. Soil aggregate stability is crucial for maintaining the arrangement of solid particles and pore space in the soil, even under mechanical stresses. Traditional direct measurements of soil aggregate stability are time-consuming and expensive. This study aimed to spatially predict the soil aggregate stability indices, including the mean weight diameter of aggregates, the geometric mean diameter of aggregates, and the percentage of water stable aggregates, using five machine learning models and environmental covariates in the framework of digital soil mapping. A total of 100 samples were collected from the surface layer (0-15 cm) of soils in the Aji-Chai watershed, northwestern Iran, and their SAS indices were determined by standard laboratory methods. Four scenarios (S) were employed to evaluate the most influencing auxiliary variables, including (S 1 ): topographic attributes, (S 2 ): topographic attributes + remote sensing data, (S 3 ): S 2 + thematic maps (geology, land use/cover maps), and (S 4 ): S 3 + selected soil properties. Among the various machine learning models, the random forest showed exceptional performance and reduced uncertainty for S 4 , compared to the other machine learning models and desired scenarios. The coefficient of deter - mination, concordance correlation coefficient, and normalized root mean squared error values of the random forest model were 0.86, 0.87, and 31.42% for mean weight diameter; 0.80, 0.84, and 31.59% for geometric mean diameter; and 0.54, 0.68, and 20.75% for water stable aggregates, respectively. Additionally, properties such as soil organic matter and clay, followed by remote sensing data, demonstrated the highest relative importance when compared to the other covariates in predicting the soil aggregate stability indices. In conclusion, the random forest ML-based model seems to be able to accurately predict soil aggregate stability indices at the watershed scale. The generated maps can serve as a valuable baseline for land use planning and decision-making. These findings contribute to the scientific understanding of soil physical quality indicators and their application in sustainable land management practices.
.即使在机械应力的作用下，土壤集料的稳定性对于保持土壤中固体颗粒和孔隙的排列也至关重要。传统的土壤集料稳定性直接测量耗时且昂贵。本研究旨在数字土壤制图框架下，利用五种机器学习模型和环境协变量，从空间上预测土壤团聚体稳定性指数，包括团聚体平均重量直径、团聚体几何平均直径和水稳定团聚体百分比。从伊朗西北部阿吉-柴流域的土壤表层（0-15 厘米）共采集了 100 个样本，并通过标准实验室方法测定了其 SAS 指数。采用四种方案（S）来评估影响最大的辅助变量，包括（S 1）：地形属性；（S 2）：地形属性 + 遥感数据；（S 3）：S 2 + 专题地图（地理信息系统）：S 2 + 专题地图（地质、土地利用/覆盖图），以及 (S 4 )：S 3 + 选定的土壤特性。在各种机器学习模型中，与其他机器学习模型和理想方案相比，随机森林在 S 4 方面表现出卓越的性能，并降低了不确定性。随机森林模型的判定系数、一致性相关系数和归一化均方根误差值分别为：平均重量直径 0.86%、0.87% 和 31.42%；几何平均直径 0.80%、0.84% 和 31.59%；水稳定团聚体 0.54%、0.68% 和 20.75%。此外，在预测土壤团聚体稳定性指数方面，与其他协变量相比，土壤有机质和粘土等属性的相对重要性最高，其次是遥感数据。总之，基于随机森林 ML 的模型似乎能够准确预测流域尺度的土壤团聚体稳定性指数。生成的地图可作为土地利用规划和决策的宝贵基准。这些发现有助于科学理解土壤物理质量指标及其在可持续土地管理实践中的应用。
{"title":"Machine learning-based soil aggregation assessment under four scenarios in northwestern Iran","authors":"Parastoo Nazeri, S. Ayoubi, Hossein Khademi, Farideh Abbaszadeh Afshar, Rouhollah Mousavi","doi":"10.31545/intagr/188506","DOIUrl":"https://doi.org/10.31545/intagr/188506","url":null,"abstract":". Soil aggregate stability is crucial for maintaining the arrangement of solid particles and pore space in the soil, even under mechanical stresses. Traditional direct measurements of soil aggregate stability are time-consuming and expensive. This study aimed to spatially predict the soil aggregate stability indices, including the mean weight diameter of aggregates, the geometric mean diameter of aggregates, and the percentage of water stable aggregates, using five machine learning models and environmental covariates in the framework of digital soil mapping. A total of 100 samples were collected from the surface layer (0-15 cm) of soils in the Aji-Chai watershed, northwestern Iran, and their SAS indices were determined by standard laboratory methods. Four scenarios (S) were employed to evaluate the most influencing auxiliary variables, including (S 1 ): topographic attributes, (S 2 ): topographic attributes + remote sensing data, (S 3 ): S 2 + thematic maps (geology, land use/cover maps), and (S 4 ): S 3 + selected soil properties. Among the various machine learning models, the random forest showed exceptional performance and reduced uncertainty for S 4 , compared to the other machine learning models and desired scenarios. The coefficient of deter - mination, concordance correlation coefficient, and normalized root mean squared error values of the random forest model were 0.86, 0.87, and 31.42% for mean weight diameter; 0.80, 0.84, and 31.59% for geometric mean diameter; and 0.54, 0.68, and 20.75% for water stable aggregates, respectively. Additionally, properties such as soil organic matter and clay, followed by remote sensing data, demonstrated the highest relative importance when compared to the other covariates in predicting the soil aggregate stability indices. In conclusion, the random forest ML-based model seems to be able to accurately predict soil aggregate stability indices at the watershed scale. The generated maps can serve as a valuable baseline for land use planning and decision-making. These findings contribute to the scientific understanding of soil physical quality indicators and their application in sustainable land management practices.","PeriodicalId":13959,"journal":{"name":"International Agrophysics","volume":null,"pages":null},"PeriodicalIF":2.0,"publicationDate":"2024-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141664965","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Gholamhossein Shahgholi, Ehsan Aghdamifar, Abdolmajid Moinfar, M. Szymanek, Wojciech Tanaś
. In order to determine the relationships between the soil stiffness constants of cohesive modulus of deformation, friction modulus of deformation and soil constant value and the rolling resistance, a series of tests was conducted using two types of loam and clay loam soil textures at four moisture contents of 10, 20, 30 and 40% and five loading speeds of 1, 2, 3, 4 and 5 mm s –1 . The results showed that all of the independent fac - tors had a significant effect on the soil stiffness constants, so with increases in moisture content and loading speed, the soil stiffness constants of cohesive modulus of deformation, friction modulus of deformation and soil constant value varied significantly. The highest cohesive modulus of deformation and friction modulus of deformation values were obtained at a moisture content of 10% and loading speed of 5 mm s –1 in a clay loam soil. All param - eters were significant in calculating the rolling resistance using Bekkers’ relationship. With increases in soil moisture content, the rolling resistance increased, while increasing the loading speed reduced the rolling resistance significantly. In general, the highest rolling resistance value of 16 887.1 N was obtained at a moisture content value of 40% and a loading speed of 1 mm s –1 in loam soil.
.为了确定土壤的内聚变形模量、摩擦变形模量和土壤恒定值等刚度常数与滚动阻力之间的关系，在 10%、20%、30% 和 40%四种含水量和 1、2、3、4 和 5 mm s -1 五种加载速度下，使用两种壤土和粘壤土质地进行了一系列试验。结果表明，所有独立因素都对土壤刚度常数有显著影响，因此随着含水量和加载速度的增加，土壤刚度常数（内聚变形模量、摩擦变形模量和土壤常数值）也有显著变化。在含水量为 10%、加载速度为 5 mm s -1 的粘壤土中，内聚变形模量和摩擦变形模量的值最高。所有参数在使用 Bekkers 关系计算滚动阻力时都很重要。随着土壤含水量的增加，滚动阻力也随之增加，而加载速度的增加则显著降低了滚动阻力。一般来说，在含水量为 40% 和加载速度为 1 mm s -1 的壤土中，滚动阻力的最高值为 16 887.1 N。
{"title":"Evaluation of the changes in Bekker's parameters and their use in determining\u0000the rolling resistance","authors":"Gholamhossein Shahgholi, Ehsan Aghdamifar, Abdolmajid Moinfar, M. Szymanek, Wojciech Tanaś","doi":"10.31545/intagr/187017","DOIUrl":"https://doi.org/10.31545/intagr/187017","url":null,"abstract":". In order to determine the relationships between the soil stiffness constants of cohesive modulus of deformation, friction modulus of deformation and soil constant value and the rolling resistance, a series of tests was conducted using two types of loam and clay loam soil textures at four moisture contents of 10, 20, 30 and 40% and five loading speeds of 1, 2, 3, 4 and 5 mm s –1 . The results showed that all of the independent fac - tors had a significant effect on the soil stiffness constants, so with increases in moisture content and loading speed, the soil stiffness constants of cohesive modulus of deformation, friction modulus of deformation and soil constant value varied significantly. The highest cohesive modulus of deformation and friction modulus of deformation values were obtained at a moisture content of 10% and loading speed of 5 mm s –1 in a clay loam soil. All param - eters were significant in calculating the rolling resistance using Bekkers’ relationship. With increases in soil moisture content, the rolling resistance increased, while increasing the loading speed reduced the rolling resistance significantly. In general, the highest rolling resistance value of 16 887.1 N was obtained at a moisture content value of 40% and a loading speed of 1 mm s –1 in loam soil.","PeriodicalId":13959,"journal":{"name":"International Agrophysics","volume":null,"pages":null},"PeriodicalIF":2.2,"publicationDate":"2024-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141269326","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Study of wheat (Triticum aestivum L.) seed rehydration observed by the Dent generalized model and 1H-NMR relaxometry","authors":"M. Bacior, Hubert Harańczyk","doi":"10.31545/intagr/186805","DOIUrl":"https://doi.org/10.31545/intagr/186805","url":null,"abstract":"","PeriodicalId":13959,"journal":{"name":"International Agrophysics","volume":null,"pages":null},"PeriodicalIF":2.2,"publicationDate":"2024-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140971207","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
I. Rousta, Safoora Izadian, H. Ólafsson, A. Siedliska, J. Krzyszczak
. Background and Aims: This research investigates vegetation dynamics in the Gavkhouni catchment from 2001 to 2021, focusing on the spring season. The aim is to analyse the relationship between aridity, vegetation, and rainfall. Moreover, additional emphasis was placed on exploring the impact of these dynamics on agricultural land cover thereby contributing to our understanding of the environmental dynamics in the Gavkhouni catchment. Methods: The study made use of MODIS data, includ - ing the Enhanced Vegetation Index and Vegetation Condition Index, along with monthly rainfall statistics from Chirps. Analytical methods include time series analyses using correlation and regression analysis. Results: Throughout the study period, the average spring vegetation cover was 9276.33 km². The years 2001 and 2018 had the lowest degree of vegetation (15.53, and 17.3% of the watershed area). Conversely, 2013, 2019, and 2020 had the most coverage (27.4, 26.8, and 26.3%). The Enhanced Vegetation Index highlighted the arid years (2001, 2008, 2011, and 2018) and the years with the lowest drought prevalence (2006, 2007, 2010, 2013). Enhanced Vegetation Index correlated with spring rainfall. Cropland cover declined over the study period, and a close correlation was found between winter rainfall and spring agricultural coverage.
{"title":"Investigation of vegetation dynamics with a focus on agricultural land cover and its relation with meteorological parameters based on the remote sensing techniques:\u0000a case study of the Gavkhoni watershed","authors":"I. Rousta, Safoora Izadian, H. Ólafsson, A. Siedliska, J. Krzyszczak","doi":"10.31545/intagr/185986","DOIUrl":"https://doi.org/10.31545/intagr/185986","url":null,"abstract":". Background and Aims: This research investigates vegetation dynamics in the Gavkhouni catchment from 2001 to 2021, focusing on the spring season. The aim is to analyse the relationship between aridity, vegetation, and rainfall. Moreover, additional emphasis was placed on exploring the impact of these dynamics on agricultural land cover thereby contributing to our understanding of the environmental dynamics in the Gavkhouni catchment. Methods: The study made use of MODIS data, includ - ing the Enhanced Vegetation Index and Vegetation Condition Index, along with monthly rainfall statistics from Chirps. Analytical methods include time series analyses using correlation and regression analysis. Results: Throughout the study period, the average spring vegetation cover was 9276.33 km². The years 2001 and 2018 had the lowest degree of vegetation (15.53, and 17.3% of the watershed area). Conversely, 2013, 2019, and 2020 had the most coverage (27.4, 26.8, and 26.3%). The Enhanced Vegetation Index highlighted the arid years (2001, 2008, 2011, and 2018) and the years with the lowest drought prevalence (2006, 2007, 2010, 2013). Enhanced Vegetation Index correlated with spring rainfall. Cropland cover declined over the study period, and a close correlation was found between winter rainfall and spring agricultural coverage.","PeriodicalId":13959,"journal":{"name":"International Agrophysics","volume":null,"pages":null},"PeriodicalIF":2.2,"publicationDate":"2024-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141010355","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Hamed Zaresani, Amir Hossein Afkari Sayyah, H. Zareiforoush, Ali Khorramifar, Marek Gancarz, Sylwester Tabor, Hamed Karami
. Rice is an annual plant from the family of Oryzeae, provides the main food for about 2.5 billion people. The quality of this product is under the influence of various factors. Quality control and adulteration detection are among the main issues in the rice industry for which, various methods have been developed. Some of these methods are costly or with low accuracy. Therefore, this study aimed to investigate and detect adulteration with spectroscopic devices and chemometric methods as well as neural network approach. The results of this study indicated the highest accuracy (100%) in the detection of authentic rice for Fourier-transform infrared combined with C-support vector machine (linear and polynomial functions) and visible–near–infrared device with quadratic discriminant analysis, multivariate discriminant analysis, Bayesian, and Decision Tree. The lowest accuracy was also related to support vector machine method with Sigmoid function for both devices. Principal component analysis method also provided very high accuracy for both devices (accuracy of 100% for visible–near–infrared and 99% for Fourier-transform infrared).
{"title":"Vis/NIR and FTIR spectroscopy supported by machine learning techniques to distinguish pure from impure Iranian rice varieties","authors":"Hamed Zaresani, Amir Hossein Afkari Sayyah, H. Zareiforoush, Ali Khorramifar, Marek Gancarz, Sylwester Tabor, Hamed Karami","doi":"10.31545/intagr/185392","DOIUrl":"https://doi.org/10.31545/intagr/185392","url":null,"abstract":". Rice is an annual plant from the family of Oryzeae, provides the main food for about 2.5 billion people. The quality of this product is under the influence of various factors. Quality control and adulteration detection are among the main issues in the rice industry for which, various methods have been developed. Some of these methods are costly or with low accuracy. Therefore, this study aimed to investigate and detect adulteration with spectroscopic devices and chemometric methods as well as neural network approach. The results of this study indicated the highest accuracy (100%) in the detection of authentic rice for Fourier-transform infrared combined with C-support vector machine (linear and polynomial functions) and visible–near–infrared device with quadratic discriminant analysis, multivariate discriminant analysis, Bayesian, and Decision Tree. The lowest accuracy was also related to support vector machine method with Sigmoid function for both devices. Principal component analysis method also provided very high accuracy for both devices (accuracy of 100% for visible–near–infrared and 99% for Fourier-transform infrared).","PeriodicalId":13959,"journal":{"name":"International Agrophysics","volume":null,"pages":null},"PeriodicalIF":2.2,"publicationDate":"2024-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140688579","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Hiroki Naito, Yasushi Kawasaki, Kota Hidaka, T. Higashide, Masahiro Misumi, Tomohiko Ota, Unseok Lee, Masaaki Takahashi, Fumiki Hosoi, Junichi Nakagawa
. Strawberries are an economically valuable fruit in Japan; hence, their production must be maintained throughout the year. In this study, we investigated the effect of temperature on the number of days required for each fruit growth and rip-ening stage in order to obtain a basic knowledge for the highly accurate prediction and control of fruit harvest time. We planted the ‘Koiminori’ variety in artificial climate chambers, and then the effect of the average air temperature on the number of days required for each stage was analysed in four stages. The results showed that the correlation between temperature and the number of days required for fruit maturity was high at the white stage, moderate at the flowering and turning stages, and weak at the green stage. In comparing our proposed method which estimates the entire maturation period of the strawberries by totalling the predicted number of days required for each stage with the conventional method of estimating the entire maturation period at once, our proposed method significantly reduced the mean abso - lute error. However, the difference was slight at 0.18 days. This result suggests that the number of days required for each stage should be optimized for prediction by adding parameters other than air temperature as independent variables.
{"title":"Effect of air temperature on each fruit growth and ripening stage of strawberry ‘Koiminori’","authors":"Hiroki Naito, Yasushi Kawasaki, Kota Hidaka, T. Higashide, Masahiro Misumi, Tomohiko Ota, Unseok Lee, Masaaki Takahashi, Fumiki Hosoi, Junichi Nakagawa","doi":"10.31545/intagr/185988","DOIUrl":"https://doi.org/10.31545/intagr/185988","url":null,"abstract":". Strawberries are an economically valuable fruit in Japan; hence, their production must be maintained throughout the year. In this study, we investigated the effect of temperature on the number of days required for each fruit growth and rip-ening stage in order to obtain a basic knowledge for the highly accurate prediction and control of fruit harvest time. We planted the ‘Koiminori’ variety in artificial climate chambers, and then the effect of the average air temperature on the number of days required for each stage was analysed in four stages. The results showed that the correlation between temperature and the number of days required for fruit maturity was high at the white stage, moderate at the flowering and turning stages, and weak at the green stage. In comparing our proposed method which estimates the entire maturation period of the strawberries by totalling the predicted number of days required for each stage with the conventional method of estimating the entire maturation period at once, our proposed method significantly reduced the mean abso - lute error. However, the difference was slight at 0.18 days. This result suggests that the number of days required for each stage should be optimized for prediction by adding parameters other than air temperature as independent variables.","PeriodicalId":13959,"journal":{"name":"International Agrophysics","volume":null,"pages":null},"PeriodicalIF":2.2,"publicationDate":"2024-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140691804","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
. Organic farming is system with a growing interest worldwide. The objective of this paper was an assessment of the after-effects of perennial cultivation of spring barley, oats, and red clover in both conventional and organic systems on the chemi - cal properties, enzymatic activity, and potential biochemical soil fertility index of the soil. The study analyzed the activity of acid phosphatase, alkaline phosphatase, urease and dehydrogenases as well as the potential biochemical soil fertility index of soil and the chemical parameters of soil. Soil material was collected from spring wheat grown after spring barley, oats and red clover, occurring in conventional or organic systems in 2009-2019. It has been shown that, compared to a conventional system, the perennial cultivation of red clover and cereals in the organic farming system has contributed to a significant improvement in the chemical (pH KCl by an average of 8%, total organic carbon – 18%, total nitrogen – 15%, N-NH 4 + – 34%) and enzymatic (acid phosphatase – 29%, alkaline phosphatase – 67%, urease – 28% and dehydrogenases – 25%) soil quality indicators. The potential biochemical soil fertility index values were also significantly higher in soils in the organic farming system (by an average of 39%).
{"title":"Integrated assessment of the impact of conventional and organic farming systems on soil biochemical indicators","authors":"B. Futa, Magdalena Myszura-Dymek, S. Wesołowska","doi":"10.31545/intagr/185985","DOIUrl":"https://doi.org/10.31545/intagr/185985","url":null,"abstract":". Organic farming is system with a growing interest worldwide. The objective of this paper was an assessment of the after-effects of perennial cultivation of spring barley, oats, and red clover in both conventional and organic systems on the chemi - cal properties, enzymatic activity, and potential biochemical soil fertility index of the soil. The study analyzed the activity of acid phosphatase, alkaline phosphatase, urease and dehydrogenases as well as the potential biochemical soil fertility index of soil and the chemical parameters of soil. Soil material was collected from spring wheat grown after spring barley, oats and red clover, occurring in conventional or organic systems in 2009-2019. It has been shown that, compared to a conventional system, the perennial cultivation of red clover and cereals in the organic farming system has contributed to a significant improvement in the chemical (pH KCl by an average of 8%, total organic carbon – 18%, total nitrogen – 15%, N-NH 4 + – 34%) and enzymatic (acid phosphatase – 29%, alkaline phosphatase – 67%, urease – 28% and dehydrogenases – 25%) soil quality indicators. The potential biochemical soil fertility index values were also significantly higher in soils in the organic farming system (by an average of 39%).","PeriodicalId":13959,"journal":{"name":"International Agrophysics","volume":null,"pages":null},"PeriodicalIF":2.2,"publicationDate":"2024-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140726766","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Olga Kosewska, S. Przemieniecki, Stanisława Koronkiewicz, M. Nietupski
study
研究
{"title":"Effect of different chemical properties of cereal grains on the foraging\u0000and microbiome of the rice weevil (Sitophilus oryzae L.)","authors":"Olga Kosewska, S. Przemieniecki, Stanisława Koronkiewicz, M. Nietupski","doi":"10.31545/intagr/185216","DOIUrl":"https://doi.org/10.31545/intagr/185216","url":null,"abstract":"study","PeriodicalId":13959,"journal":{"name":"International Agrophysics","volume":null,"pages":null},"PeriodicalIF":2.2,"publicationDate":"2024-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140377913","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
. The aim of the experiments was to evaluate shifts in the prokaryotic and eukaryotic microbiome of maize rhizoplanes treated with five forms silver nanoparticles with different surface properties, produced by chemical reduction of silver(V) nitrate. Metagenomic studies were performed using appropriate procedures to create NGS libraries and sequences to species. All silver nanoparticles forms used moderately limited the growth of maize, without significantly affecting normalized difference vegetation indexes. Significant shifts in the taxa of the microbiome while preserving bio - diversity were noted under the influence of silver nanoparticles, and the reaction of bacteria and eukaryotes was different. The eukaryotic microbiome, richer in the studied substrate, turned out to be more sensitive, showing greater qualitative and quantitative changes than the bacteriome. silver nanoparticles did not reduce the occurrence of mycorrhizal fungi, enriched the occurrence of Acidobacteriota and, with the exception of trisodium citrate reduction/sodium borohydride stabilization type, enriched the beneficial bacteria of Devosia. Within silver nanoparticles, distinct effects have been demonstrated for type with trisodium citrate reduction/sodium borohydride stabilization versus cysteamine reduction/trisodium citrate stabilization versus group: hydroxylamine hydrochloride reduction, tannic acid reduction and trisodium citrate reduction. The beneficial changes in maize rhiz - oplane microbiome can be attributed special to silver nanoparticles reduced using hydroxylamine hydrochloride.
{"title":"Comparative effect of silver nanoparticles on maize rhizoplane microbiome in initial phase\u0000of plants growth","authors":"Anna Gorczyca, S. Przemieniecki, M. Oćwieja","doi":"10.31545/intagr/184863","DOIUrl":"https://doi.org/10.31545/intagr/184863","url":null,"abstract":". The aim of the experiments was to evaluate shifts in the prokaryotic and eukaryotic microbiome of maize rhizoplanes treated with five forms silver nanoparticles with different surface properties, produced by chemical reduction of silver(V) nitrate. Metagenomic studies were performed using appropriate procedures to create NGS libraries and sequences to species. All silver nanoparticles forms used moderately limited the growth of maize, without significantly affecting normalized difference vegetation indexes. Significant shifts in the taxa of the microbiome while preserving bio - diversity were noted under the influence of silver nanoparticles, and the reaction of bacteria and eukaryotes was different. The eukaryotic microbiome, richer in the studied substrate, turned out to be more sensitive, showing greater qualitative and quantitative changes than the bacteriome. silver nanoparticles did not reduce the occurrence of mycorrhizal fungi, enriched the occurrence of Acidobacteriota and, with the exception of trisodium citrate reduction/sodium borohydride stabilization type, enriched the beneficial bacteria of Devosia. Within silver nanoparticles, distinct effects have been demonstrated for type with trisodium citrate reduction/sodium borohydride stabilization versus cysteamine reduction/trisodium citrate stabilization versus group: hydroxylamine hydrochloride reduction, tannic acid reduction and trisodium citrate reduction. The beneficial changes in maize rhiz - oplane microbiome can be attributed special to silver nanoparticles reduced using hydroxylamine hydrochloride.","PeriodicalId":13959,"journal":{"name":"International Agrophysics","volume":null,"pages":null},"PeriodicalIF":2.2,"publicationDate":"2024-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140223690","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Edyta Kwiatkowska, J. Joniec, C. Kwiatkowski, Krzysztof Kowalczyk, M. Nowak, J. Leśniowska-Nowak
. In the present study, biological indicators were used to assess the impact of applying spent mushroom substrate and manure on the soil environment. The use of spent mushroom substrate had a varied effect on the microorganisms. Stimulation was recorded in the abundance of copiotrophic bacteria and fungi, but only in the first year of the study. In the case of cellulolytic bacteria, this effect was visible only in single plots. Similar observations were also noted regarding the relative DNA content (in relation to the control), which increased for both bacteria and fungi after applying spent mushroom substrate. In the soil fertilized with spent mushroom substrate, a decrease in DNA concentration was observed, but only in the first and second year. For enzymatic activity, the use of spent mushroom substrate alone proved to be more favorable, but this effect was again observed only in the first year of the study. The application of manure caused similar changes as observed with the use of spent mushroom substrate. These observations indicate a similar impact of spent mushroom substrate and manure on the parameters tested. The research presented suggests the use of both classical methods and methods based on the analysis of DNA extracted from soil to study the impact of spent mushroom substrate on the activity of soil microbial populations.
.本研究使用生物指标来评估施用废蘑菇基质和粪肥对土壤环境的影响。使用废蘑菇基质对微生物有不同的影响。共养细菌和真菌的数量受到了刺激，但这只发生在研究的第一年。至于纤维素分解菌，只有在单个地块中才能看到这种影响。在相对 DNA 含量（与对照相比）方面也发现了类似的情况，在施用废蘑菇基质后，细菌和真菌的 DNA 含量都有所增加。在施用废蘑菇基质肥料的土壤中，DNA 含量有所下降，但仅发生在第一年和第二年。在酶活性方面，事实证明单独使用废蘑菇基质更有利，但这一效果也仅在研究的第一年出现。施用粪肥所产生的变化与使用废蘑菇基质所产生的变化相似。这些观察结果表明，废蘑菇基质和粪肥对测试参数的影响相似。这项研究建议使用传统方法和基于从土壤中提取的 DNA 分析方法来研究废蘑菇基质对土壤微生物种群活动的影响。
{"title":"Assessment of the impact of spent mushroom substrate on biodiversity and activity of soil bacterial and fungal populations based on classical and modern soil condition indicators","authors":"Edyta Kwiatkowska, J. Joniec, C. Kwiatkowski, Krzysztof Kowalczyk, M. Nowak, J. Leśniowska-Nowak","doi":"10.31545/intagr/184175","DOIUrl":"https://doi.org/10.31545/intagr/184175","url":null,"abstract":". In the present study, biological indicators were used to assess the impact of applying spent mushroom substrate and manure on the soil environment. The use of spent mushroom substrate had a varied effect on the microorganisms. Stimulation was recorded in the abundance of copiotrophic bacteria and fungi, but only in the first year of the study. In the case of cellulolytic bacteria, this effect was visible only in single plots. Similar observations were also noted regarding the relative DNA content (in relation to the control), which increased for both bacteria and fungi after applying spent mushroom substrate. In the soil fertilized with spent mushroom substrate, a decrease in DNA concentration was observed, but only in the first and second year. For enzymatic activity, the use of spent mushroom substrate alone proved to be more favorable, but this effect was again observed only in the first year of the study. The application of manure caused similar changes as observed with the use of spent mushroom substrate. These observations indicate a similar impact of spent mushroom substrate and manure on the parameters tested. The research presented suggests the use of both classical methods and methods based on the analysis of DNA extracted from soil to study the impact of spent mushroom substrate on the activity of soil microbial populations.","PeriodicalId":13959,"journal":{"name":"International Agrophysics","volume":null,"pages":null},"PeriodicalIF":2.2,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140084371","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：