Variability Of Soil Characteristics Research Articles

An ecological framework to index crop yields using productivity and Ecosystem Fit: A case study from India

On the global scale, agricultural crop yields have decreased or plateaued over the last several decades. This suggests that the current focus on selecting crop varieties based on a plant’s light-use efficiency (photosynthetic and nitrogen-use-efficiency metrics) may not be sensitive to the site’s edaphic parameters, which limit growth. This study introduces a new framework to determine if crops can achieve higher yield potentials by assessing how plants adapt to the edaphic properties that impact growth, especially when contending with climate change. The new approach calculates an Ecosystem Fit index using a ratio of remotely sensed (or observed) total net primary productivity to the theoretical maximum productivity of the site. Then, it uses that index as a benchmark to judge quantitatively whether any new crop species or variety is improving potential biomass or economic yields at that specific site. It can also determine the best soil types for those crop varieties and monitor their potential adaptability relative to climate change over time. This study used a database of 356 spatially independent reference sites to develop this framework using a landcover classification of crops across 21 ecoregions and five biomes in India. It includes total net primary productivity data, theoretical maximum productivity potential, and soil and climatic data. This comparison showed that the light-use efficiency model, as intended, was not sensitive to variations in soil characteristics, temperature, or precipitation. Our framework showed significant differences in growth by soil type and precipitation and three significant productivity thresholds by soil type. The results of this study demonstrate that total crop productivity and Ecosystem Fit create a useful index for local land managers to assess growth and yield potentials across diverse edaphic landscapes and for decision-making with changing climates.

Seasonal variations in soil characteristics control microbial respiration and carbon use under tree plantations in the middle gangetic region

Seasonal variations directly impact the biochemical and microbial properties of the soil, influence carbon and nutrient cycling within the soil system. Soils under tree plantation (TP) are rich in organic matter and microbial population, making them more susceptible to seasonal variation. We studied the effect of seasonal variations in soil chemical properties (pH, electrical conductivity (EC), total organic carbon (TOC), total nitrogen (TN), C/N ratio etc) and microclimate (moisture and temperature) on microbial respiration (SR), biomass, and carbon (C) utilization efficiency under 13 years old Kadamb (Anthocephalus cadamba Miq.), Simaraubha (Simarouba glauca DC), and Litchi (Litchi chinensis Sonn.) based TPs in middle Gangetic region. In contrast to higher SR and metabolic quotient (qCO2) in winter, the microbial biomass carbon (MBC) and microbial biomass nitrogen (MBN) in fall > summer > spring > winter, irrespective of TPs. The positive relationship between qCO2 and C/N ratios strongly supports the dependence of microbes on soil carbon for respiration. qCO2 had a significantly positive relationship with soil moisture (MC) and Electrical conductivity (EC), but a significantly negative relationship with temperature and pH. Higher MBN/TN and MBC/TOC ratios fall under simaraubha, and litchi-based TPs indicated more nitrogen (N) and carbon accumulation into microbial biomass. The seasonal variation of MBC/MBN ratios signifies the changes in microbial communities and fungi dominate over bacteria during winter, as bacteria have a lower C/N ratio than fungi. Stepwise regression analysis suggested that soil properties and micro-climate regulated microbial biomass and SR differ with TPs. Thus, the study indicates that microbial activities and biomass production can significantly influence by soil properties and seasonal variations under TPs.

Effects of local farming practices on soil organic carbon content, enzymatic activities, and microbial community structure in semi-arid soils of Morocco

Soil organic carbon (SOC) is essential in semi-arid agricultural land for enhancing soil health, particularly through the promotion of microbial activities. This study assessed the impact of different agronomic practices on soil properties, microbial communities, and SOC levels in semi-arid Moroccan wheat fields. Three treatments were investigated: eucalyptus (Eucalyptus spp.) companion planting (EU), and fallowing with harvest residue mulching (FA), with the latter involving both short (3 months; FAS) and long (15 months; FAL) fallow periods. The study revealed significant variation in soil characteristics and microbial communities between these agronomic management regimes. Notably, soils managed with FAL contained elevated SOC levels (1.2%) compared to other treatments (FAS and EU) which show lower SOC range (0.62–0.86%). Both labile C (water-soluble carbon) and recalcitrant C (humic substances) were increased by FAL. Additionally, soil microbial biomass and dehydrogenase activity were observed to be high in FAL-managed soils, along with increased levels of extracellular enzymes related to nutrient cycling (β-glucosidase, alkaline phosphatase, and urease). Phospholipid fatty acid (PLFA) analysis indicated positive correlation between carbon content in soils and microbial populations. In contrast, soils managed with EU had significantly lower SOC levels, possibly due to differences in carbon fractionation. FAL increased soil enzymatic activities and enriched the microbial community when compared to EU management. In conclusion, this study indicated the importance of fallowing and fallowing period for conservation of SOC, and potential to mitigate negative effects of biophysical constraints on agricultural productivity in semi-arid soils of Northwest Africa.

Spatial-temporal variability in nitrogen use efficiency: Insights from a long-term experiment and crop simulation modeling to support site specific nitrogen management

Within-field soil heterogeneity can lead to large variation in nitrogen use efficiency (NUE). Crop simulation models provide a multi-faceted approach to management considering both soil and plant interactions. However, research using crop models for investigating within field variation in NUE is limited, in part because of challenges quantifying spatially variable soil model parameters. Here soil apparent electrical conductivity (ECa) and measured soil properties were used to map spatial variations in soil characteristics across a Long-Term Experiment in Norfolk, England. The relationship between plot ECa across the 3 ha experiment and agronomic data across three different nitrogen rates (0, 110, and 220 kg N ha-1) over five wheat years (2010–2020) was quantified. The Sirius crop model was parameterized for two soils representing the extremes of ECa. Sirius was validated using recorded plot data. Site-specific optimal nitrogen and associated leaching risks were simulated across 29 years of weather data. Variation in soil properties had significant impact on measured NUE. At 220 kg N ha-1 mean observed yields across 5 years ranged from 9.0 to 10.7 t ha-1 and grain protein from 11.6% to 11% on the low EC and high EC plots, respectively. On average fertiliser grain N recovery was 19.7 kg N ha-1 lower on the low ECa plots. Sirius simulated the variation in yield, grain protein and grain N recovery to a good level of accuracy with RRMSE of 19.5%, 15.4% and 19.5%, respectively. Simulated optimal nitrogen on the low EC soils was on average 12 kg N ha-1 lower, with >1 in 4 years with optimal nitrogen <200 kg N ha-1. Our work demonstrated that using a combination of proximal soil EC scans and targeted soil sampling we can optimize the data requirements for model parameterisation to support site-specific N management.

Growth and Fruit morphometric characteristics of local avocado germplasm (Persea americana Mill.) grown in northern Tanzania

Tanzania has a diverse agroecological area suitable for growing tropical fruits, including avocados. In Northern Tanzania, avocados have been growing under variable soil and altitudinal characteristics for over 100 years, allowing the naturalisation of this crop in this region. However, the region's avocado germplasm is uncharacterised, thus impeding the selection of elite genotypes for increased value and breeding programmes. This study examined the growth and fruit morphometric characteristics of avocado populations grown under variable soil pH and altitude in six districts in the Tanga, Kilimanjaro and Arusha regions. Variations in growth and fruit morphometric characteristics were compared using a one-way analysis of variance (ANOVA). Pearson product-moment correlations (r) were used to evaluate the relationship between studied growth and fruit morphometric traits. A linear mixed-effects model (LMM) was used to assess the influence of the soil pH, altitude, tree height, canopy diameter, and trunk diameter on fruit length, fruit diameter, pulp thickness, and seed diameter. Principal Component Analysis (PCA) was used to depict the extent of the racial admixtures in the avocado germplasm in the Northern regions of Tanzania. The results revealed a significant variation in growth and fruit morphometric characteristics (p < 0.05). The Korogwe population had the highest tree height, while the Karatu had the lowest. Tree height was positively correlated with the trunk diameter (r = 0.63, p < 0.001. There was a positive correlation between fruit length and pulp thickness (r = 0.51, p < 0.001), fruit diameter and pulp thickness (r = 0.47, p < 0.001), and fruit length and fruit diameter (r = 0.36, p < 0.001). The fruit diameter was positively correlated with the seed diameter (r = 0.61, p < 0.001). There was a significant but weak association between fruit length and trunk diameter (−0.01), fruit length and canopy diameter (0.15), and between seed diameter and tree height (2.95e-2). These findings highlight the influence of individual tree genetic makeup on the variation in growth and fruit morphometric characteristics. The morphometric trait correlations may prove valuable in field measurements, especially when resources are limited. The study further indicates the presence of all avocado races within the local germplasm, highlighting its high diversity. Remarkably, the observed admixture of variant races implies gene flow among studied avocado populations, possibly facilitated by sharing seedlings among farmers or seed disposal through avocado fruit trading. Further study is needed, particularly in quantifying the above-ground biomass of local avocados in northern Tanzania, potentially contributing to carbon credit initiatives for fruit crops..

A Systematic Review on Digital Soil Mapping Approaches in Lowland Areas

Digital soil mapping (DSM) around the world is mostly conducted in areas with a certain relief characterized by significant heterogeneities in soil-forming factors. However, lowland areas (e.g., plains, low-relief areas), prevalently used for agricultural purposes, might also show a certain variability in soil characteristics. To assess the spatial distribution of soil properties and classes, accurate soil datasets are a prerequisite to facilitate the effective management of agricultural areas. This systematic review explores the DSM approaches in lowland areas by compiling and analysing published articles from 2008 to mid-2023. A total of 67 relevant articles were identified from Web of Science and Scopus. The study reveals a rising trend in publications, particularly in recent years, indicative of the growing recognition of DSM’s pivotal role in comprehending soil properties in lowland ecosystems. Noteworthy knowledge gaps are identified, emphasizing the need for nuanced exploration of specific environmental variables influencing soil heterogeneity. This review underscores the dominance of agricultural cropland as a focus, reflecting the intricate relationship between soil attributes and agricultural productivity in lowlands. Vegetation-related covariates, relief-related factors, and statistical machine learning models, with random forest at the forefront, emerge prominently. The study concludes by outlining future research directions, highlighting the urgency of understanding the intricacies of lowland soil mapping for improved land management, heightened agricultural productivity, and effective environmental conservation strategies.

Management zone classification for variable-rate soil residual herbicide applications

AbstractThe use of soil residual herbicides, along with other practices that diversify weed management strategies, have been recommended to improve weed management and deter the progression of herbicide resistance. Although soil characteristics influence recommended application rates for these herbicides, the common practice is to apply a uniform dose of soil residual herbicides across fields with variable soil characteristics. Mapping fields for soil characteristics that dictate the optimal dose of soil residual herbicides could improve the efficiency and effectiveness of these herbicides, as well as improve environmental stewardship. The objectives of this research were to develop and quantify the accuracy of management zone classifications for variable-rate residual herbicide applications using multiple soil data sources and soil sampling intensities. The maps were created from soil data that included (i) Soil Survey Geographic database (SSURGO), (ii) soil samples (SS), (iii) soil samples regressed onto soil electrical conductivity (EC) measurements (SSEC), (iv) soil samples with organic matter (OM) data from SmartFirmer® (SF) sensors (SSSF), and (v) soil samples regressed onto EC measurements plus OM data from SmartFirmer® sensor (SSECSF). A modified Monte Carlo cross validation method was used on ten commercial Indiana fields to generate 36,000 maps across all sources of spatial soil data, sampling density, and three representative herbicides (pyroxasulfone, s-metolachlor, and metribuzin). Maps developed from SSEC data were most frequently ranked with the highest management zone classification accuracy compared to maps developed from SS data. However, SS and SSEC maps concurrently had the highest management zone classification accuracy of 34% among maps developed across all fields, herbicides, and sampling intensities. One soil sample per hectare was the most reliable sampling intensity to generate herbicide application management zones compared to one soil sample for every 2 or 4 hectares. In conclusion, soil sampling with ECa data should be used for defining the management zones for variable-rate (VR) residual herbicide applications.

Variability of soil characteristics around an active volcano, Mt. Mayon in the Philippines with special reference to the distance and direction from the crater

ABSTRACT This study investigated soil characteristics around Mt. Mayon, an active stratovolcano in the Philippines, which might depend on the meteorological condition and distribution of volcanic material deposition varying with distance and direction from the crater. Soil profiles were prepared at four and six sites in different directions, on a circle of 6 km and 15 km away from the crater, respectively. Soil profile morphology was described and the soil samples collected from each horizon were analyzed for physicochemical properties including total element, oxalate, and dithionite-citrate extractable Si, Al, and Fe, and phosphate adsorption coefficient, as well as clay mineralogical composition by XRD analysis. In general, regarding the distance, the soils showed less weathered status at 6 km and moderately weathered status at 15 km. In terms of direction, the soils at 6 km were moist and shallow in the northeast and southeast sites but dry and deep in the northwest and southwest sites. Meanwhile, despite all being deep, the soils at 15 km were moist in the northeast and east sites and dry in the other sites. While all soils showed less acidic nature and high levels of basic cations irrespective of distance and direction, phosphate adsorption coefficient was varied widely depending on the contents of oxalate-extractable Al and dithionite-citrate extractable Fe, for which the soils containing the higher amount of the oxalate-extractable Al showed the higher values of the coefficient. Consequently, the soils at 6 km were classified into Aquandic Humudepts (northeast), Vitrandic Eutrudepts (southeast and southwest), and Typic Udivitrands (northwest) while the soils at 15 km were Vitrandic Eutrudepts (northeast), Duric Epiaquands (east), and Typic Hapludalfs (southeast, southwest, northwest, and San Miguel Island). Such differences in soil formation and characteristics around Mt. Mayon seemed to be ascribable to the different geographical setting such as decrease in the supply of new volcanic material depending on the distance from the crater and the impacts of precipitation and typhoons, of which amount and intensity are higher in the east side than the west side because of the east side facing to the Pacific Ocean.

Seasonal dynamics and spatial patterns of soil moisture in a loess catchment

Abstract. The spatial and seasonal patterns in soil moisture and the processes controlling them in semi-arid landscapes are not well understood. Loess landscapes minimize any confounding effects of variation in soil characteristics and are thus ideal for studying topographic influences on soil moisture in drylands. In this study, volumetric soil moisture was monitored monthly for 5.5 years at 20 cm intervals between the surface and 5 m depth at 89 sites across a small (0.43 km2) catchment on the Chinese Loess Plateau. The median soil moisture was computed for each month and depth for each monitoring site as a measure of the typical soil moisture conditions. Seasonal changes in soil moisture were mainly concentrated in the shallow (0–100 cm) soil, with a clear seasonal separation between wet conditions in October–March and dry conditions in May–July, even though precipitation is highest in July–August. Soil moisture was higher on the northwest-facing slopes due to increased drying from solar radiation on the southeast-facing slopes. This effect of slope aspect was greater between October and March, when the zenith angle of the sun was lower and the aspect-dependent difference in solar radiation reaching the surface was larger. The wetter, northwest-facing slopes were also characterized by larger annual soil moisture storage changes. Soil texture was nearly uniform across both slopes, and soil moisture was not correlated with the topographic wetness index, suggesting that variations in evapotranspiration dominated the spatial pattern of soil moisture in shallow soils under both wet and dry conditions. Water balance calculations indicate that over 90 % of the annual precipitation was seasonally cycled in the soil between 0 and 300 cm, suggesting that only a minor fraction infiltrates to groundwater and becomes streamflow. Our findings may be broadly applicable to loess regions with monsoonal climates and may have practical implications for catchment-scale hydrologic modeling and the design of soil moisture monitoring networks.

Variation in soil characteristics of ex-coal mining areas in Sawahlunto, West Sumatra

Soil characteristics in ex-coal mining areas can be influenced by reclamation methods and the type and age of revegetation plants used. This reclamation can also significantly impact the soil chemistry of ex-mining areas. This research was conducted in ex-coal mining areas located in Parambahan, Batu Tanjung Village, Talawi District, Sawahlunto City, West Sumatra Province. The objective of this study is to analyze variations in the reclamation process and their effects on the chemical properties of soil in these areas. Observations were made in several plots, including land that had not been mined (natural forest), land revegetated with Acacia in the planting years of 1992, 2007, 2010 (without the use of topsoil), 2019, and 2021, and land revegetated with Sengon in 2022. In each plot, soil samples were collected at three depths: 0–5 cm, 5–10 cm, and 10–20 cm, to analyze soil chemical properties. These properties included pH, total nitrogen (N), available phosphorus (P), organic carbon (C), exchangeable base cations (K, Ca, Mg, and Na), cation exchange capacity, and exchangeable aluminum (Al). The results showed that variations in the years of revegetation and reclamation practices, such as the use of topsoil and plant types, significantly influenced soil chemical characteristics. The longer the period of revegetation, the better the improvement in the soil’s chemical properties, as indicated by changes in pH, total N, organic C, exchangeable K, Na, Ca, and Mg, cation exchange capacity, and a reduction in exchangeable Al. However, the availability of P, as indicated by available P, decreased after more than 30 years of revegetation.

Fertilisation with P, N and S requires additional Zn for healthy plantation tree growth on low fertility savanna soils

Context Soil nutrient limitations characterise savanna soils globally and are one of several constraints to establishing productive tree plantations and enhancing economic opportunities in tropical regions. Fertilisation offers an approach to overcome soil nutrient limitations to maximise tree growth and health, but requires research on nutrient contents, composition, rates and methods of delivery in the context of soil characteristics. Aims To determine the optimal contents, rates and methods of application of fertiliser to maximise the growth and health of the plantation timber species Pinus caribaea on low fertility savanna soils. Methods Factorial field experiments tested growth responses to applications of phosphorus (P), nitrogen (N) and sulfur (S) on three soils near Darwin, Australia. Further experiments tested effects of zinc (Zn), copper (Cu) and potassium (K) application and small-scale variation in soil characteristics on tree performance. Key results Positive growth responses to P, N and S were recorded, yet unhealthy trees developed, particularly in better-performing treatments. Second phase experiments addressing potential causes of ill health confirmed Zn limitations. Intense spatial soil sampling demonstrated substantial variation in cation exchange capacity and composition over short distances. Conclusions Nutrient additions to enhance plantation tree growth will need to encompass minor and trace elements in addition to N, P and S, specifically Zn, and consider the mechanism of application. Implications Small-scale variability in cation exchange capacity and composition indicates that optimal fertilisation rates will vary spatially, and that soil sampling for site characterisation would be more accurate with replicated dispersed samples.

NORNE, a process-based grass growth model accounting for within-field soil variation using remote sensing for in-season corrections

A process-based model was developed to predict dry matter yields and amounts of harvested nitrogen in conventionally cropped grassland fields, accounting for within-field variation by a node network design and utilizing remotely sensed information from a drone-borne system for increased accuracy. The model, named NORNE, was kept as simple as possible regarding required input variables, but with sufficient complexity to handle central processes and minimize prediction errors. The inputs comprised weather data, soil information, management data related to fertilization, and a visual estimate of clover proportion in the aboveground biomass. A sensitivity analysis was included to apportioning variation in dry matter yield outputs to variation in model parameter settings. Using default parameter values from the literature, the model was evaluated on data from a two-year study (2016–2017, 264 research plots in total each year) conducted at two locations in Norway (i.e. in South-East and in Central Norway) with contrasting climatic conditions and with internal variation in soil characteristics. The results showed that the model could estimate dry matter yields with a relatively high accuracy without any corrections based on remote sensing, compared with published results from comparable model studies. To further improve the results, the model was calibrated shortly before harvest, using predictions of above ground dry matter biomass obtained from a drone-borne remote sensing system. The only parameters which were hereby adjusted in the NORNE model were the starting values of nitrogen content in soil (first cut) and the plant available water capacity (second cut). The calibration based on the remotely sensed information improved the predictive performance of the model significantly. At first cut, the root mean square error (RMSE) of dry matter yield prediction was reduced by 20% to a mean value of 58 g m−2, corresponding to a relative value (rRMSE) of 0.12. For the second cut, the RMSE decreased by 13% to 66 g m−2 (rRMSE: 0.18). The model was also evaluated in terms of the predictions of amounts of nitrogen in the harvested crop. Here, the calibration reduced the RMSE of the first cut by 38%, obtaining a mean RMSE value of 2.1 g N m−2 (rRMSE: 0.28). For the second cut, the RMSE reduction for simulated harvested N was 16%, corresponding to a mean RMSE value of 2.3 g N m−2 (rRMSE: 0.33). The large improvements in model accuracy for simulated dry matter and nitrogen yields obtained through calibration by utilizing remotely sensed information, indicate the importance of considering spatial variability when applying models under Nordic conditions, both for yield predictions and for decision support for nitrogen application.

Assessing spatial variability of soil and drawing location-specific management zones for coastal saline soils in Ramanathapuram District, Tamil Nadu

The production of crops in saline and alkali-degraded areas is difficult due to the heterogeneous and spatial variation of soil fertility. First, their spatial variability was analyzed and maps of the spatial distribution were created using Geostatistical techniques. The fuzzy k-mean clustering analysis was then used to define Management zones in the coastal saline soils of Ramanathapuram district in Tamil Nadu. One hundred and fifty geo-referenced soil samples (30 cm depth) were taken and analyzed for pH, electrical conductivity (ECe) in the saturated paste extract (USSL method), organic carbon (OC) (Walkley-Black chromic acid wet oxidation method), calcium carbonate (CaCO3) (Rapid titration method) and available phosphorus and extractable micronutrients (Multinutrients extraction method), revealing significant variation in soil characteristics throughout the coastal saline soils of Ramanathapuram district. The most significant factors, which together accounted for four principal components and 69% of the overall variability, were pH, electrical conductivity (ECe), calcium Carbonate and available zinc. According to Geostatistical analysis, the Exponential (pH, OC (organic carbon), P, Fe, Mn and Zn) and Stable (ECe) was the best fit semivariogram ordinary kriging model with weak to moderate spatial dependence. Fuzzy k-mean clustering was also used to identify zone 1, zone 2 and zone 3. For every soil property, there was a significant difference between MZ1(zone 1), MZ2(zone 2) and MZ3(zone 3). These results also showed that cluster analysis gave farmers a chance to use location-specific nutrient management strategies by minimizing variability within the zone. The management zones can decrease agricultural inputs and environmental pollutants while increasing crop productivity.

Version 1.1.0—pyfao56: FAO-56 evapotranspiration in Python

The pyfao56 software package is a Python-based implementation of the standardized evapotranspiration (ET) methodologies described in Irrigation and Drainage paper No. 56 of the Food and Agriculture Organization of the United Nations, commonly known as FAO-56. This update improved pyfao56 by (1) fixing a major bug related to testing for availability of weather data, (2) expanding options for reference ET calculations including hourly estimates, (3) adding functionality to specify variable soil characteristics with profile depth, (4) including optional water balance enhancements that consider soil water depletion for both the dynamic and maximum root zones, and (5) enabling the use of either constant or variable depletion fraction (p). The updates increase software versatility and expand options for use, while also maintaining the core functionality of the original software design.

Geopedology in complex landform setting: A case study in eastern Parangtritis Village, Indonesia

The structural mountain range of Baturagung continue to undergo soil development, influenced by various factors, including landform, geomorphological processes, and land use management. This research is grounded in the potential of soil resources based on landform, demanding precise land management and conservation. The study involved transecting and soil sampling across different landform features in the eastern part of Parangtritis Village. The delineation of these features was aided by the modification of the topographic position index-based landform classification. Research data revealed that the landform types encompass shoulders, backslopes, footslopes, toeslopes, depressions, and floodplains. Each of these landform features exhibits distinct soil characteristics concerning depth, color, texture, and mottling, as well as organic matter, manganese, and carbonate content. These characteristics also represent soil problems that require special management, including shallow soils, steep soils, Vertisols, and anthropogenic soils experiencing compaction. Proper soil management is essential to mitigate land degradation. Therefore, investigating the variations in soil characteristics based on geomorphology is crucial for comprehending their formation and development processes and for factoring them into land management decisions.

Applicability of existing CPT-Vs correlations to shallow Holocene Christchurch soils based on direct Push crosshole testing

The applicability of four existing empirical cone penetration test to shear wave velocity (CPT-Vs) correlations to Holocene soils in the Christchurch region of New Zealand was assessed using over 1400 CPT-Vs data pairs. While most existing correlations used seismic CPT (sCPT) or other downhole-based methods in their development, this paper uses a database based on the direct push crosshole (DPCH) method. This database allowed for an assessment of the influence of the Vs measurement method on correlation performance, with sCPT and downhole methods based on vertically propagating, horizontally polarized shear waves, compared to the horizontally propagating, vertically polarized shear waves used for the DPCH. Across the CPT-Vs correlations considered, different ranges of over- or under-predicted Vs were presented. In general, the correlations tend to underestimate the measurements for low cone tip resistance and sleeve friction values, while at higher values, they provide more reasonable estimates or slight overestimates. The correlation developed based on a sCPT database from Christchurch significantly underestimates Vs at depths less than 4 m, likely due to a combination of factors including issues with the assumed wave propagation path used in sCPT processing, variability in soil characteristics within mapped geologic units and extrapolation of the correlation beyond the original database characteristics. Underestimation at greater depths was generally within 10% which likely reflects the influence of soil anisotropy on the measured Vs from each method. The performance of these correlations demonstrates that investigation methods and the characteristics of the databases used in correlation development should be considered when they are applied in practice.

Spatial Variability of Soil Properties under Different Land Use Systems in Wokha District of Nagaland, India

The shifting cultivation practice is the predominant land use system of Nagaland, India, and Wokha district in particular. In general, there are four different forms of land use: forest, shifting cultivation, cultivated fallow, and wet terrace rice cultivation. In the Wokha district, a study was conducted in the year 2015 to evaluate the variability in soil characteristics among four different land use systems and to map their spatial distribution. A total of 381 soil samples were collected and tested for six soil fertility parameters; clay, pH, soil organic carbon, available nitrogen (N), phosphorus (P) and potassium (K). The results showed that all of the soils were very acidic in nature; however the mean value of soil pH was substantially higher in the shifting cultivation system. Soil organic carbon concentrations ranged from high to very high across all land use systems. Average soil organic carbon content was highest in the forest, followed by cultivated fallow, shifting, and wet terrace rice cultivation (WTRC) systems, whereas available N content was very low to low. The P concentration of the soil was very low in the WTRC system and low in the other systems. Soil K concentration was high in shifting (361.95 kg/ha), cultivated fallow (312.4 kg/ha), forest (309.73 kg/ha), and low in WTRC (166.975 kg/ha) land use systems. Available N, P and K deficiency was found in 93.8%, 72.2%, and 32.9% of soil samples, respectively. Soil organic carbon correlated positively with K and significantly positively with N. Soil pH correlated negatively with clay content and positively but non-significantly with P. The generated maps might be used to assist farmers in identifying the expected nutrient levels in their areas and encourage them to change their crop management practices to improve crop yield and profitability. Due to soil acidity, higher SOC, lower N and P, and higher potassium content, suitable acid loving crops, higher N and phosphorus fertilization, and some commercially advantageous potassium responsive crops may be encouraged in farming practices.

Influence of spatial soil variability on productivity and physiological quality of soybean seeds

Seed production fields present spatial and temporal variability in the physical and chemical characteristics of the soil, thus influencing the yield and quality of the produced seeds. The objective of this study was to characterize the spatial variability in soil attributes providing physiological quality and productivity in soybean seeds in two commercial production fields, aiming to define areas of agronomic management. The experiment was carried out in the 2014/15 and 2015/16 crop seasons in a 100×100 m grid. Soil sampling was performed at a depth of 0-200 mm with a 75×75 m grid. The soybean samples were collected at the end of the 2014/15 crop season. Therefore, soil analysis was determined only in the 2014/15 crop season. The plants' agronomic characteristics and the productivity and physiological quality of produced seeds were determined for both crop seasons. Thus, it was concluded that the study site presented spatial variability in soil characteristics, phosphorus content, organic matter, cation exchange capacity, sand, and clay content, and the agronomic characteristics of soybean plants cv. BMX Desafio RR, including plant height, number of nodes per plant, number of pods with three seeds, number of pods with seeds, number of seeds per plant, seed weight per plant, seed weight per linear meter, productivity, and germination. Seed productivity showed a strong spatial dependence, while germination showed a moderate spatial dependence. Three management zones were determined according to the spatial distribution of the results obtained.

Tool for the Establishment of Agro-Management Zones Using GIS Techniques for Precision Farming in Egypt

Agro-management zones recently became the backbone of modern agriculture. Delineating management zones for Variable-Rate Fertilization (VRF) can provide important ecological benefits and better sustainability of the new Egyptian farming projects. This article aims to represent an approach for delineating management zones using Spatial Multicriteria Evaluation (SMCE) within irrigated peanut pivot situated at the eastern Nile Delta, Egypt. The results indicated that soil data, such as soil texture, soil type, the elevation of the landscape, and slope, allow for sampling the study area into similar classes and in smaller units, along with a crop productivity map. The effects of the variability in soil characteristics within the field on Peanut yields are predicted by the soil suitability model. In addition, final management zones map a varied amount of nutrients that could be added to different pivot zones. In conclusion, mapping soil units with a sufficient number of field observations within each class provided an acceptable accuracy, and a good spatial distribution of the suitability classification was achieved. Hence, agro-management zones are essentially needed for policymakers in a specific field in order to furnish an evaluation about the transformations at a territorial scale and for studying the strategies to realize environmental sustainability and to reduce the territorial impacts.

Microporous carbon derived from cotton stalk crop-residue across diverse geographical locations as efficient and regenerable CO2 adsorbent with selectivity

Six porous carbons (PCs) were prepared via thermochemical methodology from cotton-stalk crop residue, collected from diverse geographical locations in India. Although similar in nature, the precursor collection sites majorly influenced the properties of the generated PCs, possibly due to variations in soil characteristics and fertilizer usage patterns. The microstructures were characterized by a series of analytical data, including FT-IR and Raman Spectra, XRD, TGA, SEM imaging, and in-depth XPS studies. Nitrogen sorption isotherms at 77 K of all PCs revealed well-defined microporosity and high specific surface area, varying from 1706 to 2438 m2/g under similar synthetic conditions. Further, gaseous CO2 adsorption studies showed that the PCs exhibited diverse uptake performances at 1 bar under varied temperatures. The maximum uptake capacity of 6.23 mmol/g (273 K), 3.85 mmol/g (298 K), and 3.28 mmol/g (313 K) defined superior values over contemporary adsorbents. A critical-point drying technique was employed further to enhance the CO2 uptake capacity of these carbons. Importantly, all the carbons revealed moderate to good CO2/N2 separation selectivity at low temperature (~25 at 273 K) that experienced a unique enhancement under elevated temperature, as calculated from ideal adsorbed solution theory. After vacuum regeneration, the activated carbons exhibited stable CO2 adsorption up to five cycles, validating their potential reusability for CO2 capture. Precisely, the cotton stalk crop residue-derived PCs represent one-of-a-kind low cost, eco-friendly, abundant, and scalable absorbents for regenerable CO2 capture with moderate heat of adsorption and selectivity values, with promises of practical usability.