Общая методика и результаты наземных гиперспектральных исследований сезонного изменения отражательных свойств посевов сельскохозяйственных культур и отдельных видов сорных растений р. Ю. данилов 1 , о. Ю. кремнева 1 , в. я. исмаилов 1 , в. а. третьяков 2 , а. а. ризванов 2 , в. в. кривошеин 2 , а. а. пачкин 1
The accurate recognition of weeds on crops supports the spot application of herbicides, the high economic effect and reduction of pesticide pressure on agrocenoses. We consider the approach based on the quantitative spectral characteristics of plant objects to be the most appropriate for the development of methods for the spot application of herbicides. We made test plots with different species composition of cultivated and weed plants on the experimental fields of the scientific crop rotation of the Federal Research Center of Biological Plant Protection. These plants form the basis of the agrocenoses of Krasnodar Krai. Our primary subjects are sunflower crops (Helianthus annuus L.), corn (Zea mais L.) and soybean (Glycine max (L.)). Besides the test plots, pure and mixed backgrounds of weeds were identified, represented by the following species: ragweed (Ambrosia artemisiifolia L.), California-bur (Xanthium strumarium L.), red-root amaranth (Amaranthus retroflexus L.), white marrow (C. album L.) and field milk thistle (Sonchus arvensis L.). We used the Ocean Optics Maya 2000-Pro automated spectrometer to conduct high-precision ground-based spectrometric measurements of selected plants. We calculated the values of 15 generally accepted spectral index dependencies based on data processing from ground hyperspectral measurements of cultivated and weed plants. They aided in evaluating certain vegetation parameters. Factor analysis determined the relationship structure of variable values of hyperspectral vegetation indices into individual factor patterns. The analysis of variance assessed the information content of the indicators of index values within the limits of the selected factors. We concluded that most of the plant objects under consideration are characterized by the homogeneity of signs according to the values of the index indicators that make up the selected factors. However, in most of the cases, it is possible to identify different plant backgrounds, both by the values of individual vegetation indices and by generalized factorial coefficients. Our research results are important for the validation of remote aerospace observations using multispectral and hyperspectral instruments.
We aimed to monitor the species diversity and the dynamics of the number of soybean pests using light traps with an original design to develop protection systems against the main phytophages. Traps lured 44 species of insects from eight orders and 27 families. The capture of 15 species of economically important phytophages was recorded—representatives of various orders and families: order Lepidoptera—Noctuidae, Crambidae, Erebidae, and Geometridae; order Hemiptera—Flatidae; order Coleoptera—Elateridae, etc. Insect identification was carried out via morphological methods. Over the study period (93 days), 4955.41 insect specimens were caught on average per one trap. Most of the attracted insects belong to harmful entomofauna: namely the cotton bollworm (Helicoverpa armigera, Hübner)—58.9%, the beet webworm (Loxostege sticticalis, L.)—12.74%, the nutmeg moth (Anarta trifolii, Hufnagel)—6.5%, the European corn borer (Ostrinia nubilalis, Hübner)—2.68%, and some other species—19.2%. In addition to economically significant phytophages, we registered some indifferent and beneficial species. The summer dynamics of the cotton bollworm and the nutmeg moth were obtained for the entire research period. Then, we calculated the values of the indices of biodiversity and the dominance of insect species. An analysis of the index values allows us to conclude a balanced entomocomplex at the research site.
The North Caucasus region in its natural and climatic conditions is a zone favorable for the cultivation of corn in Russia. Significant damage to corn plantings and crop quality is caused by a variety of pests. In connection with the annual crop losses caused by harmful insects, the development of methods for their monitoring and capture are relevant. The efficiency test of two designs of light traps based on super bright LEDs (conical and aspiration) was performed. As a result of the experiment, which lasted for two weeks, more than 260 thousand specimens of insects belonging to 8 orders and 27 families were captured. The traps were most attractive for the representatives of the coleoptera, the proportion of which was 97.5%. Traps were also highly effective in relation to Lepidoptera (1%) and Hemoptera (1.4%). Representatives of other taxa were caught in much smaller quantities; their total share was less than 0.1% of the total. The use of test traps showed their high efficiency for the elimination of the main lepidopteran maize pests - Helicoverpa armigera Hbn. and Ostrinia nubilalis Hbn., which allows them to be used not only for monitoring but also for plant protection. The low attractiveness of traps for Hymenoptera was also revealed, which allows combining their use in the system with the use of entomophages. A comparative assessment of the effectiveness of attracting insects with various designs of light traps in the corn agrocenosis showed the absence of significant differences in species diversity and mathematically significant differences in the number of attracted insects: the conical trap was almost two times more effective.
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