Nondestructive Prediction of Isoflavones and Oligosaccharides in Intact Soybean Seed Using Fourier Transform Near-Infrared (FT-NIR) and Fourier Transform Infrared (FT-IR) Spectroscopic Techniques

The demand for rapid and nondestructive methods to determine chemical components in food and agricultural products is proliferating due to being beneficial for screening food quality. This research investigates the feasibility of Fourier transform near-infrared (FT-NIR) and Fourier transform infrared spectroscopy (FT-IR) to predict total as well as an individual type of isoflavones and oligosaccharides using intact soybean samples. A partial least square regression method was performed to develop models based on the spectral data of 310 soybean samples, which were synchronized to the reference values evaluated using a conventional assay. Furthermore, the obtained models were tested using soybean varieties not initially involved in the model construction. As a result, the best prediction models of FT-NIR were allowed to predict total isoflavones and oligosaccharides using intact seeds with acceptable performance (R2p: 0.80 and 0.72), which were slightly better than the model obtained based on FT-IR data (R2p: 0.73 and 0.70). The results also demonstrate the possibility of using FT-NIR to predict individual types of evaluated components, denoted by acceptable performance values of prediction model (R2p) of over 0.70. In addition, the result of the testing model proved the model’s performance by obtaining a similar R2 and error to the calibration model.

Soybean Yield Preharvest Prediction Based on Bean Pods and Leaves Image Recognition Using Deep Learning Neural Network Combined With GRNN

Soybean yield is a highly complex trait determined by multiple factors such as genotype, environment, and their interactions. The earlier the prediction during the growing season the better. Accurate soybean yield prediction is important for germplasm innovation and planting environment factor improvement. But until now, soybean yield has been determined by weight measurement manually after soybean plant harvest which is time-consuming, has high cost and low precision. This paper proposed a soybean yield in-field prediction method based on bean pods and leaves image recognition using a deep learning algorithm combined with a generalized regression neural network (GRNN). A faster region-convolutional neural network (Faster R-CNN), feature pyramid network (FPN), single shot multibox detector (SSD), and You Only Look Once (YOLOv3) were employed for bean pods recognition in which recognition precision and speed were 86.2, 89.8, 80.1, 87.4%, and 13 frames per second (FPS), 7 FPS, 24 FPS, and 39 FPS, respectively. Therefore, YOLOv3 was selected considering both recognition precision and speed. For enhancing detection performance, YOLOv3 was improved by changing IoU loss function, using the anchor frame clustering algorithm, and utilizing the partial neural network structure with which recognition precision increased to 90.3%. In order to improve soybean yield prediction precision, leaves were identified and counted, moreover, pods were further classified as single, double, treble, four, and five seeds types by improved YOLOv3 because each type seed weight varies. In addition, soybean seed number prediction models of each soybean planter were built using PLSR, BP, and GRNN with the input of different type pod numbers and leaf numbers with which prediction results were 96.24, 96.97, and 97.5%, respectively. Finally, the soybean yield of each planter was obtained by accumulating the weight of all soybean pod types and the average accuracy was up to 97.43%. The results show that it is feasible to predict the soybean yield of plants in situ with high precision by fusing the number of leaves and different type soybean pods recognized by a deep neural network combined with GRNN which can speed up germplasm innovation and planting environmental factor optimization.

Pengaruh priming terhadap vigor benih kedelai (Glycine max (L.) Merril.) yang dikecambahkan pada media dengan cekaman alumunium

Kandungan aluminium yang tinggi pada tanah Ultisol merupakan salah satu masalah utama dalam budidaya tanaman kedelai mulai dari fase perkecambahan hingga pertumbuhan tanaman. Perlakuan priming pada benih diyakini mampu memperbaiki perkecambahan pada lingkungan yang kurang menguntungkan. Penelitian dilakukan untuk mengetahui pengaruh priming pada perkecambahan benih kedelai yang dikecambahkan dalam media masam dan mengandung aluminium. Penelitian disusun dalam Rancangan Acak Lengkap (RAL) pola faktorial. Faktor pertama adalah jenis priming : tanpa priming, H2O (air), KNO3 1%, KNO3 2%, GA3 50 ppm, GA3 100 ppm, dan PEG 6000 7,5%. Faktor kedua adalah varietas kedelai yaitu: Anjasmoro, Burangrang, dan Grobogan. Data dianalisis sidik ragamnya dan dilanjutkan dengan uji Beda Nyata Jujur (BNJ) 5% menggunakan program statistika R Studio. Hasil penelitian menunjukkan priming PEG 7,5% dan varietas Burangrang secara mandiri merupakan perlakuan terbaik untuk meningkatkan vigor benih kedelai berdasarkan variabel waktu muncul kecambah, kecepatan perkecambahan, dan panjang hipokotil. Implikasi penelitian ini adalah PEG 7,5% dapat digunakan untuk perbaikan perkecambahan pada tanah masam dengan kandungan aluminium yang relatif tinggi. High aluminium content in Ultisol is the main problem in soybean cultivation from germination to planting growth phases.Priming treatment is believed to improve seed germination in a poor-growing environment. This study aimed to determine the effect of priming of soybean seeds germinated under acid medium and aluminium stress. The experimental design used was Completely Randomized Design (CRD) with factorial pattern. The first factor was priming type : no priming, H2O (water), 1% KNO3, 2% KNO3, 50 ppm GA3, 100 ppm GA3, and 7.5% PEG 6000. The second factor was soybean variety : Anjasmoro, Burangrang, and Grobogan. The data obtained were analyzed using the R Studio statistic program with a 5% HSD test. The study resulted that each PEG 7.5% priming and Burangrang variety independently was the best in increasing soybean seed vigor based on sprout time emergence, germination speed and hypocotyl length. This research implicates that PEG 7.5% can be used to improve seed germination on acid soils with high aluminium content.

Potential neuroprotective of trans-resveratrol a promising agent tempeh and soybean seed coats-derived against beta-amyloid neurotoxicity on primary culture of nerve cells induced by 2-methoxyethanol

Resveratrol, a natural polyphenol found in tempeh, has not been investigated especially in vitro as a neuroprotective agent against 2-methoxyethanol (2-ME)-induced beta-amyloid cytotoxicity. Beta amyloid peptides (Aβ) could initiate neurotoxic events and neuron-inflammatory response via microglial activation. However, it remains unknown whether the neurotoxic effect of beta-amyloid and/or associated with the potential of 2-ME to induce neurotoxic effects on primary culture of nerve cells induced by 2-ME. This study investigated potential neuroprotective of trans-resveratrol a promising agent tempeh and soybean seed coats-derived against beta-amyloid cytotoxicity on primary culture of nerve cells induced by 2-methoxyethanol. Biotium and MTT assays were used to analyze neurons, which were isolated from the cerebral cortex of fetal mice at gestation day 19 (GD-19). A standard solution of 2-methoxyethanol was dosed at 10 μL. The cultured cells were randomly divided into the following groups: (1) 2-ME group + resveratrol standard, (2) 2-ME group + resveratrol isolated from tempeh, (3) 2-ME group + resveratrol isolated from soybean seed coats, and (4) the control group, without the addition of either 2-ME or resveratrol. Exposure of the primary cortical neuron cells to beta-amyloid monoclonal antibody pre-incubated for 24 h with 10 µL of 4.2 µg/mL resveratrol and 7.5 mmol/l 2-methoxy-ethanol additions. Here, we report that the addition of 2-ME and resveratrol (standard and isolated from tempeh) of cell culture at concentrations of 1.4, 2.8 and 4.2 µg/mL showed that the majority of neurons grew well. In contrast, after exposure to 2-ME and Beta-amyloid, showed that glial activated. These findings demonstrate a role for resveratrol in neuroprotective-neurorescuing action.

Impact of Replacing Soybean Meal with Sunflower Meal, Sesame Meal, and Black Seed Meal in diets of Barki Lambs

Crude protein content in animal diet is considered the first important factor for nutritionists when they start to formulate a diet for different types of animals. Therefore, this experiment was conducted to investigate the effect of substituting soybean seed meal by different protein sources on lamb’s diet in terms of nutrients digestibility, and growth performance. Therefore, four tested concentrate feed mixtures (CFM, 14% crude protein) were designed. The CFM1 contained soybean meal as the only source of protein, and 50% of soybean meal protein was replaced by either sunflower meal, sesame seed meal, or black seed meal in CFM2, CFM3, and CFM4 groups, respectively. A total of 28 growing Barki male lambs aged 6 months with an average body weight of 38.6 ± 0.4 Kg were used in feeding trials for 120 days. Depending on their body weight, lambs were divided into four groups (7 animals in each). Each group fed on one of the experimental diets, including D1 (CFM1+ clover hay), D2 (CFM2 + clover hay), D3 (CFM3 + clover hay), and D4 (CFM4 + clover hay). Results of digestion coefficients indicted that the digestibility of crude protein and the nitrogen-free extract was significantly higher for D1 and D4, compared to D2 and D3. The same trend was observed in nutritive values expressed as total digestible nutrients (TDN) and digestible crude protein (DCP), whereas the D1 and D4 recorded higher TDN and DCP, compared to D2 and D3. Results of rumen parameters demonstrated that there were insignificant differences among groups regarding the average pH, ammonia (NH3-N), and total volatile fatty acids (TVFAs). Data of growth performance indicated that the final live body weight, total body gain, and average daily gain of lambs feed D4 (56.75 kg, 18.62 kg, and 155 g, respectively) and D1 (56.62 kg, 17.60 kg, and 147 g, respectively) were higher than those for lambs fed D2 (53.40 Kg, 14.64 kg, and 122 g, respectively) and D3 (53.11 kg, 14.61 kg, and 122 g, respectively). The feed conversion ratio (feed/gain) was recorded better value with lambs fed D4 followed by that fed D1. In conclusion, black seed meal could be replaced with the 50% of soybean meal participation of protein in growing Barki lambs’ diets without any adverse effects on digestibility, rumen kinetics, and growth performance.

EFFECT OF ELECTROSTATIC FIELD ON SOYBEAN SEED GERMINATION PARAMETARS

The aim of this study was to examine the influence of electrostatic fields on seed vigor, mean rate of germination and coefficient of velocity of germination of five soybean genotypes. Testing was conducted at the Novi Sad Institute of Field and Vegetable Crops on the seeds of five soybean varieties: Sava, NS 2024, NS 1347, NS 3127, and NS Blackstar. The seeds were exposed to different values of direct current (DC) of the following voltage: 0 V (control), 3 V, 6 V and 9 V, to which the seeds were exposed for 0 min (control), 1 min and 3 min. After exposing the seeds to the electric field, the vigour index (VI), mean rate of germination (MGR) and coefficient of velocity of germination (CVG). The results show that the effect of the electrostatic field on seed vigour, mean rate of germination and coefficient of velocity of germination depends on the genotype, voltage and exposure time. The application of DC can be a suitable method for improving vigour index (VI), mean rate of germination (MGR) and coefficient of velocity of germination (CVG). In addition, the results indicate that it is necessary to adjust the DC treatment (voltage and duration of exposure of seeds) to a particular genotype, since inadequate treatments may deteriorate the quality of seeds. Keywords: electrostatic field, vigor index, MGR, CVG, soybean

Symptoms of Damage to Soybean Varieties Due to Major Pest Attacks in South Sulawesi, Indonesia

South Sulawesi Province is one of the centers for soybean development in Indonesia. The varieties that are widely planted by farmers in South Sulawesi include Anjasmoro, Argomulyo, Grobogan, Gema, Dering-1, and Burangrang. These varieties have different levels of seed yield and damage levels. This paper aims to provide an overview and information about the types of soybean varieties, the level of pest damage, and the types of pests that cause damage to soybean varieties developed by farmers in South Sulawesi Province. The method used is to collect various information in the form of secondary data and primary data from research results related to soybean varieties, types of pests that damage soybean plants and the level of damage caused by soybean pests in South Sulawes. The results obtained provide information that the highest level of leaf damage caused by Spodoptera litura F. occurred in the Anjasmoro variety 10.94–32.69% followed by Argomulyo 10.16–26.17% and Grobogan 8.61–24.81%. The highest level of pod damage due to pod sucking was found in Burangrang varieties, namely 13.20%, Gema 12.51%, Dering 10.5%, Argomulyo 9.40%, Grobogan 8.50%, and Anjasmoro 7.70%. The level of fruit damage caused by the fruit borer Etiella zinckenella T., the highest occurred in Detam-1 15.71%, Ring 14.50%, Burangrang 10.60%, Gema 10.0%, Argomulyo 8.20%, Grobogan 7.10%, and Anjasmoro 6.70%. The rate of soybean yield loss caused by S. litura F. was the highest at Anjasmoro 8.97%–11.29%, then Grobogan 7.88–12.80%, and Argomulyo 6.77–14.90%. Meanwhile, the percentage of seed yield loss caused by the attack of the pest Nezara viridula L. ranged from 10.0–41.0% for all varieties. Likewise with Riptortus linearis F., the percentage of soybean seed loss caused ranged from 15 to 79% for all varieties.

Formation of plants density and seed yield of soybean varieties in Altai Krai

Relevance. Soybean (Glycine max (L.) Merrill is one of the most important protein- oilseed crops in world arable farming. An acute shortage of both food and feed protein is felt in many world’s countries. In this regard, the expansion of soybean seed production is relevant and is dictated by the need for import substitution of both food and feed soybean products.Materials and methods. In the research we studied the influence of two ecologically different cultivation zones: Priobskaya and Prialtaiskaya on the formation of plants density and seed yield of soybean. Three varieties Altom, Gratsia and Pripyat were taken as the objects of the research.Results. On average, over the years of research in full seedlings stage from 60 germinating seeds per square meter (600 thousand pieces/ha), in our experiment, about 56 plants were obtained per 1 m2 or 560 thousand plants per 1 hectare. This means that, on average, 93% of sown seeds give seedlings in field conditions. For harvesting after exposure of soybean crops to numerous biotic and abiotic factors, on average, there are about 52 plants per 1 m² or 520 thousand plants per 1 hectare, that is, 88% of the sown germinating seeds are saved for harvesting and give a yield. The maximum influence on the variability of plant density is exerted by vegetation conditions (years) – 37%. On average, over the years of the study, the maximum yield under Topchikha conditions was obtained in 2019 – 1.9 t/ha – in a year that was distinguished by not hot weather with sufficient rainfall during the growing season. Varieties Gratsia and Pripyat in Smolenskoye conditions significantly exceeded the standard in terms of yield in 2018 and 2020. On average, over the years of research, the Gratsia variety showed itself as more stable with Cv=11.3% in Topchikha conditions and Cv=9.8% in Smolenskoye conditions.