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Assessment of Agricultural soil quality Indices Using Mechanistic Models

Open Journal of soil Science 2024年第6期14卷 333-352页

作者： Mohammadali Nikpey Javad Robatjazi Shahabeddin Garmehei Hendra Gonsalve W. Lasar Nguyen Khoi Nghia Benjamin Kwadwo Agyei Department of soil Science Faculty of Agriculture Tarbiat Modarres University Tehran Iran Texas A&M AgriLife Research Department of Soil and Crop Sciences Texas A&M University College Station TX USA Faculty of soil Sciences College of Agriculture Can Tho University Can Tho Vietnam Department of Plant Soil and Microbial Sciences Michigan State University East Lansing MI USA

Assessing soil quality is a critical strategy for diagnosing soil status and anticipating concerns in land use systems for agricultural sustainability. In this study, two soil quality assessment indices, the Integrated quality Index (IQI) and Nemoro quality Index (NQI), were employed using two indicator selection methods: Total Data Set (TDS) and Minimum Data Set (MDS), focusing on agricultural fields in Golestan province, Iran. A total of 89 soil samples were collected and analyzed for particle size distribution, organic carbon, calcium carbonate equivalent (CCE), electrical conductivity (EC), pH, and plant-essential nutrients, including nitrogen, phosphorus, potassium, zinc, copper, manganese, and iron. Principal component analysis (PCA) was used to extract MDS from TDS, and geostatistical adaptation and correlation analyses were performed to determine the optimal soil quality evaluation index. Our results show that the exponential model better suits the spatial structure of soil quality indicators (IQIMDS: 0.955). Conformity and correlation analyses indicate that the IQI index outperformed the NQI index in estimating soil quality. The superiority of the TDS technique over the MDS technique in terms of accuracy (IQITDSs kappa: 0.155). Linear relationships between different methods showed a higher correlation coefficient (R2 = 0.43) through the application of IQI. This study suggests the use of IQIMDS to provide a reliable measurement that is particularly useful in assessing the quality of agricultural soil.

关键词： soil quality Geographic Information System Integrated quality Index Nemoro quality Index

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soil quality estimation using environmental covariates and predictive models:an example from tropical soils of Nigeria

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Ecological Processes 2022年第1期11卷 946-967页

作者： Isong Abraham Isong Kingsley John Paul Bassey Okon Peter Ikor Ogban Sunday Marcus Afu Department of soil Science Faculty of AgricultureUniversity of CalabarCalabar PMB 1115Nigeria Department of soil Science and soil Protection Faculty of AgrobiologyFoodand Natural ResourcesCzech University of Life SciencesKamýcká12916500 PragueCzech Republic

Background:Information addressing soil quality in developing countries often depends on results from small experimental plots,which are later extrapolated to vast areas of agricultural land.This approach often results in misin-formation to end-users of land for sustainable soil nutrient management.The objective of this study was to estimate the spatial variability of soil quality index(SQI)at regional scale with predictive models using soil–environmental covariates.Methods:A total of 110 composite soil samples(0–30 cm depth)were collected by stratified random sampling schemes at 2–5 km intervals across the Cross River State,Nigeria,and selected soil physical and chemical properties were determined.We employed environmental covariates derived from a digital elevation model(DEM)and Senti-nel-2 imageries for our modelling regime.We measured soil quality using two approaches[total data set(TDS)and minimum data set(MDS)].Two scoring functions were also applied,linear(L)and non-linear(NL),yielding four indices(MDS_L,MDS_NL,TDS_L,and TDS_NL).Eleven soil quality indicators were used as TDS and were further screened for MDS using principal component analysis(PCA).Random forest(RF),support vector regression(SVR),regression kriging(RK),Cubist regression,and geographically weighted regression(GWR)were applied to predict SQI in unsampled locations.Results:The computed SQI via MDS_L was classified into five classes:≤0.38,0.38–0.48,0.48–0.58,0.58–0.68,and≥0.68,representing very low(classⅤ),low(classⅣ),moderate(classⅢ),high(classⅡ)and very high(classⅠ)soil quality,respectively.GWR model was robust in predicting soil quality(R^(2)=0.21,CCC=0.39,RMSE=0.15),while RF was a model with inferior performance(R^(2)=0.02,CCC=0.32,RMSE=0.15).soil quality was high in the southern region and low in the northern region.High soil quality class(>49%)and moderate soil quality class(>14%)dominate the study area in all predicted models used.Conclusions:Structural stability index,sand content,soil oganic carbon content,and mean weight diameter of a

关键词： Decision support system Geospatial technology Predictive model Remote sensing soil quality

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soil quality assessment for desertification based on multi-indicators with the best-worst method in a semi-arid ecosystem

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Journal of Arid Land 2023年第7期15卷 779-796页

作者： Orhan DENGİZ İnci DEMİRAĞTURAN Department of soil Science and Plant Nutrition Faculty of AgricultureOndokuz Mayıs UniversitySamsun-55139Turkey Department of Geography Faculty of EconomicAdministrative and Social SciencesSamsun UniversitySamsun-55030Turkey

Since there are some signs of land degradation and desertification showing how soil sustainability is threatened, it is crucial to create a soil quality index(SQI) model in the semi-arid ?orum Basin, situated between the Black Sea and Anatolia Region, Central Turkey. The primary aims of the study are:(1) to determine SQI values of the micro-basin in terms of land degradation and desertification.Moreover, the best-worst method(BWM) was used to determine the weighting score for each parameter;(2) to produce the soils' spatial distribution by utilizing different geostatistical models and GIS(geographic information system) techniques;and(3) to validate the obtained SQI values with biomass reflectance values. Therefore, the relationship of RE-OSAVI(red-edge optimized soil-adjusted vegetation index) and NDVI(normalized difference vegetation index) generated from Sentinel-2A satellite images at different time series with soil quality was examined. Results showed that SQI values were high in the areas that had almost a flat and slight slope. Moreover, the areas with high clay content and thick soil depth did not have salinity problems, and were generally distributed in the middle parts of the basin. However, the areas with a high slope, poor vegetation, high sand content, and low water holding capacity had low SQI values.Furthermore, a statistically high positive correlation of RE-OSAVI and NDVI indices with soil quality was found, and NDVI had the highest correlative value for June(R~2=0.802) compared with RE-OSAVI.

关键词： soil quality land degradation desertification best-worst method remote sensing

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Co-application of compost or inorganic NPK fertilizer with biochar influences soil quality,grain yield and net income of rice

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Journal of Integrative Agriculture 2022年第12期21卷 3600-3610页

作者： Christian Adler PHARES Selorm AKABA Department of soil Science School of AgricultureUniversity of Cape CoastGhana Department of Agriculture Economics and Extension School of AgricultureUniversity of Cape CoastGhana

Most agricultural soils in sub-Saharan Africa are degraded,compromising the grain yield of rice and farmers return on investment.A 3-year field study was undertaken to explore the effect of the application of compost or inorganic NPK fertilizer applied alone or in combination with biochar on soil quality,grain yield of rice and net income.The five treatments were laid out using a randomized complete block design with four replications.The treatments were applied to supply approximately 75 kg N ha–1.The best fertilizer input was compost+biochar which resulted in the greatest improvement in soil physico-chemical properties by reducing bulk density and increasing porosity and moisture retention,organic matter content,percent nitrogen,available phosphorus and cation exchange capacity.Apart from treatment with inorganic fertilizer alone,treated soils showed a decrease in pH.Bacterial and fungal counts and basal respiration decreased in soils in the following order:compost+biochar>compost only>inorganic NPK fertilizer+biochar>inorganic NPK fertilizer>control.The increase in pooled grain yield and net income in response to treatment followed the order:compost+biochar>NPK+biochar>NPK>compost>control.The findings suggest that the use of compost or NPK alone might improve soil quality and increase grain yield and net income,but it is greatly recommended to co-apply these fertilisers with biochar.

关键词： biochar compost inorganic NPK fertilizer biochar-enriched compost biochar-enriched NPK fertilizer soil quality net income rice yield

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A new hybrid approach to assessing soil quality using neutrosophic fuzzy-AHP and support vector machine algorithm in sub-humid ecosystem

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Journal of Mountain Science 2023年第11期20卷 3186-3202页

作者： ÖZKAN Barış DENGIZ Orhan ALABOZ Pelin KAYA NursaçSerda Department of Industrial Engineering Faculty of EngineeringOndokuz Mayis UniversitySamsun 55200Türkiye Department of soil Sciences and Plant Nutrition Faculty of AgricultureOndokuz Mayis UniversitySamsun 55200Türkiye Department of soil Science and Plant Nutrition Faculty of AgricultureIsparta University of Applied SciencesIsparta32000Türkiye

soil quality determination and estimation is an important issue not only for terrestrial ecosystems but also for sustainable management of soils.In this study,soil quality was determined by linear and nonlinear standard scoring function methods integrated with a neutrosophic fuzzy analytic hierarchy process in the micro catchment.In addition,soil quality values were estimated using a support vector machine(SVM)in machine learning algorithms.In order to generate spatial distribution maps of soil quality indice values,different interpolation methods were evaluated to detect the most suitable semivariogram model.While the soil quality index values obtained by the linear method were determined between 0.458-0.717,the soil quality index with the nonlinear method showed variability at the levels of 0.433-0.651.There was no statistical difference between the two methods,and they were determined to be similar.In the estimation of soil quality with SVM,the normalized root means square error(NRMSE)values obtained in the linear and nonlinear method estimation were determined as 0.057 and 0.047,respectively.The spherical model of simple kriging was determined as the interpolation method with the lowest RMSE value in the actual and predicted values of the linear method while,in the nonlinear method,the lowest error in the distribution maps was determined with exponential of the simple kriging.

关键词： soil quality Support vector machine Neutrosophic fuzzy Humid ecosystem

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The effects of crop rotation combinations on the soil quality of old apple orchard

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Horticultural Plant Journal 2022年第1期8卷 1-10页

作者： Haiyan Wang Yuefan Sheng Weitao Jiang Fengbing Pan Mei Wang Xuesen Chen Xiang Shen Chengmiao Yin Zhiquan Mao College of Horticultural Science and Engineering/State Key Laboratory of Crop Biology Shandong Agricultural UniversityTai’anShandong 271018China

This study investigated the effects of six crop rotation combinations on the soil quality of old apple orchard and seedling growth of Malus hupehensis Rehd.(apple rootstock) under pot conditions. The inhibitory effects of crops such as Allium fistulosum, Brassica juncea, and Triticum aestivum on four species of Fusarium were observed and compared in six treatments. These were continuous cropping(CK), fumigation with the methyl bromide(FM), rotating A. fistulosum only(R1), rotating A. fistulosum and T. aestivum(R2), rotating A. fistulosum, B. juncea, and T. aestivum(R3), and fallow(FC) in a year. The results showed that the biomass of Malus hupehensis Rehd. seedlings increased significantly. The root length increased and the root architecture was optimized. The respiration rate of the root system was increased by about 1 time after rotation. The treatments of R1, R2, R3, and FC increased bacterial count by 232.17%, 96.04%, 316.21%, and 60.02%, respectively. However, the fungi were reduced in varying degrees and bacteria/fungi ratio was increased by 5–10 times. The enzyme activities, p H, and organic matter were increased, but soil bulk density was decreased. Phenolic acids such as phloridzin was decreased significantly. The copy number of four Fusarium species declined by 85.59%, 74.94%, 69.68%, and 54.41% after rotating three different crops(R3 treatment). The root volatiles of three plants inhibited mycelial growth and spore germination of four Fusarium species.

关键词： Apple replant disease Rotation Malus hupehensis Rehd Seedlings soil quality Microorganism

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Improved soil quality Prediction Model Using Deep Learning for Smart Agriculture Systems

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Computer Systems Science & Engineering 2023年第5期45卷 1545-1559页

作者： P.Sumathi V.V.Karthikeyan M.S.Kavitha S.Karthik Department of Information Technology SNS College of EngineeringCoimbatoreTamilnaduIndia Department of Electrical and Electronics Engineering SNS College of TechnologyCoimbatoreTamilnaduIndia Department of Computer Science&Engineering SNS College of TechnologyCoimbatoreTamilnaduIndia

soil is the major source of infinite lives on Earth and the quality of soil plays significant role on Agriculture practices all around.Hence,the evaluation of soil quality is very important for determining the amount of nutrients that the soil require for proper yield.In present decade,the application of deep learning models in many fields of research has created greater impact.The increasing soil data availability of soil data there is a greater demand for the remotely avail open source model,leads to the incorporation of deep learning method to predict the soil quality.With that concern,this paper proposes a novel model called Improved soil quality Prediction Model using Deep Learning(ISQP-DL).The work considers the chemical,physical and biological factors of soil in particular area to estimate the soil quality.Firstly,pH rating of soil samples has been collected from the soil testing laboratory from which the acidic range has been categorized through soil test and the same data has been taken as input to the Deep Neural Network Regression(DNNR)model.Secondly,soil nutrient data has been given as second input to the DNNR model.By utilizing this data set,the DNNR method is used to evaluate the fertility rate by which the soil quality has been estimated.For training and testing,the model uses Deep Neural Network Regression(DNNR),by utilizing the dataset.The results show that the proposed model is effective for SQP(soil quality Prediction Model)with efficient good fitting and generality is enhanced with input features with higher rate of classification accuracy.The results show that the proposed model achieves 96.7%of accuracy rate compared with existing models.

关键词： soil quality classification accuracy deep learning neural network soil features training and testing

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Effect of biochar application method and amount on the soil quality and maize yield in Mollisols of Northeast China

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Biochar 2022年第1期4卷 240-254页

作者： Sihua Yan Shaoliang Zhang Pengke Yan Muhammad Aurangzeib Northeast Agricultural University 600 Changjiang RdHarbin 150030People’s Republic of China

There have been many studies on soil quality and crop yield using different biochar application amounts,but few studies have focused on the combination of different methods and amounts of biochar application in moderately degraded Mollisols.In this study,the methods of mixing biochar evenly with the soil of the plough layer(0-20 cm depth)[homogeneous biochar application(HO)]and burying biochar above the soil plow pan(under 20 cm depth)(heterogeneous biochar application(HE))were used to reveal how biochar application methods influenced soil quality,crop yield and agronomic characteristics in moderately degraded Mollisols(soil organic matter(SOM),30.33 g kg^(−1)).The biochar application amounts were 0(control),10(level 1),20(level 2),and 40(level 3)t ha^(−1)in both the HO and HE treatments.The results showed that,compared with control,HO3 significantly increased maize yield in the first year,and HO2,HO3,HE2 and HE3 continuously increased maize yield in the next three years but not significantly.HO1 and HE1 had the lowest maize yield.HO2 tended to delay maize leaf senescence.There was a posi-tive linear relationship between soil quality index(SQI)and biochar application amount in HO.Compared with other treatments,the pH,EC,SOM,available phosphorus,sucrase and catalase activities were highest in HO3.However,the effects of HE on soil quality and crop productivity were limited at first but gradually increased with time.Overall,HO3 was beneficial for improving the soil quality and crop productivity in Mollisols for short-term cultivation(3-year),while HE showed an effect over time.

关键词： Biochar Mollisols conservation Crop growth Maize yield soil quality

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The age and quality of pond bottom soil affect water quality and production of Pangasius hypophthalmus in the tropical environment

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Aquaculture and Fisheries 2023年第3期8卷 296-304页

作者： Saberina Hasibuan Syafriadiman Syafriadiman Netti Aryani Muhammad Fadhli Monalisa Hasibuan Environmental quality Laboratory Department of Aquaculture Faculty of Fisheries and Marine SciencesUniversity of RiauPekanbaru28293Indonesia Department of Aquaculture Faculty of Fisheries and Marine Sciences University of RiauPekanbaru28293Indonesia Graduate of Aquaculture Faculty of Fisheries and Marine Sciences University of RiauPekanbaru28293Indonesia Researcher at the Board of Research and Development of Riau Province Indonesia

Pangasius hypophthalmus is the most cultured freshwater fish by smallholder farmers in Indonesia.One of the main challenges in the production is the highly weathered and infertile soils on the bottom of a pond that influences aquaculture productivity.This work investigated the effects of pond age on soil quality,water quality,benthic algae population,and P.hypophthalmus production.We carried out a field experiment in a randomized design with pond age of 4 levels:Ponds aged 0-5 years(P1),6-10 years(P2),11-15 years(P3),and 16-20 years(P4).The soil is a Typic Palaeudult(Ultisol),and fish were grown for three months.The results showed that the chemical soil quality parameters and soil organic matter content increased linearly with pond age,resulting in the enhancement of water quality parameters.The increase in nitrate and phosphate directly affected benthic algae richness.These,in turn,in the highest fish production in P3,6.4 kg/m^(2),specific growth rate was 3.76%/d,survival rate of 66.7%,and feed conversion ratio of 1.8%.Linear correlation coefficients indicated that the contents of total N,total P,and organic carbon in the bottom soil of the pond were related to the increase in phosphate,nitrate,and organic matter content in pond water.Total N content,total P,carbon organic matter,C/N ratio,and CEC value in pond bottom soil significantly correlated to Pangus fish production.C/N ratio,CEC value in pond bottom soil,and CO_(2)concentration in pond water significantly correlated to fish survival rate.Multiple linear regression indicated that fish production was significantly related to the pond age,water NH3,total alkalinity,and soil total P and C/N ratio(R^(2)=0.99,Psoil C/N ratio caused a negative effect on fish production.The results suggested that old-aged ponds,with proper management,act as a nutrient sink,resulting in increased aquaculture production.The implementation of the best practices will benefit the Pangus culture in the tropical environment.

关键词： Benthic algae Production soil pond soil quality Sediment-water interface

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Coupling of reduced inorganic fertilizer with plant-based organic fertilizer as a promising fertilizer management strategy for colored rice in tropical regions

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Journal of Integrative Agriculture 2024年第1期23卷 93-107页

作者： Tingcheng Zhao Aibin He Mohammad Nauman Khan Qi Yin Shaokun Song Lixiao Nie Research Center for Physiology and Ecology and Green Cultivation of Tropical Crops School of Breeding and Multiplication(Sanya Institute of Breeding and Multiplication)Hainan UniversitySanya 572000China

Colored rice is a type of high-quality,high-added-value rice that has attracted increasing attention in recent years.The use of large amounts of inorganic nitrogen fertilizer in rice fields results in low fertilizer use efficiency and high environmental pollution.Organic fertilizer is a promising way to improve soil quality and sustain high yields.However,most studies focus on the effect of animal-based organic fertilizers.The effects of different ratios of plantbased organic fertilizer and inorganic fertilizer on the grain yield and quality of colored rice have rarely been reported.Therefore,a two-year field experiment was conducted in 2020 and 2021 to study the effects of replacing inorganic N fertilizers with plant-based organic fertilizers on the yield,nitrogen use efficiency(NUE),and anthocyanin content of two colored rice varieties in a tropical region in China.The experimental treatments included no nitrogen fertilization(T1),100% inorganic nitrogen fertilizer(T2),30%inorganic nitrogen fertilizer substitution with plant-based organic fertilizer(T3),60%inorganic nitrogen fertilizer substitution with plant-based organic fertilizer(T4),and 100% plantbased organic fertilizer(T5).The total nitrogen provided to all the treatments except T1 was the same at 120 kg ha-1.Our results showed that the T3 treatment enhanced the grain yield and anthocyanin content of colored rice by increasing nitrogen use efficiency compared with T2.On average,grain yields were increased by 9 and 8%,while the anthocyanin content increased by 16 and 10% in the two colored rice varieties under T3 across the two years,respectively,as compared with T2.Further study of the residual effect of partial substitution of inorganic fertilizers showed that the substitution of inorganic fertilizer with plant-based organic fertilizer improved the soil physiochemical properties,and thus increased the rice grain yield,in the subsequent seasons.The highest grain yield of the subsequent rice crop was observed under the T5 treatment.Our results suggested t

关键词： colored rice organic fertilizer soil quality grain yield anthocyanin

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