Arable Soils Research Articles

Influence of the Type and Use of Soil on the Distribution of Organic Carbon and Other Soil Properties in a Sustainable and Resilient Agropolitan System

Urban and peri-urban agriculture is one of the strategies that emerged on the path towards agri-food sustainability in cities. This paper aims at improving the knowledge of the soil properties in a peri-urban area and their agricultural potential to support ecosystems with biodiversity worth conserving. The study area was located in the mid-plain of the Segura River (SE Spain). Arable soil layer samples were collected at 68 points to assess the distribution of organic carbon and to study other indicators of soil quality. A Wilcoxon and Kruskal–Wallis test was conducted to compare between the types of soils present in the area (calcaric Fluvisols and calcaric Regosols) and soil uses (industrial, cultivated and abandoned). Statistical analysis indicates that there are significant differences (at the 0.05 significance level) between Fluvisols and Regosols (p value = 3.65 × 10−5). Regarding use, the abandoned Fluvisols presented an average value of 9.33 g kg−1 of OC while the Fluvisols that are currently cultivated have a higher average content of OC (11.35 g kg−1). For soils under industrial use, the average OC content is 5.13 g kg−1. Spatial distribution of organic carbon in these soils depends on the type of soil and the human influence on them, including the use.

A spectrum contextual self-attention deep learning network for hyperspectral inversion of soil metals

The retrieval of heavy metal concentrations in naturally contaminated arable soils through hyperspectral reflectance has become increasingly significant in recent years. Presently, both conventional and deep learning-oriented metal inversion methodologies mandate the development of individualized models for each metallic element, while refraining from leveraging distant dependencies to attain the inherent heterogeneity unique to each metal species. This intricacy renders the attainment of precise inversion outcomes for particular heavy metal concentrations a formidable challenge. To tackle this challenge, the current study introduces the Spectrum Contextual Self-Attention Deep Learning Network (SCSANet), which is created to encompass long-range spectral context dependencies by employing a self-attention network. The model also includes efficient and precise spectral input techniques, as well as simultaneous output of multiple metals. Experiments are carried out in the study area to assess the precision of the proposed model in identifying lead (Pb), copper (Cu), cadmium (Cd), and mercury (Hg) concentrations. The findings reveal that metal inversion does not have a significant impact on pre-processed spectra, and enhancing the input technique of neighbourhood spectra can boost the accuracy of the inversion. The SCSANet model proposed herein achieves the highest inversion accuracy for metals with a similar magnitude of content, and outperforms the compared method in terms of inversion accuracy.

Localization of C Cycle Enzymes in Arable and Forest Phaeozems within Levels of Soil Microstructure.

Soil microbial and enzyme activities are closely related to the spatial variability of soil environmental conditions at the microscale (μm-mm). The origin and localization of the enzymes are somewhat neglected when the measured activity is used to evaluate specific soil functions. The activity of four hydrolytic enzymes (β-glucosidase, Cellobiohydrolase, Chitinase, Xylanase) and microbial diversity based on community-level physiological profiling were determined in samples of arable and native Phaeozems with increasing physical impact to soil solids. The level of impact on the soil solids had a significant effect on enzyme activity and depended on both the enzyme type and soil land use. The highest proportion of the activity of Xylanase and Cellobiohydrolase of arable Phaeozem was determined at the dispersion energy in the range of 450-650 J·mL-1 and was associated with the primary soil particles' hierarchy level. The highest proportions of β-glucosidase and Chitinase activities were determined for forest Phaeozem after applying energies lower than 150 J·mL-1 and characterizing the level of soil microaggregates. The increased activity of Xylanase and Cellobiohydrolase in primary soil particles of arable soil compared to those in forest soil might be a reflection of the substrates being unavailable to decomposition, leading to enzyme accumulation on the solid surface. For the Phaeozems, the lower the level of soil microstructure organization, the greater the differences observed between soils of different land use type, i.e., microbial communities, associated with lower microstructure levels, were more specific to land use type.

Application of plant extended phenotypes to manage the agricultural microbiome belowground

Plants have a surprising capacity to alter their environmental conditions to create adequate niches for survival and stress tolerance. This process of environmental transformation, commonly referred to as “extended phenotypes” or “niche construction”, has historically been studied in the domain of ecology, but this is a process that is pervasive across the plant kingdom. Furthermore, research is beginning to show that plants’ extended phenotypes shape the assembly and function of closely associated microbial communities. Incorporation and understanding the role that plant-extended phenotypes play in agriculture may offer novel, bioinspired methods to manage our arable soil microbiomes. Here, we review the challenges agriculture faces, the plant extended phenotypes we know to shape the microbiome, and the potential utilization of this knowledge to improve the environmental impact of agriculture. Understanding how plant extended phenotypes shape microbial communities could be a key to creating a sustainable future with both plants and microbiomes in consideration.

Влияние лесополос на валовое содержание Pb и Сd и их обменные соединения в черноземах выщелоченных

The creation of artificial forest belts is an effective method of land reclamation. Forest belts have a positive impact on prevention of erosion processes, formation of heat and moisture regimes, reduction of turbulent exchange in the surface air layer and reduction of carbon dioxide share in the atmosphere. An important feature of forest plantations is the prevention of soil contamination with heavy metals (HM). It occurs due to profile redistribution of HM and partial remediation of soils. The obtained data confirm this position. Reliable transformation of leached chernozems under the influence of different-age forest belts in comparison with arable soils on the territory of All-Russian Research Institute of Sugar Beet and Sugar named after A.L. Mazlumov was revealed. Forest vegetation type contributes to more sustainable ecosystems due to stabilization of humus content and its uniform distribution throughout the soil profile. Correlation analysis revealed a close relationship between content of humus, soil solution pH and the gross content, as well as the exchangeable compounds of HM. An increase in the concentration of HM in the upper layer of arable chernozem was revealed; it was caused by active emissions of exhaust gases from agricultural machinery and the application of mineral fertilizers. The design of forest belts in order to restore contaminated soils is planned in the territory of Sichuan Province (southwest China). This project needs additional research, which is planned to be carried out in the future.

In situ 15 N-N2 O site preference and O2 concentration dynamics disclose the complexity of N2 O production processes in agricultural soil.

Arable soil continues to be the dominant anthropogenic source of nitrous oxide (N2 O) emissions owing to application of nitrogen (N) fertilizers and manures across the world. Using laboratory and in situ studies to elucidate the key factors controlling soil N2 O emissions remains challenging due to the potential importance of multiple complex processes. We examined soil surface N2 O fluxes in an arable soil, combined with in situ high-frequency measurements of soil matrix oxygen (O2 ) and N2 O concentrations, in situ 15 N labeling, and N2 O 15 N site preference (SP). The in situ O2 concentration and further microcosm visualized spatiotemporal distribution of O2 both suggested that O2 dynamics were the proximal determining factor to matrix N2 O concentration and fluxes due to quick O2 depletion after N fertilization. Further SP analysis and in situ 15 N labeling experiment revealed that the main source for N2 O emissions was bacterial denitrification during the hot-wet summer with lower soil O2 concentration, while nitrification or fungal denitrification contributed about 50.0% to total emissions during the cold-dry winter with higher soil O2 concentration. The robust positive correlation between O2 concentration and SP values underpinned that the O2 dynamics were the key factor to differentiate the composite processes of N2 O production in in situ structured soil. Our findings deciphered the complexity of N2 O production processes in real field conditions, and suggest that O2 dynamics rather than stimulation of functional gene abundances play a key role in controlling soil N2 O production processes in undisturbed structure soils. Our results help to develop targeted N2 O mitigation measures and to improve process models for constraining global N2 O budget.

Response of soil bacterial populations to application of biosolids under short-term flooding

Biosolids are applied to agricultural land as a soil conditioner and source of crop nutrients. However, there is concern that bacteria from biosolids may become established in soils, particularly if that soil becomes water-logged. This study examined the microbial community of arable soils cultivated with barley under different applications of biosolids (0, 24t/ha, 48t/ha) in laboratory mesocosms which simulated a 10-day flood. Nutrients (P and N) and organic matter in the soil increased with application rate, but plant growth was not affected by biosolid application. The biosolids contained 10× more genetic material than the soil, with much lower bacterial diversity, yet application did not significantly change the taxonomy of the soil microbiome, with minor changes related to increased nutrients and SOM. Anaerobic conditions developed rapidly during flooding, causing shifts in the native soil microbiome. Some bacterial taxa that were highly abundant in biosolids had slightly increased relative abundance in amended soils during the flood. After flooding, soil bacterial populations returned to their pre-flood profiles, implying that the native microbial community is resilient to transient changes. The short-term changes in the microbiome of biosolid-amended soils during flooding do not appear to increase the environmental risk posed by biosolid application.

Organic carbon accumulation and microbial activities in arable soils after abandonment: A chronosequence study

Increased plant carbon (C) input into the soils after cropland abandonment results in not only C accumulation, but also higher microbial activities and consequently faster organic matter decomposition. We investigated the link between soil C accumulation and microbial properties in a chronosequence (0–65 years) of post-agricultural self-restoration of Luvisols - the dominating soil type worldwide. Microbial biomass carbon (MBC) and enzyme activities increased in the top soil (0–20 cm) during the 37-year period of self-restoration. Accumulation of microbial biomass was faster than of soil organic C at earlier stages of self-restoration (0–22 years) because of the fast microbial growth induced by labile litter components. The response of microbial activity was more sensitive to land use changes compared to that of soil organic C. Activities of enzymes responsible for C cycle increased more than that of nitrogen (N) and phosphorus (P) cycles at least up to 37 years after abandonment, indicating microbial adaptations to high input of litter with wide C/N and C/P ratios. Similarly, β-xylosidase was the solely enzyme which reached the activity similar to secondary forest soils after 65 years, due to the accumulation of recalcitrant C in litter with cropland abandonment age. The increased C demand was caused by the higher bacterial portion in soil microbial community (based on PLFA composition), which in turn, resulted in a lower microbial biomass C/N ratio. Enzyme stoichiometry revealed that microorganisms were limited by C and N in the topsoil during the self-restoration up to 37 years. Overall, the quantity and quality of plant C inputs, which changed with post-agricultural land restoration, regulated the microbial activity and enzyme production, offering a profound comprehension of ecosystem succession.

Pesticide Residues in French Soils: Occurrence, Risks, and Persistence.

Contamination of the environment by pesticide residues is a growing concern given their widespread presence in the environment and their effects on ecosystems. Only a few studies have addressed the occurrence of pesticides in soils, and their results highlighted the need for further research on the persistence and risks induced by those substances. We monitored 111 pesticide residues (48 fungicides, 36 herbicides, 25 insecticides and/or acaricides, and two safeners) in 47 soils sampled across France under various land uses (arable lands, vineyards, orchards, forests, grasslands, and brownfields). Pesticides were found in 98% of the sites (46 of the 47 sampled), including untreated areas such as organic fields, forests, grasslands, and brownfields, with up to 33 different substances detected in one sample, mostly fungicides and herbicides. The concentrations of herbicides were the highest in soils with glyphosate, and its transformation product, AMPA, contributed 70% of the cumulative herbicides. Risk assessment underlined a moderate to high risk for earthworms in arable soils mostly attributed to insecticides and/or acaricides. Finally, the comparison with pesticide application by farmers underlines the presence of some residues long after their supposed 90% degradation and at concentrations higher than predicted environmental concentrations, leading to questions their real persistence in soils.

Remediation of lead and cadmium co-contaminated mining soil by phosphate-functionalized biochar: Performance, mechanism, and microbial response

The remediation of heavy metals contaminated soils is of great significance for reducing their risk to human health. Here, pristine pinewood sawdust biochar (BC) and phosphate-functionalized biochar (PBC) were conducted to investigate their immobilization performance towards lead (Pb) and cadmium (Cd) in arable soils severely polluted by Pb (9240.5 mg kg−1) and Cd (10.71 mg kg−1) and microbial response in soils. Compared to pristine BC (2.6–12.1%), PBC was more effective in immobilizing Pb and Cd with an immobilization effectiveness of 45.2–96.2% after incubation of 60 days. Moreover, the labile Pb and Cd in soils were transformed to more stable species after addition of PBC, reducing their bioavailability. The immobilization mechanisms of Pb and Cd by PBC were mainly to facilitate the formation of stable phosphate precipitates e.g., Cd3(PO4)2, Cd5(PO4)3OH, Cd5H2(PO4)4‧4H2O, and pyromorphite-type minerals. Further, PBC increased pH, organic matter, cation exchange capacity, and available nutrients (phosphorus and potassium) in soils. High-throughput sequencing analysis of 16 S rRNA genes indicated that the diversity and composition of bacterial community responded to PBC addition due to PBC-induced changes in soil physicochemical properties, increasing the relative abundance of beneficial bacteria (e.g., Brevundimonas, Bacillus, and norank_f__chitinophagaceae) in the treated soils. What's more, these beneficial bacteria could not only facilitate Pb and Cd immobilization but also alter nutrient biogeochemical transformation (nitrogen and iron) in co-contaminated soils. Overall, PBC could be a promising material for immobilization of Pb and Cd and the simultaneous enhancement of soil quality and available nutrients in co-contaminated mining soils.

Source Analysis and Ecological Risk Assessment of Heavy Metals in the Arable Soil at the Geological High Background, Based on the Township Scale

Due to the extensive development of carbonate rocks in southwest China, heavy metals are naturally occurring elements that have high natural background levels in the environment. Therefore, it is important to conduct ecological risk assessments and identify potential sources of heavy metals in the geological high background area. Based on the township scale, a total of 307 surface soil samples were collected in Qinglong Town, Fengjie County, Chongqing. The concentrations of As, Cd, Cr, Cu, Hg, Ni, Pb, and Zn and pH were analyzed and determined. The spatial distribution and source of soil heavy metals were discussed using the geostatistical analysis and an absolute principal component score-multiple linear regression (APCS-MLR) model in the studied area. The results showed that the average values of seven heavy metals (As, Cd, Cr, Cu, Hg, Ni, and Zn) in the arable soil exceeded the background values of Chongqing, and the cumulative effect of Cd and As was obvious. The concentrations of Cd significantly exceededthe screening values in The Risk Control Standard for Soil Environmental Quality and Soil Pollution in Agricultural Land (GB 15618-2018), with the over-standard rates of 52.12%. The spatial characteristics of soil heavy metal contents exhibited a pattern of high in the south and low in the north. PCA and APCS-MLR modeling revealed that the contributions of natural sources to Cr, Cu, Ni, and Zn were 86.62%, 64.34%, 76.44%, and 85.46%, respectively. As, Pb, and Hg mainly derived from industrial activities, which accounted for 74.63%, 61.90%, and 73.49%, respectively, and Cd was affected by both natural sources and industrial activities (accounting for 47.74% and 39.56% of the total Cd content, respectively). The evaluation of the soil by the Nemerow comprehensive index (P) showed that Cd pollution was relatively serious, accounting for 27.04% of soil pollution. The potential ecological hazard index showed that Cd and Hg were the main ecological hazard elements, and the distribution range of RI was 51.77 to 2228, indicating mainly mild and moderate risks, and the moderate and above risk areas in the study area were mainly located around the southern industrial source area. Altogether, our results revealed that in the study area, the heavy metal pollution was mainly caused by industrial activities, and the heavy metal pollution caused by geological background was mainly light to moderate. In conclusion, the medium and above risk areas in the study area were mainly caused by mineral and industrial activities, whereas the heavy metal pollution caused by geological background was mainly light to moderate pollution.

New insight into the soil bacterial and fungal microbiome after phosphorus biofertilizer application as an important driver of regenerative agriculture including biodiversity loss reversal and soil health restoration

At present, the exploitation of biofertilizers is revealing the vast potential for the advancement of sustainable and organic agriculture and the improvement of arable soil quality. Therefore, we investigated the capacity of an innovative phosphorus biofertilizer to enhance the activity and diversity of the soil microbiome inhabiting chemically degraded soil (type Abruptic Luvisol). The two-year field experiment comprised a control treatment (FC) devoid of microbial enrichment, an optimal dose of fertilizer containing beneficial microorganisms (FA100) and a dose of fertilizer that was 40 % below this optimal level and contained microorganisms (FA60). Phosphorus biofertilizer increased soil enzymatic activity immediately after application and between the corresponding treatments in subsequent sampling times, it alleviated the effects of metabolic stress, improved phytoavailable phosphorus content and increased maize yield. Identification based on the terminal restriction fragments size revealed the presence of microorganisms important for soil health such as phosphorus solubilizers, nitrogen fixers, biological control agents, entomopathogens, mycorrhizal fungi, bioremediators and plant growth promoters. Next Generation Sequencing (NGS) showed that the application of phosphorus biofertilizer changed the relative abundance of different microbial phyla, classes and orders, increased the diversity of soil microorganisms and indicated that the composition of the soil microbiome was also dependent on the sampling time. The prediction of bacterial community function using PICRUSt demonstrated that the application of biofertilizer raised the number of functional sequences associated with metabolism and cell processes, including phosphorus compound pathways. FUNGuild showed that saprotrophic and symbiotrophic fungi were more abundant in microbiologically enriched treatments. Our results proved that the phosphorus biofertilizer used offers a sustainable and promising solution to the problem of reducing traditional mineral fertilizer inputs while ensuring soil microorganism welfare and enhancing land productivity, and, what is more, it can be effectively exploited in regenerative agriculture and as a factor used to enhance resilience to climate change.

A new sample preparation approach for the analysis of 98 current-use pesticides in soil and herbaceous vegetation using HPLC-MS/MS in combination with an acetonitrile-based extraction

A simple acetonitrile-based extraction method for the determination of 98 current-use pesticides (CUPs) in soil and herbaceous vegetation using HPLC-ESI-MS/MS is reported. The method was optimized in terms of extraction time, buffer (ammonium formate) ratio, and graphitized carbon black (GCB) ratio for the clean-up of vegetation. The validated method yielded accuracy in terms of percentage recovery of 71–125% (soil) and 70–117% (vegetation) for the majority of 98 CUPs. The precision in terms of relative standard deviation was at 1–14% (soil), and 1–13% (vegetation). Matrix-matched calibration curves exhibited good linearities (R2 > 0.99). The limits of quantitation ranged between 0.008 and 21.5 μg kg−1 in soil and vegetation. The reported method was applied to soils and vegetation from 13 agricultural sites across Germany. Overall, 44 of the 98 common CUPs were detected in our samples and the qualitative load is well above the average for arable soils in the EU.

Earthworm ecotype diversity mitigates resource limitations of microbial community in arable soils

Resource limitation hinders soil biota to sustain multiple ecosystem functions. Earthworms are known for their ecotype diversity and the ability to accelerate nutrient cycling. However, the roles of earthworm ecotype diversity in alleviating soil resource limitations have yet to be discovered. Here, we conducted a microcosm study to investigate whether the increase of earthworm ecotypes, including epigeic Eisenia foetida, endogeic Metaphire guillelmi, and epi-endogeic Amynthas corticis, could promote soil nutrient provision by stimulating soil microbial communities. Earthworm ecotype diversity resulted in greater phosphorus contents than the earthworm inoculated alone, which were associated with increased fungal richness and network complexity. The result suggests that the increase of earthworm ecotype diversity drives the fungi-based micro-food web. Further, the alternations of extracellular enzymes related to nitrogen and phosphorus hydrolysis are also coupled with the richness, community composition, and network topology of fungi rather than those of bacteria, suggesting the more predominant effects of fungi in mediating extracellular enzymes. Thus, the increase of earthworm ecotype diversity could alleviate the resource limitation by steering fungal communities to excrete more hydrolysis enzymes. Our findings shed new light on the essential roles of earthworm ecotype diversity in strengthening microbiome-mediated functions in resource limited environments.

Ecological risk assessment of potentially toxic elements in selenium-rich soil with different land-use types.

Dashan Village area is one of the representative areas in China with high selenium concentration in the natural environment. A total of 133 topsoil samples have been collected in the Dashan Village area to explore the potential toxic elements (PTEs) background concentrations in soils under different land-use types for a comprehensive PTEs risk assessment (arsenic, cadmium, chromium, copper, mercury, nickel, lead, selenium and zinc). The results show that the geometric mean concentrations of As, Cr, Cu, Hg, Ni, Pb, Se and Zn found in the soil of the Dashan Village area were lower than the control standard for soil contamination risk in agricultural land. However, the geometric mean concentrations of Cd exceeded their corresponding standard values. For different land-use types, geometric mean concentrations of As, Cd, Cu, Hg, Ni and Pb in the arable soils were higher than in woodland soils and tea garden soils. Based on the potential ecological risk assessment, the woodland, arable and tea garden were at low-risk levels. Cadmium posed the highest ecological risk, while the other PTEs were of low risk in soils. Multiple statistical analyses and geostatistical analysis indicated that the concentrations of Cr, Ni, Pb, Cu, Zn and Se originated mainly from natural sources, while the concentrations of Cd, As and Hg could be influenced by anthropogenic activities. These results provide scientific support for the safe utilization and ecological sustainability of selenium-rich land resources.

Using a variety of machine learning approaches to predict and map topsoil pH of arable land on a regional scale

AbstractIn order to accurately predict soil properties, various machine learning (ML) approaches and hybrid models constructed by integrating ML into regression kriging framework were used to predict and map arable land topsoil pH in Henan province, central China. Random forest (RF), cubist (Cu), support vector machine, artificial neural network, multiple linear regression, classification and regression trees (CART) and their hybrid models were compared for pH accuracy prediction. Among all standalone ML models, RF had the best predictive performance, in terms of the metrics employed in this study, followed by Cu, and CART was the worst. Compared with their ML counterparts, hybrid models could improve the accuracy of topsoil pH prediction to various extents. The accuracy improvement of the hybrid models constructed based on the simple ML was much greater than that based on the complex ensemble ML. Except for artificial neural network kriging , there was no significant difference between different hybrid models in the predicted results of topsoil pH. The outputs from the best predictive models showed that weak acidic soils and weak alkaline soils were the dominant arable soils in the study region, accounting for more than 30% and more than 50% of the total arable land area respectively, the topsoil pH of arable land in the north of the study area is generally higher than that in the south. Boruta variable selection revealed that altitude, climatic covariates closely related to soil moisture availability and some soil properties were the most critical factors affecting and controlling the topsoil pH of arable land.

Glyphosate Effects on Some Characteristics of Biological Activity and Phytotoxicity of Sod-Podzolic Soil in a Short-Term Model Experiment

In a model laboratory experiment on infertile arable soil with low biological activity, it was found that the introduction of glyphosate leads to a short-term change in the intensity of the main processes of microbial transformation of nitrogen in the soil. When incubating soil with glyphosate at the maximum recommended dose of 8 l/ha for 22 days, there is an increase in nitrogen-fixing and denitrifying activity by 30–80% and 300% and a decrease in the nitrification process by 20–40%. The effects are of a short-term nature and do not reflect the entire complex of ongoing microbiological processes: no effect of glyphosate was detected on the emission of CO2, which is an integral indicator of biological activity. At the end of incubation in the soil with the introduced glyphosate, there was an increase in the number of bacteria by 40% and a decrease in the number of micromycetes by 70%. In general, under the selected conditions, the introduction of glyphosate led to a marked deterioration in the biological activity of the soil. By the method of multisubstrate testing, it was shown that under the action of the herbicide there is an increase in the value of the coefficient of rank diversity of the consumption spectra of substrates d, accompanied by a decrease in the specific metabolic work W and the integral vitality index G. It was shown for the first time that when glyphosate is introduced into soil with low biological activity and availability of phosphorus and the herbicide is degraded along the sarcosine pathway with a break in the C–P bond, excluding the formation of toxic metabolites, there is a pronounced negative effect of glyphosate on soil microorganisms, which leads to inhibition of wheat plant growth.

COTTON ADVANCED LINES ASSESSMENT IN THE SOUTHERN REGION OF KAZAKHSTAN

The Turkestan region is a cotton-growing zone in South Kazakhstan, but also the northernmost cotton-growing area in the world. Annually, medium-staple cotton (Gossypium hirsutum L.) cultivation occurs on 115,000–125,000 ha, with 80,000–85,000 ha grown in the Districts of Maktaaral and Zhetysay, Kazakhstan. This region is highly susceptible to salinity, drought, invasion of dangerous pests (cotton budworm, beet borer, spider mites, and aphids), and diseases (fusarium blight [wilt] and gummosis). An extremely high salt content and aridity in the arable soil are the main limiting factors of that region, hence, genotype selection through genetic principles is the most effective and economical way to reduce their negative impacts on vegetation. Therefore, the research on developing resistant cotton cultivars suitable for such soil and climatic conditions is most relevant. Considering the above situation, assessment of newly developed high-yielding cotton cultivars with fiber quality of types III–IV for tolerance to heat and drought, salinization, and pests and diseases ensued during 2019, 2020, and 2021 at the Agricultural Experimental Station of Cotton and Melon Growing, Atakent, Kazakhstan. Their promising cotton genotypes resulted from strains developed through intraspecific and interspecific diallel hybridization. The newly developed eight cotton cultivars, grown on more than 92% of the hectarage in the Southern region of Kazakhstan, are PA-3031, PA-3044, M-4005, M-4007, M-4011, Bereke-07, Myrzashol-80, and M-4017.

Effect of Microbial Preparation and Biomass Incorporation on Soil Biological and Chemical Properties

In order to meet the global nutritional needs of a growing population, attempts are being made to develop strategies that can effectively offset the negative effects of intensive farming. The aim of this study was to investigate the effect of Effective Microorganisms (EM) preparation and organic matter incorporation on the soil microbiological and chemical features. The analyses included the number of heterotrophic bacteria, fungi, actinobacteria, cellulolytic, amylolytic and proteolytic microorganisms, and bacteria of the genus Azotobacter. The content of organic carbon, the total and mineral nitrogen forms of phosphorus, potassium, magnesium, and the pH were also determined. The application of an EM of higher dose combined with the manure and straw resulted in the highest abundance of heterotrophic bacteria (165.1 × 106 cfu g−1), actinobacteria (43.2 × 105 cfu g−1), cellulolytic (17.2 × 106 cfu g−1), and proteolytic bacteria (82.0 × 106 cfu g−1). The highest content of chemical parameters was always observed in the experimental variant, including biomass incorporation, accompanied by EM use. The novelty of our research is the analysis of the synergistic effect of the experimental factors studied on the microbiological and chemical parameters of arable soils.

Extracts and Residues of Common Ragweed (Ambrosia artemisiifolia L.) Cause Alterations in Root and Shoot Growth of Crops.

Following the novel weapon hypothesis, the invasiveness of non-native species, such as common ragweed (Ambrosia artemisiifolia L.) can result from a loss of natural competitors due to the production of chemical compounds, which negatively affect native communities. Particularly the genus Ambrosia produces several types of organic compounds, which have the potential to inhibit germination and growth of other plants. Subsequent to an assessment of the chemical content of three different ragweed extracts (aqueous shoot and root extracts, as well as essential oil), two different trials on the effects of different concentrations of these extracts, as well as ragweed residues, were conducted on two different mediums (Petri dish vs. soil). In addition, we investigated the impact on the infection potential of Bradyrhizobium japonicum on soybean roots in three different soil types (arable soil, potting soil, and sand). The results showed that the exposure to common ragweed extracts and residues induced changes in the biomass and root production of crops and ragweed itself. Even though crops and ragweed differed in their response behavior, the strongest negative impact on all crops and ragweed was observed with ragweed residues, leading to reductions in biomass and root growth of up to 90%. Furthermore, we found a decrease in the number of rhizobial nodules of up to 48% when soybean was exposed to ragweed root extract.