Viral complexes in the Allium cepa L.- Frankliniella occidentalis P. interaction by DAS-ELISA in Baja California, Mexico

The onion (Allium cepa L.) is one of the main horticultural crops produced in Baja California, Mexico. In this crop, it has been observed presumptive viral symptoms, which are able to cause losses in yield and quality. Therefore, the objective of this study was to detect the associated virus in onion in high producing culture zones in Baja California. Plant material samples (symptomatic and asymptomatic) and trips insects were collected from commercial farming or areas. Commercial anti-serum were used for the detection of Iris yellow spot virus (IYSV), Tomato spot wilt virus (TSWV), Leek yellow spot virus (LYSV), Onion yellow dwarf virus (OYDV) and Garlic common latent virus (GarCLV). Seven indicator plants species were mechanically inoculated with onion sap (symptomatic and asymptomatic). The results showed the presence of IYSV, TSWV, OYDV and GarCLV in symptomatic onion plants. The plant samples showed a 77 % of incidence in the form of viral complexes and in a 23 % only the presence of LYSV was detected. The trips identified as Frankiniella occidentalis P. harbored IYSV, TSWV, LYSV, OYDV and GarCLV in the form of complexes in La Trinidad and San Quintin. The indicator plants did not show sympotoms of virosis. It is evident that F. occidentalis P. is responsible for the transmision of the analyzed viruses in this study in cultured onions. There are not previous reports for the detection of Orthotospovirus, Potyvirus and Carlavirus in Baja California onions.

EMPIRICAL CRITERIA FOR PHYTOMONITORING OF TECHNOGENIC LOAD IN DONBASS

From the data on the structural heterogeneity of indicator plants (Berteroa incana (L.) DC., Plantago major L., Reseda lutea L., Echium vulgare L., and Capsella bursa-pastoris (L.) Medik.) under unfavorable environmental conditions of Donbass selected their most informative characteristics for a general assessment of the level of anthropogenic load on local ecotopes. Empirical criteria were calculated as a result of correlation analysis between data sets on the content of heavy metals in soil samples and the values of phytoindication indices.

Using Visual Ozone Damage Scores and Spectroscopy to Quantify Soybean Responses to Background Ozone

Remotely-sensed identification of ozone stress in crops can allow for selection of ozone resistant genotypes, improving yields. This is critical as population, food demand, and background tropospheric ozone are projected to increase over the next several decades. Visual scores of common ozone damage have been used to identify ozone-stress in bio-indicator plants. This paper evaluates the use of a visual scoring metric of ozone damage applied to soybeans. The scoring of the leaves is then combined with hyperspectral data to identify spectral indices specific to ozone damage. Two genotypes of soybean, Dwight and Pana, that have shown different sensitivities to ozone, were grown and visually scored for ozone-specific damage on multiple dates throughout the growing season. Leaf reflectance, foliar biophysical properties, and yield data were collected. Additionally, ozone bio-indicator plants, snap beans, and common milkweed, were investigated with visual scores and hyperspectral leaf data for comparison. The normalized difference spectral index (NDSI) was used to identify the significant bands in the visible (VIS), near infrared (NIR), and shortwave infrared (SWIR) that best correlated with visual damage score when used in the index. Results were then compared to multiple well-established indices. Indices were also evaluated for correlation with seed and pod weight. The ozone damage scoring metric for soybeans evaluated in August had a coefficient of determination of 0.60 with end-of-season pod weight and a Pearson correlation coefficient greater than 0.6 for photosynthetic rate, stomatal conductance, and transpiration. NDSI [R558, R563] correlated best with visual scores of ozone damage in soybeans when evaluating data from all observation dates. These wavelengths were similar to those identified as most sensitive to visual damage in August when used in NDSI (560 nm, 563 nm). NDSI [R560, R563] in August had the highest coefficient of determination for individual pod weight (R2 = 0.64) and seed weight (R2 = 0.54) when compared against 21 well-established indices used for identification of pigment or photosynthetic stress in plants. When evaluating use of spectral bands in NDSI, longer wavelengths in SWIR were identified as more sensitive to ozone visual damage. Trends in the bands and biophysical properties of the soybeans combined with evaluation of ozone data indicate likely timing of significant ozone damage as after late-July for this season. This work has implications for better spectral detection of ozone stress in crops and could help with efforts to identify ozone tolerant varieties to increase future yield.

Automatic Grassland Degradation Estimation Using Deep Learning

Grassland degradation estimation is essential to prevent global land desertification and sandstorms. Typically, the key to such estimation is to measure the coverage of indicator plants. However, traditional methods of estimation rely heavily on human eyes and manual labor, thus inevitably leading to subjective results and high labor costs. In contrast, deep learning-based image segmentation algorithms are potentially capable of automatic assessment of the coverage of indicator plants. Nevertheless, a suitable image dataset comprising grassland images is not publicly available. To this end, we build an original Automatic Grassland Degradation Estimation Dataset (AGDE-Dataset), with a large number of grassland images captured from the wild. Based on AGDE-Dataset, we are able to propose a brand new scheme to automatically estimate grassland degradation, which mainly consists of two components. 1) Semantic segmentation: we design a deep neural network with an improved encoder-decoder structure to implement semantic segmentation of grassland images. In addition, we propose a novel Focal-Hinge Loss to alleviate the class imbalance of semantics in the training stage. 2) Degradation estimation: we provide the estimation of grassland degradation based on the results of semantic segmentation. Experimental results show that the proposed method achieves satisfactory accuracy in grassland degradation estimation.

The comparison of Cd, Cu, Fe, Mg, Mn, P, Pb, Zn concentrations in ash of the roots of some herbaceous plant species (Filipendula ulmaria, Carex species, Urtica dioica)

A common problem in biogeochemical mapping and contamination studies is that the same plant species are not available everywhere. Filipendula ulmaria is a widely used indicator plant but it does not grow in dry and high altitude areas. We used different plant species (F. ulmaria, Carex species and Urtica dioica) and analysed the concentrations of Cd, Cu, Fe, Mg, Mn, Pb, Zn and P in the material from 19 sampling points in eastern Estonia. The geometric mean concentrations of Pb, Cd and Zn were similar in F. ulmaria and Carex, as were the dominating ranges of Cu, Mn and Zn. The geometric mean concentrations typically differ between F. ulmaria and U. dioica. Simultaneous use of multiple indicator plants could generally not be recommended. Still, in case of urgent need the results could be amalgamated for the elements with more than 50% similarity of dominating ranges in different plants.

ENVIRONMENTAL PROBLEMS IN THE TERRITORIES WITH THE MINING INDUSTRY, AND ACTIVE REMEDIATION OF TOXIC SOILS

Реабилитация территорий загрязненных солями тяжелых металлов, весьма токсических, является актуальной фундаментальной и, одновременно, важнейшей прикладной экологической задачей. При этом особую роль играют физико-механические свойства грунтов-оснований объектов подобных загрязнений. В статье рассмотрен вопрос использования травосмесей для реабилитации или рекультивации соответствующих территорий. В связи с этим, необходимо отметить, что проблема эта, в частности, в фиторемедиации почв на настоящее время изучена недостаточно. Авторы предложили некоторые варианты применения таких видов растений, которые характеризуются способностью произрастать на загрязненных землях и, при этом, аккумулировать загрязнители надземной биомассой. В случае сильного загрязнения почв тяжелыми металлами, авторами предлагается в первый год рекультивации использовать однолетние растения с большой биомассой, способные за первый год вывести из биологического круговорота до 50% загрязнителей. Изучая растения на токсических почвах, определяли их аккумулирующие способности и использовали их как фитомелиорантов. В нескольких опытах использовали растения-индикаторы: амарант, клевер, люцерну, вязель, стевию, амброзию, рыжик озимый в смеси с однолетним видом клевера и другие, которые при накоплении максимальной биомассы запахивали в почву в смеси с цеолитсодержащими глинами местного значения. Результаты опытов показали, что с помощью растений-индикаторов можно не только улучшить плодородие почв, но и значительно снизить количество тяжелых металлов, нефтепродуктов, радионуклидов, остаточные явления химических средств борьбы с сорной растительностью, болезнями и вредителями. Большое значение в снижении токсичности почв имели и органические отходы сельскохозяйственного производства: кукурузные кочерыжки, корзинки подсолнечника, отходы спиртового производства – послеспиртовая барда, а также листовой опад, заделываемые в почву с биопрепаратами. Результаты опытов показали значительное снижение токсикантов в почве при использовании органических отходов и запашке растений в качестве зеленого удобрения в смеси с цеолитсодержащими глинами и биопрепаратами. Rehabilitation of territories contaminated with salts of heavy metals, very toxic, is an urgent fundamental and, at the same time, the most important applied environmental task. A special role is played by the physical and mechanical properties of soils- bases of objects of such pollution. The article deals with the use of grass mixtures for rehabilitation or recultivation of the respective territories. In this regard, it should be noted that this problem, in particular, in soil phytoremediation is currently insufficiently studied. The authors proposed some variants of the use of plant species, which are characterized by the ability to grow on contaminated land and, at the same time, accumulate pollutants above-ground biomass. In the case of heavy metal contamination of soils, the authors propose to use annual plants with large biomass in the first year of reclamation, capable of removing up to 50% of pollutants from the biological cycle. Studying plants on toxic soils, determined their accumulating capacity and used them as phytomeliorants. In several experiments, indicator plants were used: amaranth, clover, alfalfa, vyazel, stevia, ambrosia, winter ginger mixed with an annual clover species and others, which, when accumulating maximum biomass, were plowed into the soil in a mixture with zeolite-containing clays of local importance. The results of the experiments showed that with the help of indicator plants it is possible not only to improve soil fertility, but also to significantly reduce the amount of heavy metals, petroleum products, radionuclides, residual effects of chemical means of weed control, diseases and pests. Of great importance in reducing the toxicity of soils were organic waste of agricultural production: corn stalks, sunflower baskets, waste alcohol production-post-alcohol bard, as well as leaf litter, embedded in the soil with biological products. The results of the experiments showed a significant reduction of toxicants in the soil when using organic waste and plowing plants as a green fertilizer in a mixture with zeolite-containing clays and biopreparations.