Soil Nutrient Content Research Articles

Effect of integrated vermicompost and chemical nitrogen fertilizer for productivity of bread wheat (Triticum aestivum L.)

The study was conducted at Horo district on six (6) farmers’ fields to investigate the effect of integrated vermicompost and chemical nitrogen fertilizer for bread wheat and the soil nutrient content. The treatments consist of without any fertilizer, recommended chemical NP fertilizer, 100% N equivalent vermicompost + recommended P2O5, 75% N equivalent Vermicompost + 25% recommended N + recommended P2O5, 50% equivalent Vermicompost + 50% recommended N + recommended P2O5 and 25% equivalent Vermicompost + 75% recommended N + recommended P2O5. The experimental design was a randomized complete block design (RCBD) with three replications. Dendea seed variety with a rate of 150 Kg ha-1 was used for the trial. ANOVA analysis for after harvesting soil parameters showed significant (P<0.05) differences among treatments for available phosphorus, organic carbon, exchangeable acidity and cations exchange capacity while pH and exchangeable Ca and Mg were not statistically significant among the treatments. ANOVA showed that the treatments significantly influenced all collected yield and yield related parameters of the crop. Relatively the highest crop yield and yield related traits were obtained from T2 (recommended chemical fertilizer) while the lowest was from control (without fertilizer). The highest net income (91971.70 birr/ha) was obtained from 25% equivalence vermicompost + 75% recommended N + recommended P2O5. To have more confidence in the technology; it should be verified in the same area with the same management procedure.

Smart watering of ornamental plants: exploring the potential of decision trees in precision agriculture based on IoT

Ornamental plant farmers face various challenges due to climate change and environmental stress that significantly affect plant health and growth. This research overcomes these challenges by developing an intelligent watering system that uses internet of things (IoT) technology and decision trees (DTs) algorithms to optimize the use of planting land by ensuring plants grow in the most optimal conditions, both in terms of water and nutrients and increase land productivity. The system is built by integrating various sensors to monitor soil moisture, air humidity, temperature, and light intensity in real-time. The collected data is used to automate watering schedules and provide recommendations on suitable plant species based on the soil nutrient content of nitrogen (N), phosphorus (P), and potassium (K). The use of the DTs algorithm helps in analyzing the data from the sensors and providing recommendations on the most suitable plants for the land. The smart watering system was tested in three zones, each simulating a different watering scenario, and successfully maintained optimal conditions for plant growth in each zone. The machine learning (ML) model with the DTs algorithm can predict the right type of ornamental plants based on the existing land conditions in three watering zones, with an accuracy of 89 %, 90 %, and 91 %, respectively. Furthermore, farmers can follow these recommendations to minimize damage and death of plants so that the level of productivity on the land becomes optimal.

Effect of AMF Inoculation on Reducing Excessive Fertilizer Use.

Excessive use of chemical fertilizer is a global concern. Arbuscular mycorrhizal fungi (AMF) are considered a potential solution due to their symbiotic association with crops. This study assessed AMF's effects on maize yield, fertilizer efficiency, plant traits, and soil nutrients under different reduced-fertilizer regimes in medium-low fertility fields. We found that phosphorus supplementation after a 30% fertilizer reduction enhanced AMF's positive impact on grain yield, increasing it by 3.47% with pure chemical fertilizers and 6.65% with mixed fertilizers. The AMF inoculation did not significantly affect the nitrogen and phosphorus fertilizer use efficiency, but significantly increased root colonization and soil mycelium density. Mixed fertilizer treatments with phosphorus supplementation after fertilizer reduction showed greater mycorrhizal effects on plant traits and soil nutrient contents compared to chemical fertilizer treatments. This study highlights that AMF inoculation, closely linked to fertilization regimes, can effectively reduce fertilizer use while sustaining or enhancing maize yields.

Optimizing Glutinous Corn Productivity through Demonstration Plots with the Application of Combined Organic Ameliorants

Sandy soil in Muncuk Karya, Ampenan, has low water retention and nutrient content, making it difficult for sticky rice farmers to meet their plants' water and nutrient needs. To overcome this challenge, research entitled "Optimizing Glutinous Corn Productivity through Demonstration Plots with the Application of Combined Organic Ameliorants" was carried out using an experimental methodology using a randomized block design involving five treatments and four replications, so that there were a total of 20 treatment plots. The treatments applied consisted of: A1 (50% cow manure + 50% mycorrhizal biofertilizer), A2 (50% compost + 50% mycorrhizal biofertilizer), A3 (50% fertile organic fertilizer + 50% mycorrhizal biofertilizer), A4 (50% rice husk charcoal + 50% mycorrhizal biofertilizer), and A5 (50% mixture of cow manure, compost, fertile organic fertilizer, and rice husk charcoal with a volume ratio of 1:1:1:1 + 50% mycorrhizal biofertilizer). The research results showed that the application of ameliorant, a combination of 50% cow manure and 50% mycorrhizal biofertilizer, was proven to be effective in increasing growth, plant productivity, soil nutrient concentration, plant nutrient uptake, and mycorrhizal development in the soil. To increase the productivity of sticky corn plants, soil fertility, plant nutrient uptake, and mycorrhiza development, it is recommended to use this combination ameliorant application.

基于土壤养分检测的变量施肥系统的设计与试验

In order to solve the problems of low correlation between variable fertilizer application system and soil nutrient content detection and insufficient real-time performance, a variable fertilizer application system based on real-time soil nutrient content detection was developed. This paper describes the structure, working principle and design of key components of the soil information acquisition and fertilizer application system. It includes the simulation and analysis of fertilizer application using the discrete element method and the selection of curved blade fertilizer application discs. The system uses STM32F429IGT6 microcontroller and ROS higher-level computer for decision making. The device detects soil nutrients in real time, adjusts the fertilizer motor speed accordingly, and runs autonomously along the planned path. The decision coefficient R^2 between the fertilizer application rate and the speed of the fertilizer application wheel is not less than 0.97, and the relative error between the actual fertilizer application rate and the theoretical fertilizer application rate is up to 5.91%, with the maximum value of the coefficient of variation (CV) of 10.18%. The indoor bench test shows that the relative error between the actual fertilizer application rate and the target fertilizer application rate within a single operating grid is up to 6.2%, with the maximum value of CV being 6.64%. The field test in the orchard showed that the maximum relative error between the actual fertilizer application and the target fertilizer application in a single operation grid was 6.3%, and the maximum value of CV was 12.34%, and the fertilizer application was completed in the operation grid, which demonstrated that the device was able to realize real-time and accurate variable fertilizer application according to the soil nutrient information.

No tillage and organic fertilization improved kiwifruit productivity through shifting soil properties and microbiome

AbstractThe preservation of edaphic quality and productivity is critical for the ecological sustainability of vine orchards. The heavy utilization of intensified tillage and singular chemical fertilizers can shift changes in edaphic physicochemical and biological features, thus exerting significant pressure on agroecosystems. In current research, we assessed the shifts in soil physicochemical features and soil microbiome composition over 11 years carrying out no tillage and organic fertilizer substitution in a typical Chinese Guanzhong kiwifruit production area, and explore the fundamental factors that contribute to alterations in the microbial community and the influence on kiwifruit performance. Results showed that long‐term no tillage and organic fertilizer improved the soil condition by significantly increasing the proportion of soil macroaggregates, bulk density, and nutrient content (e.g., organic matter, nitrogen, and ammonia), as compared to conventional tillage with chemical fertilization. Moreover, no tillage significantly increased soil bacterial α‐diversity but had no significant effects on fungal. No tillage also enhanced the abundance of potential beneficial soil bacteria (e.g., Acidobacteria, Actinobacteria, and Nitrospira), while decreasing the abundance of Proteobacteria, Pseudomonas, and Fusarium. In addition, no tillage and mixed fertilized soil microbial network exhibited higher complexity (i.e., node and edge numbers, and positive edge proportion) and connectivity (i.e., average number of neighbors) than conventional tillage and chemical fertilization group. Changes in nitrate, ammonia, available phosphorus, and pH values accounted for the variation in the structure of soil microbial community. Hence, the utilization of both no tillage and organic fertilization practices could serve as a suitable and sustainable approach for managing kiwifruit production in the fragile environmental conditions of the Chinese Guanzhong region, and lead to an improvement in soil nutrient levels and help regulate the soil microbial community.

Soil Fungal Function Centralization Enhances the Decomposition of Fine Roots at Canopy Gap Borders

Canopy gaps can result in abiotic heterogeneities and diverse niches from gap borders to centers, potentially affecting fine root decompositions mediated by soil fungal communities. Despite extensive discussions on the relationship between soil fungi and fine root decomposition, the mechanism by which gap locations regulate fine root decomposition through the soil fungal community remains elusive. Here, we conducted an in situ field decomposition experiment of Chinese Toon (Toona senensis) fine roots in a low-efficiency weeping cypress (Cupressus funebris) plantation forest across three microhabitats: gap centers, gap borders, and closed canopy areas. Soil fungal communities were determined using internal transcribed spacer (ITS) sequencing after two years of field incubation. Results showed that soil properties and nutrient content in residual roots varied across the three microhabitats, with the gap borders exhibiting the highest decomposition rates. While fungal α-diversity remained relatively consistent, taxonomic compositions differed significantly. Decomposition rates did not show significant correlations with soil properties, observed fungal ASVs, or overall community composition. However, they positively correlated with the relative abundance of saprotrophic Sordariomycetes, which in turn positively correlated with soil total nitrogen (with a highest correlation), peaking at the gap borders. Overall community variations were primarily driven by soil temperature and magnesium content in residual roots. Further analysis revealed high fungal community similarities and low dispersal limitations between the gap borders and closed canopy areas, with more phylogenetically clustered communities at the borders. These results demonstrate that the gap borders possess a high decomposition rate, likely due to the centralization of functions driven by soil fungi such as saprotrophs existing in the “microbial seed bank” or migrating from closed canopy areas. These findings highlight the key role of soil fungi, especially saprotrophic fungi, in fine root decomposition at the gap borders, stressing the importance of soil fungi-driven mechanisms in nutrient cycling, and also informing sustainable forest management practices.

Seed endophytes and rhizosphere microbiome of Imperata cylindrica, a pioneer plant of abandoned mine lands.

Some plant-associated microorganisms could improve host plants biotic and abiotic stress tolerance. Imperata cylindrica is a dominant pioneer plant in some abandoned mine lands with higher concentrations of heavy metal (HM). To discover the specific microbiome of I. cylindrica in this extreme environment and evaluate its role, the microbiome of I. cylindrica's seeds and rhizosphere soils from HM heavily contaminated (H) and lightly contaminated (L) sites were studied. It was found that HM-contamination significantly reduced the richness of endophytic bacteria in seeds, but increased the abundance of resistant species, such as Massilia sp. and Duganella sp. Spearman's rank correlation coefficient analysis showed that both Massilia sp. and Duganella sp. showed a significant positive correlation with Zn concentration, indicating that it may have a strong tolerance to Zn. A comparison of the microbiome of rhizosphere soils (RS) and adjacent bare soils (BS) of site H showed that I. cylindrica colonization significantly increased the diversity of fungi in rhizosphere soil and the abundance of Ascomycota associated with soil nutrient cycling. Spearman's rank correlation coefficient analysis showed that Ascomycota was positively correlated with the total nitrogen. Combined with the fact that the total nitrogen content of RS was significantly higher than that of BS, we suppose that Ascomycota may enhance the nitrogen fixation of I. cylindrica, thereby promoting its growth in such an extreme environment. In conclusion, the concentration of HM and nutrient contents in the soil significantly affected the microbial community of rhizosphere soils and seeds of I. cylindrica, in turn, the different microbiomes further affected soil HM concentration and nutrient contents. The survival of I. cylindrica in HM severely contaminated environment may mainly be through recruiting more microorganisms that can enhance its nutrition supply.

The Ability of Different Tea Tree Germplasm Resources in South China to Aggregate Rhizosphere Soil Characteristic Fungi Affects Tea Quality.

It is generally recognized that the quality differences in plant germplasm resources are genetically determined, and that only a good "pedigree" can have good quality. Ecological memory of plants and rhizosphere soil fungi provides a new perspective to understand this phenomenon. Here, we selected 45 tea tree germplasm resources and analyzed the rhizosphere soil fungi, nutrient content and tea quality. We found that the ecological memory of tea trees for soil fungi led to the recruitment and aggregation of dominant fungal populations that were similar across tea tree varieties, differing only in the number of fungi. We performed continuous simulation and validation to identify four characteristic fungal genera that determined the quality differences. Further analysis showed that the greater the recruitment and aggregation of Saitozyma and Archaeorhizomyces by tea trees, the greater the rejection of Chaetomium and Trechispora, the higher the available nutrient content in the soil and the better the tea quality. In summary, our study presents a new perspective, showing that ecological memory between tea trees and rhizosphere soil fungi leads to differences in plants' ability to recruit and aggregate characteristic fungi, which is one of the most important determinants of tea quality. The artificial inoculation of rhizosphere fungi may reconstruct the ecological memory of tea trees and substantially improve their quality.

Miscanthus sp. root exudate alters rhizosphere microbial community to drive soil aggregation for heavy metal immobilization

The heavy metals (HMs) spatial distribution in soil is intricately shaped by aggregation processes involving chemical reactions and biological activities, which modulate HMs toxicity, migration, and accumulation. Pioneer plants play a central role in preventing HMs at source, yet the precise mechanisms underlying their involvement in soil aggregation remain unclear. This study investigates HMs distribution within rhizosphere and bulk soil aggregates of Miscanthus sp. grown in tailings to elucidate the impact of root exudates (REs) and rhizosphere microbes. The results indicate that Miscanthus sp. enhance soil stability, increasing the proportion of macroaggregates by 4.06 %–9.78 %. HMs tend to concentrate in coarse-aggregates, particularly within rhizosphere environments, while diminishing in fine-aggregates. Under HMs stress, lipids and lipid-like molecules are the most abundant REs produced by Miscanthus sp., accounting for under up to 26.74 %. These REs form complex with HMs, promoting microaggregates formation. Charged components such as sugars and amino acids further contribute to soil aggregation. REs also regulates rhizosphere bacteria and fungi, with Acidobacteriota, Chloroflexi were the dominant bacterial phyla, while Ascomycota and Basidiomycota dominate the fungal community. The synergistic effect of REs and microorganisms impact soil organic matter and nutrient content, facilitating HMs nanoparticle heteroaggregation and macroaggregates formation. Consequently, soil structure and REs shape the distribution of HMs in soil aggregation. Pioneer plants mediate REs interaction with rhizosphere microbes, promoting the distribution of HMs into macroaggregates, leading to immobilization. This study sheds light on the role of pioneer plants in regulating soil HMs, offering valuable insights for soil remediation strategies.

Soil pH and Nutrient Content Sustain Variability of Soil Bacterial Community Structure and Activity after Forest Clear-Cutting

Clear-cutting is the most robust intervention in a forest ecosystem, causing marked changes in ecosystem processes. Although the effects of forest harvesting have been widely investigated, comparative studies can provide vital supplementary information concerning specific fields, including changes in soil microbiota structure and functioning. Our study examined the soil bacterial community composition, diversity, and activity of a mixed pedunculate oak stand over three years after clear-cutting based on 16S rRNA sequencing and substrate-induced respiration data. In addition, we conducted a yearly comparison with a control oak stand already in the regeneration phase. According to our results, the forest harvest caused only limited changes in the diversity, structure, and activity of the soil bacterial community of the oak stand, suggesting that soil parameters influence the soil bacterial community structure and functioning more significantly than the cessation of forest cover.

Low-cost precision agriculture for sustainable farming using paper-based analytical devices.

The United Nations estimates that by 2030, agricultural production must increase by 70% to meet food demand. Precision agriculture (PA) optimizes production through efficient resource use, with soil fertility being crucial for nutrient supply. Traditional nutrient quantification methods are costly and time-consuming. This study introduces a rapid (15 min), user-friendly, paper-based platform for determining four essential macronutrients-nitrate, magnesium, calcium, and ammonium-using colorimetric methods and a smartphone for data reading and storage. The sensor effectively detects typical soil nutrient concentrations, showing strong linearity and adequate detection limits. For nitrate, the RGB method resulted in an R 2 of 0.992, a detection range of 0.5 to 10.0 mmol L-1, and an LOD of 0.299 mmol L-1. Calcium quantification using grayscale displayed an R 2 of 0.993, a detection range of 2.0 to 6.0 mmol L-1, and an LOD of 0.595 mmol L-1. Magnesium was best quantified using the hue color space, with an R 2 of 0.999, a detection range of 1.0 to 6.0 mmol L-1, and an LOD of 0.144 mmol L-1. Similarly, ammonium detection using the hue color space had an R 2 of 0.988, a range of 0.5 to 2.5 mmol L-1, and an LOD of 0.170 mmol L-1. This device enhances soil fertility assessment accessibility, supporting PA implementation and higher food production.

Monitoring soil nutrients using machine learning based on UAV hyperspectral remote sensing

ABSTRACT Unmanned aerial vehicles (UAV) are rapidly evolving experimental platforms that play an important role in remote sensing. In this study, we investigated a machine learning method for monitoring soil nutrient content using UAV hyperspectral remote sensing. We employed machine learning techniques for feature extraction and soil hyperspectral information modelling. In contrast to traditional mathematical transformation methods, we adopted a combination of random forest and differential evolution algorithms to rank the weights of individual hyperspectral data, thereby obtaining a series of spectral feature subsets for soil organic matter, total nitrogen and available phosphorus and potassium. Furthermore, the analytic hierarchy process was used for weight analysis, and the characteristic bands of the four soil nutrients were successfully extracted. Next, a quantitative inversion model based on a back-propagation (BP) neural network was established to estimate soil nutrient content, with determination coefficients higher than 0.7 and 0.6 for the modelling and verification sets, respectively. The relative percent difference values were greater than 2, among which the highest was for available potassium, with determination coefficients of 0.95 and 0.84 for the modelling and verification sets, respectively. In addition, visualization distribution maps of soil nutrients were obtained by combining the BP model and original reflectance hyperspectral images, and the comparisons of content histograms showed a relatively consistent distribution between the sampling and inversion points. The results verified the effectiveness of the combined machine learning method for large-scale and high-precision monitoring and visualization of soil nutrient contents.

Assessment of Soil Structural Quality Under Area Closure and Open Grazing Land in Hidabu Abote District, North Shewa Zone, Oromia Regional State, Ethiopia

The experiment was conducted at Sire Morise kebele, Hidabu Abote district, to assess soil structural quality of different land management system (area closure and open grazing land). In this study, area closure land management practice was compared with open grazing land management practice in similar slope positions for soil structural quality build up. Soil samples were collected from both land management system at three slope position with three times replication. Totally 36 undisturbed soil blocks were collected from both land management system at 10 and 20 cm sampling depths. The finding of the study showed that the average value of volumetric moisture content and saturated hydraulic conductivity of soil were greater at area closure than open grazing land management system and also higher at bottom slope position than middle and upper slope position. The mean value of air-filled porosity and bulk density were lower at both area closure management practices and bottom slope position. Bulk density, volumetric soil moisture content and saturated hydraulic conductivity at 20 cm sampling depth were shows significantly different with respect to management practices. According to visual assessment in the field, soil physical quality was unfavourable in open grazing land management system and upper part of landscape position soils and the visual assessment scores showed that the soils under area closure had a good soil structural quality. There were strong relations among the three visual field assessment methods and also between visual assessment methods and laboratory determined soil properties of both land management system. In general, the result of the study showed that physical and structural quality of soil in area closure was improved due to good land management system. Based on the result of study it can be conclude that area closure improves soil physical and soil structural qualities and from the technical point of view, open grazing lands in hilly area should be changed to area closure before soil properties and soil nutrient contents are exhausted more.

Once in Three-Year Deep-Banding and Annual Shallow-Banding of P, K and Cu Fertilizer Effects on Crops and Soil Nutrients

Deep-banding of the immobile nutrients (P, K, and Cu) is considered one technique that may improve crop production under temperate dryland systems, where moister soil conditions prevail at seeding followed by relatively drier soil during the growing period. The objectives were to compare growth and yield of canola (Brassica napus L.), field pea’s (Pisum sativum L.) and wheat (Triticum aestivum L.); and nutrient concentrations in crops and soil from once in three-year deep-banding (12.5-15 cm) and annual shallow-banding (3.75 to 5 cm diagonally deeper than seeding depth) of P, K and Cu under direct seeding systems. Small plot trials were conducted at the three sites; representing Brown (Dark Brown Chernozem), Black (Black Chernozem), and Grey (Dark Grey Luvisol) soil zones in Alberta, Canada; which represent crop growing conditions for most areas of western Canada. The nine treatments were annual shallow-banding and once in three year deep-banding of P, K, Cu and PKCU nutrients plus a control (no P, K, or Cu fertilizer). Applied thrice the recommended rate for deep-banding (in 2018) treatments and the recommended rate for the annual shallow-banding treatments in 2018, 2019 and 2020. All three phases of pea’s-wheat-canola rotation were grown at each site to generate nine years of data for each crop. The density, height, NDVI (normalized difference vegetation index) and biomass of plants, yield for crops and nutrient concentrations in seed and biomass of crops and soil showed significantly positive responses to P, K, and PKCu additions in some cases; generally not linked to the deep or shallow placement of tested nutrients. Changes in nutrient concentrations in seed and biomass of crops in response to nutrient additions were not consistent. Treatments with P showed response more often than with the K and Cu. The soil P and Cu concentrations increased in response to their additions in some cases, but no change was observed from the K addition. Once in three-year deep-banding or annual shallow-banding methods were equally effective. The findings provide another option (once in three year deep-banding) for applying the P, K and Cu fertilizers.

Effects of different afforestation years on soil moisture and nutrient content in Maxian Mountain of the Loess Plateau

In the area of “returning farmland to forest” on the Loess Plateau in China, it is difficult to cultivate artificially planted trees into forests. In the current study, abandoned cultivated land after 10 years of natural restoration served as controls (CK), while the treatments included afforestation periods of 2, 4, 6, 8, and 10 years. Soil samples were collected from various depths: 0–20, 20–40, 40–60, 60–80, to 80–100 cm. The findings revealed that with increasing years of artificial afforestation, soil pH gradually increased, and soil moisture content rose in the 0–20 cm layer while declining in deeper layers (20–100 cm) in the Maxian Mountain region of the Loess Plateau. Moreover, the total carbon, nitrogen, phosphorus, and potassium content initially increased and then decreased with the duration of artificial afforestation, reaching peak values after 8 years. Contents of organic matter, ammonium nitrogen, nitrate nitrogen, available phosphorus, and available potassium in the same soil layer increased with each year of afforestation. However, upon reaching 10 years of artificial afforestation, the effective nutrient content in the 60–80 and 80–100 cm soil layers exhibited a decrease. The values of Integrated Fertility Index (IFI) in different afforestation years were ranked as follows: 8 years > 6 years > 10 years > 4 years > 2 year, but all of them were significantly smaller than those of natural restoration plot CK (P < 0.05). Overall, soil fertility in the Maxian Mountain area of the Loess Plateau increases with each additional year of artificial afforestation. However, when the artificial afforestation period is 10 years, soil fertility decreases and marking a shift from enhancement to decline beyond this duration.

Evaluation of spent coffee grounds as a nutrient source for turfgrass systems

The growing popularity of cold-brewed coffee has resulted in large amounts of localized spent coffee grounds (SCG) generated from production plants. Spent coffee grounds offer many favorable agronomic properties, but also contain caffeine, tannins and phenolic compounds that may be deleterious to plant growth. There is a growing body of research examining the effects of SCG on plants, but little of which pertains to use in turfgrass systems. The objective of this two-year field study was to evaluate the feasibility of using SCG as an agronomic source of nutrients for turfgrass. Field studies were conducted over two years to characterize performance of ‘Riley’s Super Sport’ (Celebration®) bermudagrass (Cynodon dactylon) receiving multiple nutrient source treatments including fresh and composted SCG, as well as synthetic, natural organic, and bridge fertilizers, some which included SCG. Soils were analyzed at the conclusion of the study to determine whether SGC provided long-term effects of on soil pH and/or nutrient concentrations. Our results demonstrated that although SCG possesses between 2.3-2.9% N and a favorable C:N ratio, direct SCG applications over two seasons did not produce responses typical of a fertilizer when applied as a topdressing. However, when combined with poultry litter, the SCG-containing organic fertilizer GeoJava produced improved turf quality relative to other organic and synthetic commercial fertilizers in our study, including Milorganite, ammonium sulfate, and URI-PEL S.R. Further, despite the acidic nature of SCG, their repeated application over multiple years did not result in any long-term changes to soil pH. Although early on, SCG treatments caused mild and transient phytotoxicity, these effects were not observed when it was applied in combination with the manure used in GeoJava.

Study on Soil Fertility Characteristics of Walnut Orchards with Different Parent Materials and Soil Types in Gyaca County, Tibet

Walnut trees on the Tibetan Plateau have sustainable and nutritious characteristics. They grow naturally without the use of any chemical fertilizers and pesticides. Therefore, the soil fertility of walnut orchards is a key factor influencing walnut yield and quality. This experiment measured and analyzed the basic soil nutrient content, microbial biomass carbon (MBC), nitrogen (MBN), phosphorus (MBP), and leaf nutrient indicators in five types of representative walnut orchard soil parent materials in Gyaca County to clarify the fertility characteristics of different soil types and their correlations with walnut nutrients, providing a basis for the sustainable development of the plateau walnut industry. The results showed that there were significant differences in soil organic matter (SOM), total nitrogen (TN), available nutrient contents, and microbial activity among soil types with different parent materials. The comprehensive representation of available nutrient levels in the soils is as follows: gray-cinnamon soil and calcareous alluvial soil &gt; mountain meadow soil &gt; plateau prairie soil and brush prairie soil. The average MBC, MBN, and MBP contents in the five soils were 368.8 mg/kg, 28.4 mg/kg, and 23.6 mg/kg, respectively, and the content in the topsoil (0–20 cm) was higher than that of the subsoil (20–40 cm). The total nitrogen (PN), total phosphorus (PP), and total potassium (PK) contents in walnut leaves were found to be closely related to the soil physicochemical properties and microbial activity, among which five indicators, including soil TN, available nitrogen (AN), SOM, MBC, and slowly available potassium (SAK), had the greatest impact on leaf nutrient levels. These findings are valuable for the future management and development of walnut orchards. Therefore, for different soil parent materials and soil types, improving the soil fertility and actively applying nitrogen-rich organic fertilizers should be prioritized to improve the yield and quality of Tibetan Plateau walnuts.

In the Qaidam Basin, Soil Nutrients Directly or Indirectly Affect Desert Ecosystem Stability under Drought Stress through Plant Nutrients.

The low nutrient content of soil in desert ecosystems results in unique physiological and ecological characteristics of plants under long-term water and nutrient stress, which is the basis for the productivity and stability maintenance of the desert ecosystem. However, the relationship between the soil and the plant nutrient elements in the desert ecosystem and its mechanism for maintaining ecosystem stability is still unclear. In this study, 35 sampling sites were established in an area with typical desert vegetation in the Qaidam Basin, based on a drought gradient. A total of 90 soil samples and 100 plant samples were collected, and the soil's physico-chemical properties, as well as the nutrient elements in the plant leaves, were measured. Regression analysis, redundancy analysis (RDA), the Theil-Sen Median and Mann-Kendall methods, the structural equation model (SEM), and other methods were employed to analyze the distribution characteristics of the soil and plant nutrient elements along the drought gradient and the relationship between the soil and leaf nutrient elements and its impact on ecosystem stability. The results provided the following conclusions: Compared with the nutrient elements in plant leaves, the soil's nutrient elements had a more obvious regularity of distribution along the drought gradient. A strong correlation was observed between the soil and leaf nutrient elements, with soil organic carbon and alkali-hydrolyzed nitrogen identified as important factors influencing the leaf nutrient content. The SEM showed that the soil's organic carbon had a positive effect on ecosystem stability by influencing the leaf carbon, while the soil's available phosphorus and the mean annual temperature had a direct positive effect on stability, and the soil's total nitrogen had a negative effect on stability. In general, the soil nutrient content was high in areas with a low mean annual temperature and high precipitation, and the ecosystem stability in the area distribution of typical desert vegetation in the Qaidam Basin was low. These findings reveal that soil nutrients affect the stability of desert ecosystems directly or indirectly through plant nutrients in the Qaidam Basin, which is crucial for maintaining the stability of desert ecosystems with the background of climate change.

Smart Solutions for Sustainable Agriculture: Design and Development of IoT-Powered Soil Health Identification Systems

This research examines smart solutions for agricultural sustainability using IoT-powered soil health detection systems. Innovative solutions are needed to manage resources and protect the environment as the world population grows and agricultural resources are under strain. IoT-enabled soil health monitoring has great potential. The suggested system uses IoT sensors to measure soil moisture, pH, nutrient content, and temperature in real time. This data is analyzed using powerful data analytics and machine learning algorithms to provide farmers soil health information. Monitoring soil quality allows farmers to make educated irrigation, fertilization, and crop selection choices, optimizing resource use and yields while minimizing environmental effect. The study also examines sensor selection, data transmission methods, and data security for IoT-powered soil health detection systems. Widespread use of these technologies might boost agricultural output, lower input costs, and enhance food security. Finally, IoT-powered soil health detection systems are a major step toward agricultural sustainability. These devices enable precision farming that is ecologically friendly and profitable by giving real-time soil data. However, effective implementation would need agricultural value chain stakeholders to collaborate and continued research to address growing issues and possibilities.