Increasing contribution of microbial residues to soil organic carbon in grassland restoration chronosequence

Yang, Yang; Dou, Yanxing; Wang, Baorong; Wang, Yunqiang; Liang, Chao; An, Shaoshan; Soromotin, Andrey; Kuzyakov, Yakov

doi:10.1016/j.soilbio.2022.108688

Cited by 90 publications

(42 citation statements)

References 82 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…It has been observed that on high-pH soils (pH > 7), phosphorus and iron become limitedly available nutrients because of their decrease in solubility and thus affecting on species diversity of an area. Slope facing to poles are wetland cool, with rich organic matter and deeper soil and characterized by mesic vegetation, while the slope facing toward equator are usually hot and xeric type with low soil nutrients and thus having severe erosion, subsequently they are supporting xeric type of vegetation 44 , 45 . It has a common observation that sunny slope retains less moisture compared to shady slope, because of greater solar radiation and high evaporation.…”

Section: Introductionmentioning

confidence: 99%

Vegetation assessments under the influence of environmental variables from the Yakhtangay Hill of the Hindu-Himalayan range, North Western Pakistan

Ullah

Khan

Jaremko

et al. 2022

Sci Rep

View full text Add to dashboard Cite

Vegetation structures and dynamics are the result of interactions between abiotic and biotic factors in an ecosystem. The present study was designed to investigate vegetation structure and species diversity along various environmental variables in the Yakhtangay Hills of the Hindu-Himalayan Mountain Pakistan, by using multivariate statistical analysis. Quadrat quantitative method was used for the sampling of vegetation. PC-ORD version 5 software was used to classify the vegetation into different plants communities using cluster analysis. The results of regression analysis among various edaphic variables shows that soil organic matter, total dissolved solids, electrical conductivity, CaCO3 and moisture contents shows a significant positive correlation with species abundance, while the soil pH has inverse relationship with plant species abundance. Similarly, species richness increases with increase in soil organic matter, CaCO3 and moisture contents, while decrease with increase in soil pH, total dissolved solids and electrical conductivity (p < 0.05). The vegetation was classified into four major plant communities and their respective indicators were identified using indicator species analysis. Indicator species analysis reflects the indicators of the study area are mostly the indicators to the Himalayan or moist temperate ecosystem. These indicators could be considered for micro-habitat conservation and respective ecosystem management plans not only in the study area but also in other region with similar sort of environmental conditions.

show abstract

Section: Introductionmentioning

confidence: 99%

Vegetation assessments under the influence of environmental variables from the Yakhtangay Hill of the Hindu-Himalayan range, North Western Pakistan

Ullah

Khan

Jaremko

et al. 2022

Sci Rep

View full text Add to dashboard Cite

show abstract

“…Singh and Kumar, 2021). Such a phenomenon is termed as enhanced stimulation defense mechanisms of a plant (Anderson et al, 2017;Yang et al, 2022). Seed priming decreases the time duration between planting and the emergence of a seed.…”

Section: Seed Priming Crosstalk With Salinity Tolerancementioning

confidence: 99%

A practical and economical strategy to mitigate salinity stress through seed priming

Khan

Irfan

Asim

et al. 2022

Front. Environ. Sci.

View full text Add to dashboard Cite

Soil salinity is one of the significant abiotic threats to crops that deteriorates crop yields, and the world’s increasing population faces serious food problems due to abiotic threats. It is one of the major abiotic problems affecting more than 30% of irrigated land across the globe. The concentrations of various salts, such as NaCl, KCl, Na2SO4, and Na2CO3, cause saline stress; however, NaCl is the most abundant salt in the soil. Salinity could affect seed germination due to osmotic potential or due to specific toxic ion effects, and it decreases germination percentage and increases germination time, and high salt stress is responsible for delaying seed germination. Therefore, it is necessary to alleviate the negative impact of soil salinity during seedling growth periods, so the growth of crops in salt-affected soil will be much more enhanced. Seed priming is the utmost effective technique that could mitigate the harmful impact of soil salinity. This methodology not only minimizes the salinity tolerance but also strengthens the defense system of crops. In this technique, the hydration level within the seeds is controlled by applying pre-sowing treatments, allowing specific pre-germinative metabolic processes to occur and preventing radical emergence. Seed priming also decreases the seed germination time and improves antioxidant enzyme activities, stopping or minimizing reactive oxygen species’ adverse effects. It enhances the seedling performance with rapid and homogenous germination and vigorous and dynamic growth of the seedling, achieving a physiological situation leading to quick and enhanced emergence and germination of various crops. This review covers the mechanisms of seed priming, salinity tolerance, seed priming crosstalk with salinity tolerance, and seed priming techniques that induce biochemical, physiological, and morphological mechanisms in saline stress. Further research needs to be performed on advanced seed priming methods such as priming with nanoparticles and seed priming with physical agents (UV radiation, X-rays, gamma rays, and microwaves) to minimize the negative impact of salinity stress on different crops under different harsh environmental conditions.

show abstract

“…Comparing the proposed traceability system with the traceability system constructed by Yang et al [ 37 ], the advantage of the proposed system is that the system solves the problems of asymmetric information, difficult sharing, easy tampering, and centralized storage in the IoT-based agricultural products traceability system of previous researchers, thus making the whole chain of agricultural product information credible and reliable [ 38 – 42 ]. Meanwhile, the proposed system also overcomes the common problems of information storage isolation, data sharing of information systems, and difficult interaction in the traceability of traditional agricultural products [ 43 – 47 ].…”

Section: Traceability Experiments Using Blockchainmentioning

confidence: 99%

Implementation of Trusted Traceability Query Using Blockchain and Deep Reinforcement Learning in Resource Management

Jiang

Lei

2022

Computational Intelligence and Neuroscience

View full text Add to dashboard Cite

To better track the source of goods and maintain the quality of goods, the present work uses blockchain technology to establish a system for trusted traceability queries and information management. Primarily, the analysis is made on the shortcomings of the traceability system in the field of agricultural products at the present stage; the study is conducted on the application of the traceability system to blockchain technology, and a new model of agricultural product traceability system is established based on the blockchain technology. Then, a study is carried out on the task scheduling problem of resource clusters in cloud computing resource management. The present work expands the task model and uses the deep Q network algorithm in deep reinforcement learning to solve various optimization objectives preset in the task scheduling problem. Next, a resource management algorithm based on a deep Q network is proposed. Finally, the performance of the algorithm is analyzed from the aspects of parameters, structure, and task load. Experiments show that the algorithm is better than Shortest Job First (SJF), T e t r i s ∗ , Packer, and other classic task scheduling algorithms in different optimization objectives. In the traceability system test, the traceability accuracy is 99% for the constructed system in the first group of samples. In the second group, the traceability accuracy reaches 98% for the constructed system. In general, the traceability accuracy of the system proposed here is above 98% in 8 groups of experimental samples, and the traceability accuracy is close for each experimental group. The resource management approach of the traceability system constructed here provides some ideas for the application of reinforcement learning technology in the construction of traceability systems.

show abstract

Increasing contribution of microbial residues to soil organic carbon in grassland restoration chronosequence

Cited by 90 publications

References 82 publications

Vegetation assessments under the influence of environmental variables from the Yakhtangay Hill of the Hindu-Himalayan range, North Western Pakistan

Vegetation assessments under the influence of environmental variables from the Yakhtangay Hill of the Hindu-Himalayan range, North Western Pakistan

A practical and economical strategy to mitigate salinity stress through seed priming

Implementation of Trusted Traceability Query Using Blockchain and Deep Reinforcement Learning in Resource Management

Contact Info

Product

Resources

About