Co-incorporating green manure and crop straw increases crop productivity and improves soil quality with low greenhouse-gas emissions in a crop rotation

In a nine-year field experiment in a wheat-maize-sunflower cropping system in Hetao Irrigation Area,Inner Mongolia,China,organic amendments applied as straw,manure,green manure,and the combination of green manure and straw increased wheat and maize yield,soil aggregate stability,and soil microbial activity in comparison with chemical fertilizer,without changing greenhouse gas emission intensity.

Effect of fertigation frequency on soil nitrogen distribution and tomato yield under alternate partial root-zone drip irrigation

Alternate partial root-zone drip fertigation (ADF) is a combination of alternating irrigation and drip fertigation,with the potential to save water and increase nitrogen (N) fertilizer efficiency.A 2-year greenhouse experiment was conducted to evaluate the effect of different fertigation frequencies on the distribution of soil moisture and nutrients and tomato yield under ADF.The treatments included three ADF frequencies with intervals of 3 days (F3),6 days (F6) and 12 days (F12),and conventional drip fertigation as a control (CK),which was fertilized once every 6 days.For the ADF treatments,two drip tapes were placed 10 cm away on each side of the tomato row,and alternate drip irrigation was realized using a manual valve on the distribution tapes.For the CK treatment,a drip tape was located close to the roots of the tomato plants.The total N application rate of all treatments was 180 kg ha^(-1).The total irrigation amounts applied to the CK treatment were450.6 and 446.1 mm in 2019 and 2020,respectively;and the irrigation amounts applied to the ADF treatments were 60%of those of the CK treatment.The F3 treatment resulted in water and N being distributed mainly in the 0–40-cm soil layer with less water and N being distributed in the 40–60-cm soil layer.The F6 treatment led to 21.0 and 29.0%higher 2-year average concentration of mineral N in the 0–20 and 20–40-cm soil layer,respectively and a 23.0%lower N concentration in the 40–60-cm soil layer than in the CK treatment.The 2-year average tomato yields of the F3,F6,F12,and CK treatments were 107.5,102.6,87.2,and 98.7 t ha^(-1),respectively.The tomato yield of F3 was significantly higher (23.3%) than that in the F12 treatment,whereas there was no significant difference between the F3 and F6 treatment.The F6 treatment resulted in yield similar to the CK treatment,indicating that ADF could maintain tomato yield with a 40%saving in water use.Based on the distribution of water and N,and tomato yield,a fertigation frequency of 6 days under ADF should be considered as a water-saving strategy for greenhouse tomato production.

The changes in soil organic carbon stock and quality across a subalpine forest successional series

Soil organic carbon(SOC)affects the function of terrestrial ecosystem and plays a vital role in global carbon cycle.Yet,large uncertainty still existed regarding the changes in SOC stock and quality with forest succession.Here,the stock and quality of SOC at 1-m soil profile were investigated across a subalpine forest series,including shrub,deciduous broad-leaved forest,broadleaf-conifer mixed forest,middle-age coniferous forest and mature coniferous forest,which located at southeast of Tibetan Plateau.The results showed that SOC stock ranged from 9.8 to29.9 kg·m^(-2),and exhibited a hump-shaped response pattern across the forest successional series.The highest and lowest SOC stock was observed in the mixed forest and shrub forest,respectively.The SOC stock had no significant relationships with soil temperature and litter stock,but was positively correlated with wood debris stock.Meanwhile,the average percentages of polysaccharides,lignins,aromatics and aliphatics based on FTIR spectroscopy were 79.89%,0.94%,18.87%and 0.29%,respectively.Furthermore,the percentage of polysaccharides exhibited an increasing pattern across the forest successional series except for the sudden decreasing in the mixed forest,while the proportions of lignins,aromatics and aliphatics exhibited a decreasing pattern across the forest successional series except for the sudden increasing in the mixed forest.Consequently,the humification indices(HIs)were highest in the mixed forest compared to the other four successional stages,which means that the SOC quality in mixed forest was worse than other successional stages.In addition,the SOC stock,recalcitrant fractions and HIs decreased with increasing soil depth,while the polysaccharides exhibited an increasing pattern.These findings demonstrate that the mixed forest had higher SOC stock and worse SOC quality than other successional stages.The high proportion of SOC stock(66%at depth of 20-100 cm)and better SOC quality(lower HIs)indicate that deep soil have tremendous potential to store SOC and needs more attention under global chan ge.

In situ digital testing method for quality assessment of soft soil improvement with polyurethane

This study purposes an in situ testing method on quality assessment of soil improvement.Factual drilling data includes the spatial distribution and in situ strength of untreated and treated soil along three different drillholes measured by on-site drilling monitoring method.These factual drilling data can characterize the degree of soil improvement by penetration injection with permeable polyurethane.Result from on-site drilling monitoring shows that the linear zones represent constant drilling speeds shown in the plot of drill bit advancement vs.net drilling time,which indicates the spatial distributions of soil profile.The soil profile at the study site is composed of four layers,which includes fill,untreated silty clay,treated silty clay,and mucky soil.The results of soil profile are verified by the parallel site loggings.The constant drilling speeds profile the coring-resistant strength of drilled soils.By comparing with the untreated silty clay,the constant drilling speeds of the treated silty clay have been decreased by 13.0-62.8%.Two drilling-speed-based indices of 61.2%and 65.6%are proposed to assess the decreased average drilling speed and the increased in situ strength of treated silty clay.Laboratory tests,i.e.uniaxial compressive strength(UCS)test,have been performed with core sample to investigate and characterize in situ strength by comparing that with drilling speeds.Results show that the average predicted strengths of treated silty clay are 2.4-6.9 times higher than the average measured strength of untreated silty clay.The UCS-based indices of 374.5%and 344.2%verified the quality assessment(QA)results by this new in situ method.This method provides a cost-effective tool for quality assessment of soil improvement by utilizing the digital drilling data.

Multivariate Approach to Characterizing Soil Quality of Gabonese’s Ferralitic Soils

Assessing soil quality is essential for crop management and soil temporal changes. The present study aims to evaluate soil quality in the Ferralitic soils context countrywide. This assessment was done using multivariate soil quality indice (SQI) models, such as additive quality index (AQI), weighted quality indexes (WQIadd and WQIcom) and Nemoro quality index (NQI), applied to two approaches of indicator selection: total data set (TDS) and minimum data set (MDS). Physical and chemical soil indicators were extracted from the ORSTOM’s reports resulting from a sampling campaign in different provinces of Gabon. The TDS approach shows soil quality status according to eleven soil indicators extracted from the analysis of 1,059 samples from arable soil layer (0 - 30 cm depth). The results indicated that 87% of all provinces presented a very low soil quality (Q5) whatever the model. Among soil indicators, exchangeable K+ and Mg2+, bulk density and C/N ratio were retained in MDS, using principal component analysis (PCA). In the MDS approach, 50 to 63% of provinces had low soil quality grades with AQI, WQIadd and NQI, whereas the total was observed with WQIcom. Only 25% of provinces had medium soil quality grades with AQI and NQI models, while 12.5% (NQI) and 25% (AQI) presented high quality grades. Robust statistical analyses confirmed the accuracy and validation (0.80 r P ≤ 0.016) of AQI, WQIadd and NQI into the TDS and MDS approaches. The same sensitivity index value (1.53) was obtained with AQI and WQIadd. However, WQIadd was chosen as the best SQI model, according to its high linear regression value (R2 = 0.82) between TDS and MDS. This study has important implications in decision-making on monitoring, evaluation and sustainable management of Gabonese soils in a pedoclimatic context unfavorable to plant growth.

Assessment of Agricultural Soil Quality Indices Using Mechanistic Models

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.

Prediction of Apple Fruit Quality by Soil Nutrient Content and Artificial Neural Network

The effect of soil nutrient content on fruit yield and fruit quality is very important.To explore the effect of soil nutrients on apple quality we investigated 200 fruit samples from 40 orchards in Feng County,Jiangsu Province.Soil mineral elements and fruit quality were measured.The effect of soil nutrient content on fruit quality was analyzed by artificial neural network(ANN)model.The results showed that the prediction accuracy was highest(R2=0.851,0.847,0.885,0.678 and 0.746)in mass per fruit(MPF),hardness(HB),soluble solids concentrations(SSC),titratable acid concentration(TA)and solid-acid ratio(SSC/TA),respectively.The sensitivity analysis of the prediction model showed that soil available P,K,Ca and Mg contents had the greatest impact on the quality of apple fruit.Response surface method(RSM)was performed to determine the optimum range of the available P,K,Ca,and Mg contents in orchards In Feng County,which were 10∼20 mg⋅kg^(−1),170∼200 mg⋅kg^(−1),1000∼1500 mg⋅kg^(−1),and 80∼200 mg⋅kg^(−1),respectively.The research also concluded that improving the content of available P and available Ca in orchard soil was crucial to improve apple fruit quality in Feng County,Jiangsu Province.

Evaluation and Driving Force Analysis of Cultivated Land Quality in Black Soil Region of Northeast China

Cultivated land is an important natural resource to ensure food,ecological and economic security.The cultivated land quality evaluation(CQE)is greatly significant for protecting and managing cultivated land.In this study,320 counties in the black soil region of Northeast China(BSRNC)represent the research units used to construct the CQE system measuring the soil properties(SP),cultivated land productivity(CLP),ecological environment(EE)and social economy(SE).The total of 19 factors were selected to calculate the integrated fertility index(IFI)and divided into grades.Simultaneously,we used the coupling coordination degree model to comprehensively analyze the spatial pattern of the cultivated land quality(CLQ)in the BSRNC,and use the structural equation model(SEM)to analyze the driving mechanism.The results show the following:1)The CLQ of 262 counties in the BSRNC is in a state of coupling and coordination,and the coupling and coordination degree presents a spatial distribution pattern of‘high in the southwest and northeast,low in the northwest and southeast’.The coordinated development degree of 271 counties is between 0.4 and 0.6,which is in a transitional state between coordination and disorder.2)The CLQ in the BSRNC is generally good,with an average grade of 3.High-quality cultivated land accounts for 58.45%of all counties,middle-and upper-quality cultivated land accounts for 27.05%,and poor-quality cultivated land accounts for 14.49%.3)The SEM analysis shows that the SP,CLP,EE,and SE all influence the CLQ.Among them,the SP has the largest driving force on the CLQ,while the SE has the smallest driving force on it.The results confirm that the main factors affecting the evaluation results are crop productivity level,normalized difference vegetation index,ratio vegetation index,difference vegetation index,and organic carbon content.When implementing protection measures in counties with a low CLQ,considering a balanced coordination of multiple systems and reasonably controlling the quality degradation are important.This study provides the current situation and driving factors of the CLQ in the BSRNC and will play an important role in black soil governance and utilization.

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

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.

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

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.

Improved Soil Quality Prediction Model Using Deep Learning for Smart Agriculture Systems

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.

Effects of Microbial Fertilizers in Improving Acidic Tobacco-planting Soil and Tobacco Leaf Quality

[Objectives]This study was conducted to improve acidic soil and enhance the quality of tobacco leaves.[Methods]The effects of different microbial fertilizers on improving acidic tobacco-planting soil and tobacco leaf quality were investigated through plot experiments.[Results]The application of microbial fertilizers could improve the pH value of acidic soil,and composite microbial agent A showed the best application effect.The application of bio-organic fertilizer was beneficial to improving the contents of available phosphorus and available boron in acidic soil.The application of composite microbial agent A was beneficial to improving the contents of available phosphorus and available potassium in acidic soil,and could promote the growth of tobacco plants and improve the economic traits of flue-cured tobacco and the coordination of chemical components in tobacco leaves.The application of composite microbial agent B led to a downward trend in the content of available boron in acidic soil.The application of composite microbial agent B could promote the absorption of nutrients by tobacco plants,and improve their disease resistance and the quality of tobacco leaves.Due to the differences in functional microorganisms contained,the application effects of different microbial fertilizers in improving acidic tobacco-planting soil and improving tobacco leaf quality varied.Overall,the application of microbial fertilizers could increase soil pH,activate soil nutrients,promote tobacco growth,enhance disease resistance,increase tobacco output value,and improve tobacco quality.Microbial fertilizers have good application prospects in improving acidic soil and improving tobacco quality.[Conclusions]The application of microbial fertilizers to improve acidic tobacco-planting soil can ensure the normal growth and development of tobacco plants and the improvement of tobacco leaf quality,achieving high-quality and sustainable development of Zhaotong tobacco.

Soil Organic Carbon Stock and Soil Quality under Four Major Agroecosystems in the Eastern Flank of Mount Bambouto (West-Cameroon)

Assessing soil organic carbon stock (SOCS) and soil quality (SQ) helps design better agricultural practices to improve environmental sustainability and productivity. The purpose of the study is to assess SOCS and soil quality SQ in the main agroecosystems (AES) of the eastern flank of Mount Bambouto (West, Cameroon). Using multiple statistics tests and principal component analysis (PCA), SOCS and Soil Quality Index (SQI) were computed for each AES. SOCS and SQI were computed based on soil chemical properties and analysis of variance. Topsoil samples (0 - 30 cm) were collected in a different AES and analyzed in the laboratory. The four AES identified and selected are cultivated land (CL), forest areas (FA), mixed areas (MA), and bush areas (BA). Further, multiple comparison tests were used to compare soils from different AES. PCA was used to select the most appropriate indicators that control SOCS and SQ. Several soil properties showed high to very high coefficient of variation within the AES. Organic matter (OM) was significantly high in FA. SOCS and SQ differ significantly (p = 0.000) between the AES. The study further indicates that the main variables controlling SQ within the eastern flank of Mount Bambouto are OM, pHw, N, C/N, and CEC. While the main soil parameters controlling SOCS are OM, OC, BD, C/N, S, and pHKCl.

Geochemical Characterization of Soils in the Playa Lake Environment of Laguna de Encinillas, Chihuahua, Mexico

Laguna de Encinillas, located in Chihuahua, Mexico, is an ephemeral lake situated within a playa lake sedimentary depositional environment. This region plays a significant role in the aquifer supplying water to Chihuahua City. A surficial soil sampling campaign was conducted in 2017, 2018, and 2021 to assess the potential impact of surface soil composition on groundwater quality. The collected soil samples were analyzed using inductively coupled plasma mass spectrometry (ICP-MS) following microwave-assisted digestion. The analytical results were employed to generate spatial distribution maps of elemental concentrations using QGIS, applying interpolation methods such as inverse distance weighting (IDW) and Kriging. The analysis revealed elevated concentrations of beryllium (Be), calcium (Ca), cadmium (Cd), chromium (Cr), magnesium (Mg), and strontium (Sr) in the eastern part of the study area. In contrast, arsenic (As) and iron (Fe) were more prevalent in the western sector. Notably, high levels of barium (Ba), silver (Ag), cobalt (Co), potassium (K), and scandium (Sc) were identified in the northeastern region. At the same time, nickel (Ni), titanium (Ti), and vanadium (V) were concentrated in the northern portion. Manganese (Mn) was particularly prominent in the southern area. The geogenic source of these elements is likely linked to the volcanic rocks from the surrounding mountain ranges.

Rice Cultivation under Film Mulching Can Improve Soil Environment and Be Beneficial for Rice Production in China

Rice cultivation under film mulching is an integrated management technology that can conserve water, increase soil temperature, improve yield, and enhance water and nitrogen use efficiencies. Despite these advantages, the system does have its drawbacks, such as soil organic matter reduction and microplastic pollution, which impede the widespread adoption of film mulching cultivation in China. Nonetheless, the advent of degradable film, controlled-release fertilizer, organic fertilizer, and film mulching machinery is promoting the development of rice film mulching cultivation. This review outlines the impact of rice cultivation under film mulching on soil moisture, soil temperature, soil fertility, greenhouse gas emissions, weed control, and disease and pest management. It also elucidates the mechanism of changes in rice growth, yield and quality, water use efficiency, and nitrogen use efficiency. This paper incorporates a review of published research articles and discusses some uncertainties and shortcomings associated with rice cultivation under film mulching. Consequently, prospective research directions for the technology of rice film mulching cultivation are outlined, and recommendations for future research into rice cultivation under film mulching are proposed.

Differential Expression of Genes Related to Fruit Development and Capsaicinoids Synthesis in Habanero Pepper Plants Grown in Contrasting Soil Types

Habanero pepper(Capsicum chinense Jacq.)is a crop of economic relevance in the Peninsula of Yucatan.Its fruits have a high level of capsaicinoids compared to peppers grown in other regions of the world,which gives them industrial importance.Soil is an important factor that affects pepper development,nutritional quality,and capsaicinoid content.However,the effect of soil type on fruit development and capsaicinoid metabolism has been little understood.This work aimed to compare the effect of soils with contrasting characteristics,black soil(BS)and red soil(RS),on the expression of genes related to the development of fruits,and capsaicinoid synthesis using a transcriptomic analysis of the habanero pepper fruits.Plants growing in RS had bigger fruits and higher expression of genes related to floral development,fruit abscission,and softening which suggests that RS stimulates fruit development from early stages until maturation stages.Fruits from plants growing in BS had enrichment in metabolic pathways related to growth,sugars,and photosynthesis.Besides,these fruits had higher capsaicinoid accumulation at 25 days post-anthesis,and higher expression of genes related to the branched-chain amino acids metabolism(ketol-acid reductisomerase KARI),pentose phosphate pathway and production of NADPH(glucose-6-phosphate-1-dehydrogenase G6PDH),and proteasome and vesicular traffic in cells(26S proteasome regulatory subunit T4 RPT4),which suggest that BS is better in the early stimulation of pathways related to the nutritional quality and capsaicinoid metabolism in the fruits.

Effects of Fungi Fusarium sp. to Rhizosphere Soil and Physiological Characteristics of Camellia oleifera Abel.

[Objectives]To study the effects of fungi Fusarium sp.to rhizosphere soil and physiological characteristics of Camellia oleifera Abel.[Methods]We investigated the effects of Fusarium sp.to rhizosphere soil nutrient element content and metabolites of C.oleifera.C.oleifera was inoculated with the suspension of Fusarium sp.in pot experiments and ammonium-N,available phosphorus,available potassi-um,organic matter,enzymes and pH of rhizosphere soil,MDA content,activity of SOD,POD of C.oleifera leaves were analyzed.[Results]Fusarium sp.stress significantly inhibited soil enzyme activities and significantly reduced available phosphorus content,especially for phospha-tase and sucrase.Antioxidant enzyme activities in C.oleifera tissues showed that Fusarium sp.stress significantly increased MDA and SOD enzyme activities and decreased POD enzyme activity.Especially,SOD enzyme activity was elevated by 53.86%compared with the CK group.In addition,analysis of the content of major metabolites in C.oleifera leaves showed that Fusarium sp.stress significantly reduced the content of total flavonoids,quercetin,isoquercitrin and isoquercitrin in C.oleifera leaves by 7.80%,50.00%and 75.90%,respectively.[Conclusions]Our results are an important step which showed strong resistance of C.oleifera and can give a novel insight for researches on the effects in the rhizosphere soil enzyme,soil nutrient elements and metabolites of C.oleifera under the Fusarium sp.too.

Geogenic Pollution of Groundwater Quality in Gampaha District, Sri Lanka: A Case Study of Groundwater Acidification from Rathupaswala

Over recent decades, Gampaha district, Sri Lanka, has experienced significant urbanisation and industrial growth, increasing groundwater demand due to limited and polluted surface water resources. In 2013, a community uprising in Rathupaswala, a village in Gampaha district, accused a latex glove manufacturing factory of causing groundwater acidity (pH < 4). This study evaluates the spatial and temporal changes in geochemical parameters across three transects in the southern part of Gampaha district to 1) assess the impact of geological formations on groundwater;2) compare temporal variations in groundwater;and 3) explain acidification via a geochemical model. Seventy-two sample locations were tested for pH, electrical conductivity (EC), and anion concentrations (sulphate, nitrate, chloride and fluoride). Depth to the water table and distance from the sea were measured to study variations across sandy, peaty, lateritic, and crystalline aquifers. Results showed pH readings around 7 for sandy and crystalline aquifers, below 7 for peaty aquifers, and below 5 for lateritic aquifers, with significant water table fluctuations near Rathupaswala area. Principal component analysis revealed three principal components (PCs) explaining 86.0% of the variance. PC1 (40.6%) correlated with pH, EC, and sulphate (saltwater intrusion), while PC2 (32.0%) correlated with nitrates and depth to the water table (anthropogenic nutrient pollution). A geochemical transport model indicated a cone of depression recharged by acidic groundwater from peat-soil aquifers, leading to acidic groundwater in Rathupaswala area. Previous attributions of acidic pH to the over-exploitation of groundwater by the latex factory have been reevaluated;the results suggest natural acidification from prolonged water-rock interactions with iron-rich lateritic aquifers. Groundwater pH is influenced by local climate, geology, topography, and drainage systems. It is recommended that similar water-rock interaction conditions may be present throughout the wet zone of Sri Lanka, warranting detailed studies to confirm this hypothesis.

Assessment of the Variations in Soil Physicochemical Parameters of the Natural Forest and Plantations in Orumba North Local Government Area, Anambra State, Nigeria

Soil physicochemical parameters are the physical and chemical characteristics of soil such as pH, bulk density, organic carbon, nitrogen content, and nutrient levels at different soil depths. These parameters vary from one vegetation to the other and from one soil to the other. The study assessed the variations in soil physicochemical parameters of the natural forest and plantations in Agu Eke (Eke bush) in Etti village, Nanka and Umunnebo village, Ufuma both located in Orumba North Local Government Area, Anambra State. The experimental research design and stratified random sampling methods were used for the study and a total of 12 soil samples were collected at 30 cm depth from the selected locations of natural forest, cashew and palm plantations. The samples were analyzed using laboratory Varian AA240 Atomic Absorption Spectrophotometer, after which the result was subjected to statistical analysis—Analysis of Variance (ANOVA). The study found that there was no significant difference (variation) between the moisture contents of natural forests and the plantations;that is, the moisture contents were the same. It was also found that there was no significant variation between the bulk densities of the natural forest, oil plantation, and cashew plantation, meaning that the bulk densities were significantly the same. However, there were significant variations in nitrogen, potassium and phosphates, with p-values: sig = .000 < .05, sig = .010 < .05 and sig = .000 < .05, respectively. That is, the nitrogen and phosphate contents of the natural forest significantly vary more than those of the oil palm and cashew plantations, which probably means that by reducing natural forest to plantation, the nitrogen and phosphate contents of the natural forest reduced from what it used to be when the lands were mere forests. This shows that plantations do not have the same function of maintaining or improving soil quality as natural forests. The study recommended adopting a sustainable plantation agricultural system, such as using diverse nutrient sources (manure and compost), in order to maintain the desired soil quality.

Study and Application of Partial Least Squares Regression on Relationship between Soil Nutrient and Fruit Quality

[Objective] The objective of the study was to elucidate the duplicate collinearity diagnosis method for soil nutrient and provide basis for establishment of multiple regression model of relationship between independent variable and depen- dent variable in fruit trees. [Method] An investigation on soil nutrients and ＇Fuji＇ fruit quality was conducted at 153 commercial apple orchards in the production re- gions of 51 counties in China from 2011 to 2012. At first, the regression equation was used to do the duplicate collinearity diagnosis, and then the partial least squares regression was used to analyze the weights of different soil nutrients that affected the fruit quality and screen out main soil nutrients. [Result] The results showed the conditional number between soil nutrients was 61.31, and the correlation coefficient of soil pH and available calcium, iron was 0.82 and -0.824 respectively, which demonstrated that there was multicollinearity between various soil nutrient contents. The soil organic matter, total nitrogen, available potassium, available nitro- gen, available phosphorus, available zinc, available iron and available boron showed positive effect Ioadings on fruit quality, while the }oadings and weights of the effects of available calcium and pH on fruit quality were negative. The variable importance for projection method was adopted to get the orders of the effects of major soil nu- trients on fruit quality, which was in the order of soil available calcium, nitrogen, available iron, available phosphorous, organic matter and available boron. The solu- ble solid content of the fruit was affected by soil organic matter, available phospho- rus, available iron, available boron and soil pH. [Conclusion] This study provided an analysis method and theoretical basis for the study and analysis on the relationships between dependent variables and multi-objective optimization, as well as the effects of soil nutrients on fruit quality in fruit tree.