varieties of soybean seeds. We improved the traditional sample preparation scheme for LIBS. Instead of grinding and squashing, we propose a time-efficient method by pressing soybean seeds into rubber sand filled with culture plates through a ruler to ensure a relatively uniform surface height. In our experimental scheme, three LIBS spectra were finally collected for each soybean seed. A majority vote based on three spectra was applied as the final decision judging the attribution of a single soybean seed. The results showed that the support vector machine (SVM) obtained the optimal identification accuracy of 90% in the prediction set. In addition, PCA-ResNet (propagation coefficient adaptive ResNet) and PCSA-ResNet (propagation coefficient synchronous adaptive ResNet) were designed based on typical ResNet structure by changing the way of self-adaption of propagation coefficients. Combined with a new form of input data called spectral matrix, PCSA-ResNet obtained the optimal performance with the discriminate accuracy of 91.75% in the prediction set. T-distributed stochastic neighbor embedding (t-SNE) was used to visualize the clustering process of the extracted features by PCSA-ResNet. For the interpretation of the good performance of PCSA-ResNet coupled with the spectral matrix, saliency maps were further applied to visually show the pixel positions of the spectral matrix that had a significant influence on the discrimination results, indicating that the content and proportion of elements in soybean seeds could reflect the variety differences.

PERKECAMBAHAN BENIH KOPI ARABIKA (Coffea arabica L.) VARIETAS GAYO I AKIBAT PENGUPASAN KULIT TANDUK DAN PEMBERIAN ZAT PENGATUR TUMBUH (ZPT)

Hairunnas “Germination Arabica coffee Seeds (Coffea arabica L.) Variety Gay Due to Peeling Off The Skin And Giving Growth Regulator” which is carried out as collaborative research between lecturers and students. This research was conducted at the Faculty of Agriculture- Agricultural Laboratory of Universitas Gajah Putih, Pegasing Aceh Tengah District with an altitude above sea level of 1,200 m and the degree of soil acidity (pH) was 6. The research was carried out in October 2019. The results showed that the stripping of hornbones had a significant effect on potential Growth and germination, the best yield was potential growth with the treatment without hornbill (B1) at the age of 55 days germinating. The use of growth regulators had a significant effect on the potential for growth, with the best yielding potential for the growth potential of 55 days after seedling with 200 cc / l (Z2) treatment. There is a very real interaction with the stripping of horn skin and the administration of growth regulators in the growth potential test. The best results were obtained in the interaction between treatment without horn skin (B1) and dosage of 200 cc / l (Z2) or (B1Z2).

Varietal Classification of Lactuca Sativa Seeds Using an Adaptive Neuro-Fuzzy Inference System Based on Morphological Phenes

Seed varieties are often differentiated via the manual and subjective classification of their external textural, spectral, and morphological biosignatures. This traditional method of manually inspecting seeds is inefficient and unreliable for seed phenotyping. The application of computer vision is an ideal solution allied with computational intelligence. This study used Lactuca sativa seed variants, which are commercially known as grand rapid, Chinese loose-leaf, and iceberg (which serves as noise data for extended model evaluation), in determining their corresponding classifications based on the extended morphological phenes using computational intelligence. Red-green-blue (RGB) imaging was employed for individual kernels. Extended morphological phenes, that is, solidity, roundness, compactness, and shape factors, were computed based on seed architectural traits and used as predictors to discriminate among the three cultivars. The suitability of ANFIS, NB, and CT was explored using a limited dataset. A mean accuracy of 100% was manifested in ANFIS; thus, it was proved to be the most reliable model.

Varietal classification of maize seeds using computer vision and machine learning techniques

AbstractIn agriculture, seed sorting is critical for production and marketing purposes. Low‐quality seeds can cause poor plant growth and lead to problems such as disease and low yields. This study uses machine vision and machine learning to develop a rapid detection and classification method for maize (Zea mays L.) seeds based on variety purity. A computer vision system was designed to recognize five varieties of maize seeds. Halogen lamps were applied for illumination and a high‐resolution RGB camera was used to acquire images of 8,080 maize seeds in the laboratory. An image processing algorithm was proposed to extract 16 important features (12 dimensional and 4 of shape) from the maize seed images, and a user‐friendly interface was developed using a MATLAB graphical user interface (GUI). Multilayer perceptron (MLP), decision tree (DT), linear discrimination (LDA), Naive Bayes (NB), support vector machine (SVM), k‐nearest neighbors (KNN), and AdaBoost algorithm were used to develop the varietal classification model. The optimal model parameters were obtained with 10‐fold cross‐validation, and the performance metrics were compared. The names of the maize varieties were marked in the GUI. The overall classification accuracy was determined as 96.26, 94.95, 95.97, 93.97, 96.46, 95.59, and 95.31% for MLP, DT, LDA, NB, SVM, KNN, and AdaBoost, respectively. The SVM classification model obtained the highest accuracy for BaoQiu, ShanCu, XinNuo, LiaoGe, and KouXian varieties, which reached 93.07, 98.95, 96.15, 89.65, and 99.22%, respectively. The classification results satisfy the needs of producers and consumers.

Economic analysis of the impact of cultivated potato cultivars on the productivity of the spring season 2018 (Ameriyat al-Fallujah district is an applied model)

The importance of the research is highlighted by the economic importance of the potato crop as it is cultivated with two lugs a year, In addition to its nutritional importance. Despite the expansion of potato cultivation in Ameriyat al-Fallujah district, potato production is still below the level that meets local demand. Lack of knowledge of varieties suitable for environmental conditions may be one of the factors contributing to the low yields of the crop. The aim of this study was to estimate the production functions as one of the factors affecting potato production determine the production elasticities and the effect of the cultivated variety on the technological and other factors in the estimated function. The study was based on a random sample of 183 potato farms in the study area for the spring season 2018. Using SPSS and EVIEWS9, The results showed that the Safrana variety had a positive effect on the estimated function while the Sanjari variety had a negative effect. Production elasticities indicated that the automated component is less influential on potato production than the manual component Which had the strongest effect among the elements of production and from it we deduce the small areas planted with the crop the prevalence of the use of traditional handicrafts in the cultivation and service of the crop. Therefore, the researcher recommends the cultivation of varieties of seeds with high productivity and good economic yield such as (Safrana) the expansion of potato crop cultivation and the use of production elements as recommended by the competent authorities.

Integrated Planting Machine with Metering Mechanism Suitable for Various Seeds

This study was conducted for the purpose of developing and manufacturing integrated planting machine with a disc metering device attached crank mechanism suitable for many seeds of different shapes and size. A (4.5 Hp) diesel engine as a source of power for machine ground wheel rotation and metering system parts motivation, machine was tested under three ground wheel revolutions GR (30, 45 and 55) rpm, three metering disc to ground wheel revolution ratios MG (0.25, 0.3 and 0.5) and three kinds of seeds variety SV (sun-flower seed, cowpea and black seed) .Experimental measurements were taken for the purpose of characterizing the experimental seed factors as follows:shape index (SI), weight of 1000 seeds (W), seeds moisture content (MC) determination, Actual seeds volume (V) and real density (γ). To evaluate the influence of previous factors there were procedural experiments on machine performance with main three measurements visible, invisible and total seeds damage (SD), actual seed feeding rate (SF) /10m of planting row distance and seeds lateral scattering frequency (L.S %) around the planting row centerline. The results showed that: experimental seeds tend to be oval in shape factor and have a low moisture content less than 18.5%, the highest (SD) at the higher value of ground wheel revolutions GR3=55 rpm. The best feeding rate for black seed (4 to 5 seed in feed-blot) obtained with MG2=0.3 while sun flower seed and cowpea (1 seed in feed-blot) with planting distance 20 cm at MG1=0.25 and GR1= 30 rpm.

Nondestructive identification of barley seeds variety using near‐infrared hyperspectral imaging coupled with convolutional neural network

AbstractNondestructive inspection of varietal purity of seeds plays an important role in crop improvement, agricultural production, and plant breeding. In the present study, a rapid and nondestructive technique, that is, near‐infrared hyperspectral imaging (NIR‐HSI) was applied to discriminate the barley seeds variety. A large dataset of 35,280 seeds was collected from different locations and years incorporating 35 Indian barley varieties (29 hulled and 6 naked barley varieties). The hyperspectral reflectance images of the ventral side and dorsal side of seeds were acquired in the near‐infrared range of 900–1700 nm. Mean spectra were extracted and pretreated by six preprocessing techniques (standard normal variate (SNV), multiplicative scatter correction (MSC), Savitzky–Golay (SG) smoothing, SG first derivative, SG second derivative, and detrending). Subsequently, raw and preprocessed spectral data were fed as input to the convolutional neural network (CNN) including traditional machine learning models (partial least squares discriminant analysis (PLS‐DA), K‐nearest neighbors (KNN), and support vector machines (SVM)). It was observed that the end‐to‐end CNN model built on raw spectra overperformed the model using the preprocessing strategies. In addition, the CNN model outperformed the three traditional models with a testing set accuracy of greater than 98%. The results demonstrated that NIR‐HSI coupled with end‐to‐end CNN could be a robust way to quickly, accurately, and nondestructively identify the variety of barley seeds.Practical ApplicationsThe commercial price and quality of barley mainly depend upon its varietal purity. Identification of barley seeds variety is an important step to select the seeds for different purposes such as food, malt, and fodder. Traditional methods for the identification of barley seeds variety are time‐consuming, expensive, and destructive. Near‐infrared hyperspectral imaging, as an emerging fast and nondestructive technique, looks promising for seed quality and safety evaluation. Moreover, the convolutional neural network has a better capability to accurately discriminate spectra extracted from seeds of different varieties of barley. The results in this study can provide a reference and theoretical basis to develop a real‐time inspection system for fast, accurate, and nondestructive barley seeds purity testing.

Effects of Consuming Different Varieties of Bambara Nut (Vigna subterranea) Seeds on Liver and Kidney of Diabetic and Non-diabetic Subject

Aims: Bambara nut seeds have been reported as a good source of food with high fiber and nutritional contents, and is consumed by persons with diabetes as one of the dietary therapy. However, the plant seeds are of different varieties and whether they might have vary biological effects on renal and liver functions is not fully known. This has prompted the study to evaluate effects of consuming different varieties of Bambara Nut seeds on liver and kidney of both diabetic and non-diabetic rats.
 Methodology: Four Bambara nut seeds varieties were dehulled and each heated at 60oC, cooled then grounded into flour using a mechanical grinder. The flours were used to formulate feeds which were given to different diabetic and non-diabetic rats’ groups as follows; group A (ALK01 feed), group B (ALK02 feed), group C (ALK03 feed), group D (ALK04 feed), group E (Basal feed), and group F (Normal animal’s feed). The animals were fed for 28 days then sacrifice, blood collected and serum separated and used for hepatic and renal parameters analysis.
 Results: The results of the study showed decrease levels of serum total protein and albumin, and elevation of AST and ALT activities as well as urea and creatinine concentrations in diabetic rats fed basal and normal diets, whereas, reverse in these parameters were recorded from diabetic rats fed varieties of Bambara nut seeds’ formulated feeds. 
 Conclusion: Findings from the study suggest consumption of Bambara nut seeds of different varieties is safe and has ability to ameliorate diabetic hepatic and renal failure in a variety dependent manner where; ALK 04 is more likely the most effective.

Correlation of physical properties for establishments of standardized groups of soybean seed technologies in post-harvest

Physical characteristics determination of soybean seeds will help optimize processes and the development of projects and regulation of post-harvest equipment. Thus, the study aimed to characterize and correlate the physical properties of different varieties of soybean seeds to identify and form groups of cultivars with physical similarities for a technical-scientific recommendation of management of seed lots, adjustments, and dimensioning equipment and structures post-harvest. Seeds from forty soybean cultivars were clustered using the k-means algorithm, which groups treatments whose centroids are closest until there is no significant variation in each observation's minimum distance to each centroid characterized as G1-seeds larger, G2-seeds medium-large, G3-seeds medium-smaller, G4-seeds smaller. Next, Pearson's correlation coefficients were estimated to verify the association between physical properties. The cultivars of G1 and G4 differed from the predominant groups G2 and G3. The cultivars FLECHA IPRO, 6139 RR, KWS RK 6813 RR, KWS RK 6813 RR2, and MAMBA RR predominated as G1-seeds larger. The cultivars NS 7447, TMG 1180GX RR, KWS RK 6813 RR2, CD 2686 IPRO, M6410, 6139 RR, and 8473 RR predominated as G4-seeds smaller. The correlation of most physical properties between cultivars was low, indicating individual evaluations in projects. The physical variability of soybean seeds defined the important interaction between the industry of post-harvest equipment manufacturing and the area of genetic improvement of seeds to advance the development of quality technologies, enabling the optimization of agricultural processes.

Structure-function relationship of black cumin seeds protein isolates: Amino-acid profiling, surface characteristics, and thermal properties

• The extraction of black cumin seeds proteins was optimized using response surface methodology. • The black cumin seeds proteins isolate showed a semi-crystalline structure. • FTIR analysis revealed the typical peaks of protein. • Black cumin seeds proteins were thermally stable until approximately 90 °C. • Black cumin seeds proteins presented peculiar functional properties. The aim of the present investigation was to determine the chemical composition, the amino-acid profiling, the structural characteristics and the functional properties of protein isolates of two black cumin seeds varieties. Response surface methodology (RSM) was firstly carried out to determine optimal conditions of proteins extraction from black cumin seeds. Results indicated that the meal to solvent ratio, pH and extraction time were stated as the main influencing factors to obtain protein isolates of black cumin seeds. The protein content of cumin seeds protein isolates varied between 68.76%–78.41% showing the predominance of glutamic acid (12.73–14.59 %), aspartic acid (5.28–5.62 %) and arginine (4.94–5.49 %) amino acids. X-ray diffraction patterns of the protein isolates showed a semi-crystalline structure. Structural characterization by FTIR analysis showed the typical peaks of protein, namely, amide I, amide II and amide III. The thermal properties of protein isolates were investigated by differential scanning calorimetry. A denaturation temperature ranged from 88.11 °C to 90.65 °C. Black cumin seeds protein isolates were able to decrease the interfacial tension (down to 17.62 mN/m) leading to an interesting emulsifying (up to 159.53 m 2 /g) and foaming (up to 145.54 %) properties as function of pH.

Nondestructive identification of barley seeds varieties using hyperspectral data from two sides of barley seeds

AbstractThe identification of seed varieties is of significance to ensure seed purity. In this study, 1,600 barley seeds (400 per variety) were selected as the samples. By using a near‐infrared hyperspectral imaging system, the hyperspectral cube data on the reverse and ventral sides of each barley seed were obtained. Three preprocessing methods (standard normal variate, multivariate scatter correction, and Savitzky–Golay first derivative) and three discriminant models (k‐nearest neighbors, support vector machine [SVM], and random forest) were selected for preprocessing and modeling, respectively. The results indicated that the reverse spectral data preprocessed by multivariate scatter correction and the ventral spectral data preprocessed by Savitzky–Golay first derivative had the best modeling results. In order to further simplify the model, feature selection algorithm (successive projections algorithm) was used for feature wavelength selection. After multivariate data analysis, the combination of k‐nearest neighbors and successive projections algorithm based on the reverse spectral data was selected as the best discriminant model. The accuracy of the calibration set and the prediction set were 95.52% and 93.71%, and the Kappa value were 0.9424 and 0.9156, respectively. The reverse spectral data of barley seeds of the validation set were used to verify the accuracy of the discriminant model and visualize the classification results. Finally, considering the practical application, the mixed spectral data containing different ratios of the reverse spectral data was analyzed, and satisfactory results were obtained. It can be concluded from this study that hyperspectral imaging technology was a very promising method for identification of barley seed varieties.Practical applicationsWith the circulation of the seed market, the traditional methods used for variety identification can no longer meet the needs of large‐scale, high‐quality production. As a nondestructive determination method, hyperspectral imaging technology combined machine vision and near‐infrared spectroscopy. In this study, hyperspectral imaging technology was used to identify barley seed varieties, and satisfactory results were obtained. It can provide a theoretical reference for future multispectral online detection technology.

Approximate composition analysis and nutritive values of different varieties of edible seeds

Background: The Dietary Guidelines for Americans (DGA) 2015-2020 supports that healthy eating patterns should include a variety of vegetables from all five of the following vegetable subgroups: dark green, red and orange, legumes, starchy, and others.
 Aims and Objective: To determine the approximate composition and nutritive values of edible portions of different varieties of popular seeds and to identify the heavy metals contents of these seeds.
 Materials and Methods: Five different seeds were collected from traditional supermarkets in Benghazi. Moisture and Ash contents in the samples were determined by A.O.A.C method. Total fat and the crude protein content in the seed sample were measured by using soxhlet extraction, and the Kjeldahl method of AOAC, respectively. The mineral content in seeds also determined by Atomic Absorption, spectrophotometer.
 Result: Five different seeds (pumpkin, sunflower, watermelon seeds, corn and chickpea) were analyzed for determination their protein, fat, energy and moister contents. The highest and signifi cant protein contents found in sunflower seeds 27.5% (p=0.001) whilst the lowest content was observed in corn. The highest fat and carbohydrate contents found in sunflower seeds and in the corn, 50%; 50% (P= 0.014) and (72.4%) (P=0.0005) respectively. In compared to other seeds, the moisture contents of pumpkin seeds presented the highest amount with signifi cant values (p=0.0001). The energy contents of sunflower seeds were the predominant value 626.28 kcal/100 g followed by both pumpkin seeds and watermelon seeds 591.2 and 585.89 kcal/100g respectively. The ash content of pumpkin seeds was approximately 5.87%. Furthermore, Pumpkin seeds had higher amounts of potassium 871 mg/100g, and watermelon seed was the highest sources of calcium (86 mg/100g) than other seeds. Magnesium, Iron and copper signifi cantly found higher in sunflower seeds.
 Conclusion: Overall seeds could be one of the good sources of food staple for macro and micronutrients, and may have health and economic benefi cial. Consumption of such seeds should be at recommended levels due to presences some quantities of lead and cadmium,which could have detrimental health effect.

Effect of Sprouting on the Physico-Chemical Properties of Mung Bean Seeds

The physico-chemical properties of seed are significant in designing equipment, marketing for evaluating seed quality. In this context, physico-chemical properties of three varieties of mung bean seeds, physical properties and germination properties during the sprouting period were evaluated. The average length, width and thickness were 4.64 mm, 3.64 mm and 3.26 mm at moisture content 10.70% on a dry weight basis. Hydration capacity ranged from 0.041 to 0.050 g/seed and hydration index ranged from 0.921 to 1.062, whereas swelling capacity ranged from 0.035 to 0.045 ml/seed and swelling index ranged from 0.927 to 1.447. Maximum sprout length and the germination rate were recorded in the variety SGC-20 at 96 h germination period as 45.56 mm and 96.67% respectively followed by the variety SGC-16 while IPM-02-3 reported lower sprout length and germination rate. Hence, the variety SGC-20 is best for consumption as sprouts among the three varieties.

The pathogenic mycobium in seeds of cultural plant varieties

The number phytopathogenic micromycetes is determined in the seeds of such cultivated varieties of cultural plant as soybeans, sunflowers, yellow mustard, buckwheat and thistle, which are grown by organic technology. It is shown that the number of micromycetes in the plant seeds differs significantly and ranges from 0.2 to 1.3 thousand NCO/g seeds. It depends on properties plants variety and hybrid, which are characterized by some certain set of physiological and biochemical characteristics that influences the formation seed mycobiome and it is quantitative composition. In the seeds varieties of these crops we identified such species of the phytopathogenic fungi as Alternaria alternate Fr., Fusarium oxysporum Schleht, Cladosporium herbarum Lket Gray, Botrytiscinerea Pers. Ex Fr., Ascochyta fagopyri Bres., Alternaria tenuissima (Kunze) Wiltshire, Aspergillus P. Micheliex Haller, Pénicillium Link. It was found that the species composition of phytopathogenic micromycetes in the seeds of soybean cultivar Kent and thistle Riches is much more diverse than the seeds other crops dominated by fungi A. alternate and F. oxysporum, which are characterized by different frequency of occurrence. These phytopathogenic fungi can cause plant diseases at different stages of ontogenesis, produce mycotoxins and reduce the quality of plant products. In the mycobiome of seeds buckwheat varieties Sophia, Sуn and sunflower hybrids Oscar and Oliver are dominated by fungi of the genus Pénicillium аnd Aspergillus (60–90%). The seeds affected by saprotrophic fungi can be reinfected during storage. This reduces its field and laboratory germination of the seeds. Saprotrophic fungi that dominate the seeds significantly impair its quality during storage and cause dangerous plant diseases in agrophytocenoses during the cultivation of this variety/hybrid. This requires the application of additional preventive protection measures of plants. Mycobioma mustard seeds of а yellow variety Ford represents a small number the phytopathogenic micromycetes. This may indicate its environmental safety in organic production. Thus, the analyzed research results indicate a significant differentiation in varieties species as to composition and number of phytopathogenic species of micromycetes in the seed mycobioma. Therefore, in order to avoid ecologic risks and biological contamination of agrocenoses, it is necessary to test the seeds, as on the density of the mycobiome and on the frequency of phytopathogenic micromycetes damage.

CHANGING AGRICULTURAL PRACTICES AND IT’S SOCIAL AND ENVIRONMENTAL INFLUENCES

Agricultural technology advancements are continuously taking place in India, as the progress of agricultural sector directly impacts a major proportion of population and its living condition. Farmers are interested to adopt new inventions and technologies in agriculture. Modern agricultural practices are significantly affecting human health and environment. The release of greenhouse gases such as carbon dioxide, methane and nitrous oxide are adversely affecting biodiversity and increasing air, water and soil pollution. Agricultural residue management, use of pesticides and insecticides, inorganic manure, chemical fertilizers leads to harmful effect on human health and increasing environmental pollution. Recent agriculture trends emphasizes on enhancing agricultural production in terms of quantity in less time, overlooking its adverse affects. In this paper we have analyzed the negative effects of modern agricultural practices on human health and environment. It leads to decline in soil fertility, loss of biodiversity, climate change, air, water and soil pollution, environmental degradation etc. Our farmers are now adopting modern agricultural techniques, using chemical fertilizers, pesticides, insecticides, expanding irrigation facilities, using high yielding varieties of seeds, modern machines, varying crop sequences etc. But these efforts of expanding food supply in less time is taking place at the cost of human health and environment degradation. Spray of harmful chemicals on crops not only pollutes underground water and air but also bad for human and animal health. Non harmonious, unwise and unsustainable agricultural practices have a considerable impact on environment and also harmful for living beings.

Autoregressive distributed lag (ARDL) approach to study the impact of climate change and other factors on rice production in South Korea

Abstract This study aims to explore the impact of climate change, technology, and agricultural policy on rice production in South Korea. In the presence of a long-run relationship among variables, the results show that an increase in CO2 emissions increases rice production by 0.15%. The mean temperature raises rice production by 1.16%. The rainfall has an adverse impact on rice production which shows improper irrigation systems and weather forecasting reports. Similarly, for technical factors, the area under rice and fertilizer used in the study has a direct effect on rice production. The study suggests that the Korean government needs to implement new policies and acquire advanced technology for weather forecasting. The concerned authorities need to inform rice growers about future weather and climate changes. We recommend that Korea needs to provide virgin arable undivided land to deserving rice growers based on ownership and/or lease for future food security. Finally, the study recommends that legislators should recommend policies for sustainable food security with the introduction of new agricultural technologies and subsidies, along with the provision of new varieties of seeds that can absorb the adverse shock of climate change and ensure a suitable amount of food.

Experimental studies to identify the influence of low power monochromatic optical radiation on the seeding qualities of cucumber seeds variety “Feniks+”

A further increase in the volume of cultivated and harvested agricultural products today depends not on the expansion of sown areas, but on scientific achievements aimed at increasing yields. The experimental study presents the results of studying the effect of low-power monochromatic optical radiation on the seeds of cucumbers of the “Fenisk+” variety. The research is based on the principles of refusal to use chemical fertilizers, the use of natural organic substances, and the creation of conditions for the growth and development of plants, identical to the conditions of their natural growth. There are various physical effects, including those based on the use of electrical energy and its transformation into light energy. Monochromatic optical radiation can be attributed to such effects. Based on the analysis of the experimental results, regression equations were obtained for the dependence of the average dry weight of cucumber seedlings on the wavelength of irradiation and exposure, and the optimal range of wavelengths of optical radiation was found: from 565 to 615 nm. At these wavelengths, the best results were obtained in terms of seed germination, the length of shoots and roots, as well as the dry weight of the vegetative part and roots. Based on the results obtained, it is possible to formulate the technological requirements for the design and development of a specialized electrotechnical installation using monochromatic optical radiation in agricultural production with the aim of presowing stimulation of seeds of such a vegetable crop as cucumbers.

Inspection of paddy seed varietal purity using machine vision and multivariate analysis

Abstract Seed varietal purity is vital to establish a uniform plant population. If the seeds are impure, it creates an unhealthy plant population that brings labor-intensive crop production. In this study, a rapid inspection method was established to classify the paddy seed based on varietal purity using a machine vision technique with multivariate analysis methods. Three varieties of paddy seeds were taken, namely - BR 11, BRRI dhan 28 and BRRI dhan 29. The individual paddy seed image was captured using an RGB camera with white LED lighting conditions in the laboratory. An image processing algorithm was developed for extracting 20 important features (seven color features, nine morphological features, and four textural features) from 375 paddy seed images. In the next step, the significant difference of extracted features data among the paddy varieties was studied using variance analysis. Also, the principal component analysis was performed to explore the separability of paddy seed varieties. Accordingly, the paddy seed variety classification models were developed for the combination of paddy varieties and selected feature data using partial least squares-discriminant analysis (PLS-DA), Support vector machine-classification (SVM-C) and K-Nearest Neighbors (KNN) algorithm. During model development, it was seen that the morphological image features were more significant compare to color and textural image features. The accuracy of 83.8%, 93.9%, and 87.2% was achieved using combined selected features of color, morphological, and textural for the PLS-DA, SVM-C, and KNN model, respectively. Finally, it was stated that the SVM-C algorithm with selected features of color, morphological, and textural could be used to classify the paddy seed variety.

Extraction, analysis of polyphenols and antioxidant properties of morrocan barley seed extracts (Hordeum vulgare L.)

This study investigated the effect of extraction method and the choice of solvent on the phenolic substance and antioxidant activity of certain varieties of grain seeds (Hordeum vulgare L.). In this ponder, three diverse solvents were used, specifically acetone, ethanol, and methanol, and three extraction methods were utilized to extract the phenolic substance ultrasound extraction, Soxhlet, and maceration. The levels of total phenols (TPC), total flavonoids (TFC) and proanthocyanidins (PA) were decided. The results appeared that diverse solvents of different polarity had a major impact on polyphenol content and antioxidant activity; the highest TPC (1.990 mg EG/g of dried extract), PA (1.628 mg EC/g of dried extract) were obtained with acetone, the results of TPC and PA were in this order: 70% acetone extract > 70% ethanol extract > 70% methanol extract and the highest TFC (2.204 mg EQ/g of dried extract) were obtained with methanol, the results of TFC were in this order: 70% methanol extract > 70% acetone extract ≈ 70% ethanol extract. However, different extraction methods gave comparable results. In vitro antioxidant activities were assessed utilizing the DPPH radical scavenging capacity, The lowest IC50 value reflects the highest antioxidant potency, acetone extract showed the greatest ability to scavenge DPPH free radicals with an IC50 of 2.013 mg/ml, 2.024 mg/ml, 2.635 mg/ml, 3.428 mg/ml respectively observed in the varieties MASSINE, LOCALE, CASAMENCE, AMALOU, these results show that barley seeds of the two-row type (MASSINE and LOCALE) have a higher antioxidant activity compared to the six-row type (CASAMENCE and AMALOU). Ultrasonic extraction was better for extracting antioxidant molecules from barley seeds in comparison to soxhlet and maceration.

In vitro radical scavenging activity of two varieties of pumpkin seeds

In vitro radical scavenging activity of two varieties of pumpkin seeds