Correlation-Based Network Analysis of the Influence of Bemisia tabaci Feeding on Photosynthesis and Foliar Sugar and Starch Composition in Soybean

Bemisia tabaci (MEAM1) represents a species of economic importance in soybean. One of the obstacles to the management of B. tabaci is the quantification of damage by the pest because damage is indirectly inferred through losses in productivity. The objective of this study was to characterize the influence of B. tabaci feeding on soybean by assessing effects on photosynthetic parameters and the sugar and starch content of soybean leaves. The goal was to identify the optimal parameter to directly quantify pest damage on crop yield. Correlation networks were created among data on sugar content (fructose, glucose, and sucrose), starch and photosynthetic parameters (initial fluorescence, performance index on absorption basis, and turn-over number), and the number of nymphs at each of three infestations level (low, medium, and high) during both the vegetative and reproductive stage of the crop. In general, nymphs were more abundant during the vegetative stage. Starch content was strongly correlated with nymph density. A strong positive correlation was observed between fructose and nymph density during the vegetative stage. Among the photosynthetic parameters, the turn-over number N was positively correlated with nymph density at a low-infestation level and negatively correlated with nymphs when they occurred at a high-infestation level. B. tabaci feeding affected the plant’s physiology and its interaction is reflected in part by the relationships among photosynthetic parameters as well as the levels of sugars and starch. This understanding might be useful in developing better monitoring tools for pest management.

Anatomical features of conductive tissues of soybeans that prevent the penetration of pathogenic agents of bacterial blight into seeds

The ways of penetration of pathogenic bacteria from the infected vegetative parts of plants into soybean seeds remain practically unexplored. It is widely believed that soybean seeds are infected through the vascular system from already infected areas of the vegetative parts. The aim of the present research was to study the possibility of penetration of pathogens of bacterial blight into soybean seeds through the conductive tissues of plants. The studies were carried out in 2019–2021 in V.S. Pustovoit All-Russian Research Institute of Oil Crops on plants and seeds of soybean variety Vilana. It was found that the size of stomatal slots in soybean leaves is 8–12 µm. This ensures free penetration of bacteria with a diameter of 1.3–1.7 µm into the leaf mesophyll. The pore sizes of the sieve plates of the phloem range from 0.4–0.7 to 0.8–1.6 µm, depending on the age of the plants. The largest pores of the phloem sieve plates are comparable to the diameters of pathogenic bacteria. However, a large number of transverse sieve plates located in the vessels of the phloem every 0.05–0.1 mm will filter and partially retain bacteria in each sieve tube along the path of cell sap in the phloem. Therefore, the pathogenic bacteria passing through the entire phloem from leaves infected with bacteriosis up to pods is physically unlikely. In pods, the vascular system ends in the area of attachment of the placenta to the seed hilum. In the hilum, there are no conductive tissues, and the further flow of water and nutrients into the seed is carried out diffusely through the plasmodesma of cell walls. It was found that the anatomical structure of the soybean phloem prevents the free movement of pathogenic bacteria along the conductive system directly into the inner tissues of the seeds. Therefore, the hypothesis of infection of soybean seeds with pathogens of bacterial blight through the conducting system of the plant should be considered untenable

Effects of the Soil Moisture Content on the Superoxide Anion and Proline Contents in Soybean Leaves

Background: As an important source of feed protein, soybean is involved in the processing industry, food industry and other fields. Therefore, in recent years, the demand for soybean has increased and soybean planting areas have also increased. However, frequent droughts have a serious impact on soybean yield. Methods: During the flowering period, the soybean plants were subjected to drought treatments of different degrees (0-7 days without water). The superoxide anion and proline contents in the leaves were determined. Then, fitting curves were drawn between the soil moisture content and the superoxide anion and proline contents. Result: The effects of different soil moisture contents on the superoxide anion and proline contents in soybean leaves and the correlation between these contents were analyzed. According to the fitting curves, with a decrease in the volumetric water content of soil, the superoxide anion and proline contents in soybean leaves increased. The superoxide anion contents in drought-tolerant cultivars were significantly lower than those in drought-sensitive cultivars and the proline contents were significantly higher in drought-tolerant cultivars than those in drought-sensitive cultivars. The superoxide anion content in soybean leaves was positively correlated with the proline content in the soil volumetric water content range of 31.5% to 14.5%.

Optimizing the Experimental Method for Stomata-Profiling Automation of Soybean Leaves Based on Deep Learning

Stomatal observation and automatic stomatal detection are useful analyses of stomata for taxonomic, biological, physiological, and eco-physiological studies. We present a new clearing method for improved microscopic imaging of stomata in soybean followed by automated stomatal detection by deep learning. We tested eight clearing agent formulations based upon different ethanol and sodium hypochlorite (NaOCl) concentrations in order to improve the transparency in leaves. An optimal formulation—a 1:1 (v/v) mixture of 95% ethanol and NaOCl (6–14%)—produced better quality images of soybean stomata. Additionally, we evaluated fixatives and dehydrating agents and selected absolute ethanol for both fixation and dehydration. This is a good substitute for formaldehyde, which is more toxic to handle. Using imaging data from this clearing method, we developed an automatic stomatal detector using deep learning and improved a deep-learning algorithm that automatically analyzes stomata through an object detection model using YOLO. The YOLO deep-learning model successfully recognized stomata with high mAP (~0.99). A web-based interface is provided to apply the model of stomatal detection for any soybean data that makes use of the new clearing protocol.

Trophic Transfer without Biomagnification of Cadmium in a Soybean-Dodder Parasitic System

Cadmium (Cd) is among the most available and most toxic heavy metals taken up by plants from soil. Compared to the classic plant-animal food chains, the host-parasitic plant food chains have, thus far, been largely overlooked in the studies of Cd trophic transfer. To investigate the pattern of Cd transfer during the infection of parasitic plants on Cd-contaminated hosts, we conducted a controlled experiment that grew soybeans parasitized by Chinese dodders (Cuscuta chinensis) in soil with different levels of Cd treatment, and examined the concentration, accumulation, allocation and transfer coefficients of Cd within this parasitic system. Results showed that among all components, dodders accounted for more than 40% biomass of the whole system but had the lowest Cd concentration and accumulated the least amount of Cd. The transfer coefficient of Cd between soybean stems and dodders was much lower than 1, and was also significantly lower than that between soybean stems and soybean leaves. All these features were continuously strengthened with the increase of Cd treatment levels. The results suggested no evidence of Cd biomagnification in dodders parasitizing Cd-contaminated hosts, and implied that the Cd transfer from hosts to dodders may be a selective process.

Characterization of Molecular Properties and Expression of Gene GmPLMT and Its Effects on the Production of Lipid Metabolites in Soybean and Arabidopsis thaliana

Phospholipid N-methyltransferase (PLMT) plays an important role in the synthesis of phosphatidylcholine (PtdCho). The aim of this study was to characterize the molecular properties of GmPLMT and the expression of soybean GmPLMT and its effects on the production of lipid metabolites. Results showed that GmPLMT composed of mainly α-helix was a hydrophobic and transmembrane protein. In soybean leaves, GmPLMT was highly expressed during seedling and flowering stages. In transgenic Arabidopsis thaliana, the highest and lowest expression levels of GmPLMT were detected at flowering and maturity stages, respectively. The total phospholipid contents in soybean grains were decreased from 7.2% (35 days after flowering) to 4.8% (55 days after flowering) and then increased to 7.0% (75 days after flowering). The contents of PtdCho showed a similar pattern to that of total phospholipids. In transgenic A. thaliana seeds, the contents of total phospholipids and PtdCho were significantly increased. Significantly positive correlations were revealed between expression of GmPLMT and contents of both PtdCho and crude fats, and between the contents of PtdCho and both linoleic acid and linolenic acid, suggesting that increased expression of GmPLMT improved the production of lipid metabolites. This study provided solid experimental evidence for further improvement of soybean quality based on GmPLMT in the molecular breeding of soybeans.

Study of Rhizobia Impact on Nutritional Element Concentration in Legumes

The concentration of nitrogen in the Earth’s atmosphere is about 78%, but most plants are not able to acquire it directly from the atmosphere. One of the most common ways for binding atmospheric nitrogen is the development of an efficient symbiotic system between legumes and rhizobia. The aim of this study was to compare how different legumes and rhizobia symbiosis systems affect the concentrations of nutrients and other elements in soya and faba beans. Seeds of plants were inoculated with a preparation of rhizobia just before sowing. Plant samples were collected at the flowering stage (vegetative parts) and during harvest (seeds). Samples were air-dried and analysed with inductively coupled plasma mass spectrometry (ICP-MS). Total nitrogen and carbon concentrations were determined with an elemental analyser (EA). The obtained results showed that inoculation of legume plants with rhizobia not only affected nitrogen uptake by plants but also uptake of other elements. Inoculation had an effect on mineral element uptake for both faba bean and soybean leaves, where a significant increase in Mg, P, K, and Ca was observed. Treatment of legume plants with rhizobia caused a decrease of P and K concentrations in seeds, and there were changes in Fe and Mn concentrations.

A novel hyperspectral compressive sensing framework of plant leaves based on multiple arbitrary-shape regions of interest

Massive plant hyperspectral images (HSIs) result in huge storage space and put a heavy burden for the traditional data acquisition and compression technology. For plant leaf HSIs, useful plant information is located in multiple arbitrary-shape regions of interest (MAROIs), while the background usually does not contain useful information, which wastes a lot of storage resources. In this paper, a novel hyperspectral compressive sensing framework for plant leaves with MAROIs (HCSMAROI) is proposed to alleviate these problems. HCSMAROI only compresses and reconstructs MAROIs by discarding the background to achieve good reconstructed performance. But for different plant leaf HSIs, HCSMAROI has the potential to be applied in other HSIs. Firstly, spatial spectral decorrelation criterion (SSDC) is used to obtain the optimal band of plant leaf HSIs; Secondly, different leaf regions and background are distinguished by the mask image of the optimal band; Finally, in order to improve the compression efficiency, after discarding the background region the compressed sensing technology based on blocking and expansion is used to compress and reconstruct the MAROIs of plant leaves one by one. Experimental results of soybean leaves and tea leaves show that HCSMAROI can achieve 3.08 and 5.05 dB higher PSNR than those of blocking compressive sensing (BCS) at the sampling rate of 5%, respectively. The reconstructed spectra of HCSMAROI are especially closer to the original ones than that of BCS. Therefore, HCSMAROI can achieve significantly higher reconstructed performance than that of BCS. Moreover, HCSMAROI can provide a flexible way to compress and reconstruct different MAROIs with different sampling rates, while achieving good reconstruction performance in the spatial and spectral domains.

A Potential Role of Coumestrol in Soybean Leaf Senescence and Its Interaction With Phytohormones

Coumestrol is a natural organic compound synthesized in soy leaves and functions as a phytoalexin. The coumestrol levels in plants are reported to increase upon insect attack. This study investigates the correlation between coumestrol, senescence, and the effect of phytohormones on the coumestrol levels in soybean leaves. Our analysis involving high-performance liquid chromatography and 2-D gel electrophoresis indicated a significant difference in the biochemical composition of soybean leaves at various young and mature growth stages. Eight chemical compounds were specifically detected in young leaves (V1) only, whereas three different coumestans isotrifoliol, coumestrol, and phaseol were detected only in mature, yellow leaves of the R6 and R7 growth stage. MALDI-TOF-MS analysis was used to identify two proteins 3,9 -dihydroxypterocarpan 6A-monooxygenase (CYP93A1) and isoflavone reductase homolog 2 (IFR2) only in mature leaves, which are key components of the coumestrol biosynthetic pathway. This indicates that senescence in soybean is linked to the accumulation of coumestrol. Following the external application of coumestrol, the detached V1-stage young leaves turned yellow and showed an interesting development of roots at the base of the midrib. Additionally, the application of phytohormones, including SA, methyl jasmonate (MeJA), and ethephon alone and in various combinations induced yellowing within 5 days of the application with a concomitant significant increase in endogenous coumestrol accumulation. This was also accompanied by a significant increase in the expression of genes CYP81E28 (Gm08G089500), CYP81E22 (Gm16G149300), GmIFS1, and GmIFS2. These results indicate that various coumestans, especially coumestrol, accumulate during leaf maturity, or senescence in soybean.