Soil aggregation is of great importance in agriculture due to its positive effect on soil physical properties, plant growth and the environment. A long-term (1996–2008) field experiment was performed ...to investigate the role of mycorrhizal inoculation and organic fertilizers on some of soil properties of Mediterranean soils (Typic Xerofluvent, Menzilat clay–loam soil). We applied a rotation with winter wheat (
Triticum aestivum L
.) and maize (
Zea mays L.) as a second crop during the periods of 1996 and 2008. The study consisted of five experimental treatments; control, mineral fertilizer (300–60–150
kg
N–P–K
ha
−1), manure at 25
t
ha
−1, compost at 25
t
ha
−1 and mycorrhiza-inoculated compost at 10
t
ha
−1 with three replicates. The highest organic matter content both at 0–15
cm and 15–30
cm soil depths were obtained with manure application, whereas mineral fertilizer application had no effect on organic matter accumulation. Manure, compost and mycorrhizal inoculation
+
compost application had 69%, 32% and 24% higher organic matter contents at 0–30
cm depth as compared to the control application. Organic applications had varying and important effects on aggregation indexes of soils. The greatest mean weight diameters (MWD) at 15–30
cm depth were obtained with manure, mycorrhiza-inoculated compost and compost applications, respectively. The decline in organic matter content of soils in control plots lead disintegration of aggregates demonstrated on significantly lower MWD values. The compost application resulted in occurring the lowest bulk densities at 0–15 and 15–30
cm soil depths, whereas the highest bulk density values were obtained with mineral fertilizer application. Measurements obtained in 2008 indicated that manure and compost applications did not cause any further increase in MWD at manure and compost receiving plots indicated reaching a steady state. However, compost with mycorrhizae application continued to significant increase (P
<
0.05) in MWD values of soils. Organic applications significantly lowered the soil bulk density and penetration resistance. The lowest penetration resistance (PR) at 0–50
cm soil depth was obtained with mycorrhizal inoculated compost, and the highest PR was with control and mineral fertilizer applications. The results clearly revealed that mycorrhiza application along with organic fertilizers resulted in decreased bulk density and penetration resistance associated with an increase in organic matter and greater aggregate stability, indicated an improvement in soil structure.
►The decline in organic matter lead disintegration of aggregates demonstrated on lower MWD values. ►Manure and compost did not cause any further increase in MWD indicated reaching a steady state. However, compost with mycorrhizae application continued to significant increase in MWD of soils. ►Mycorrhiza along with organic fertilizers resulted in an improvement of soil structure. ►Compost application lowered the bulk density and reached to a steady state at the given conditions.
Soil salinity is a major land degradation process reducing biological productivity in arid and semi-arid regions. Therefore, its effective monitoring and management is inevitable. Recent developments ...in remote sensing technology have made it possible to accurately identify and effectively monitor soil salinity. Hence, this study determined salinity levels of surface soils in 2650 ha agricultural and natural pastureland located in an arid region of central Anatolia, Turkey. The relationship between electrical conductivity (EC) values of 145 soil samples and the dataset created using Landsat 5 TM satellite image was investigated. Remote sensing dataset for 23 variables, including visible, near infrared (NIR) and short-wave infrared (SWIR) spectral ranges, salinity, and vegetation indices were created. The highest correlation between EC values and remote sensing dataset was obtained in SWIR1 band (r = -0.43). Linear regression analysis was used to reveal the relationship between six bands and indices selected from the variables with the highest correlations. Coefficient of determination (R2 = 0.19) results indicated that models obtained using satellite image did not provide reliable results in determining soil salinity. Microtopography is the major factor affecting spatial distribution of soil salinity and caused heterogeneous distribution of salts on surface soils. Differences in salt content of soils caused heterogeneous distribution of halophytes and led to spectral complexity. The dark colored slickpots in small-scale depressions are common features of sodic soils, which are responsible for spectral complexity. In addition, low spatial resolution of Landsat 5 TM images is another reason decreasing the reliability of models in determining soil salinity.
Soil salinity is the most common land degradation agent that impairs soil functions, ecosystem services and negatively affects agricultural production in arid and semi-arid regions of the world. ...Therefore, reliable methods are needed to estimate spatial distribution of soil salinity for the management, remediation, monitoring and utilization of saline soils. This study investigated the potential of Landsat 8 OLI satellite data and vegetation, soil salinity and moisture indices in estimating surface salinity of 1014.6 ha agricultural land located in Dushak, Turkmenistan. Linear regression model was developed between land measurements and remotely sensed indicators. A systematic regular grid-sampling method was used to collect 50 soil samples from 0-20 cm depth. Sixteen indices were extracted from Landsat-8 OLI satellite images. Simple and multivariate regression models were developed between the measured electrical conductivity values and the remotely sensed indicators. The highest correlation between remote sensing indicators and soil EC values in determining soil salinity was calculated in SAVI index (r = 0.54). The reliability indicated by R2 value (0.29) of regression model developed with the SAVI index was low. Therefore, new model was developed by selecting the indicators that can be included in the multiple regression model from the remote sensing indicators. A significant (r = 0.74) correlation was obtained between the multivariate regression model and soil EC values, and salinity was successfully mapped at a moderate level (R2: 0.55). The classification of the salinity map showed that 21.71% of the field was non-saline, 29.78% slightly saline, 31.40% moderately saline, 15.25% strongly saline and 1.44% very strongly. The results revealed that multivariate regression models with the help of Landsat 8 OLI satellite images and indices obtained from the images can be used for modeling and mapping soil salinity of small-scale lands.
Crop production is negatively impacted by excess and lack of soil micronutrients. Due to anthropogenic and natural factors, soil micronutrients vary greatly in space, necessitating time- and ...money-consuming large-scale sampling. Therefore, modeling their spatial distributions and forecasting in non-sampled areas are essential for high crop production.
In this study, regional variations in soil micronutrient content of the Upper Tigris Basin were modeled to produce local change maps for the development of site-specific nutrient management systems. The concentrations of extractable zinc (Zn), copper (Cu), manganese (Mn), and iron (Fe) in soil samples taken at 388 different sites between 0 and 20 cm deep were determined. Using variogram and kriging analyses, the spatial distribution of the micro element concentrations was modeled and mapped in a GIS environment.
The micronutrients demonstrated significant variability with a high coefficient of variation (CV > 35%). It was found that the spatial dependence of the samples ranged from low for Fe and Cu to high for Zn and Mn. The spatial distribution of soil micronutrients was influenced by soil texture in addition to distance. Overall, the results demonstrated that the management of site-specific micronutrients may be aided by the integration of geostatistics and GIS, which is particularly beneficial in terms of effective management of the lands and the optimal use of inputs.
Overall, the findings showed that the integration of geostatistics and GIS may be helpful in the management of site-specific micronutrients, which is especially advantageous in terms of efficient management of the lands and the best use of inputs.
Assessing the spatial variability of soil properties is vital in proper planning of agricultural farmlands. The aim of this study is to determine and map the spatial variability of important physical ...and chemical soil properties using geoistatistical models for land use planning of a farm located in Thrace region of Turkey. Two hundred fifty-four surface and subsurface soil samples were collected from at approximately the corners of 150m x 150m size grids cells. The land area of study area was 557 ha and used for what and sunflower production. Soil samples were analyzed for particle size distribution, soil reaction (pH), electrical conductivity (EC), organic matter (OM), lime content (CaCO3), available phosphorus (P) and extractable potassium (K). Penetration resistance was also measured at each sampling point. Soil pH ranged from 4.46 to 8.20 in surface and 4.01 to 8.30 in subsurface soils. Sand content was the least variable (CV=11.5% and 13.9% for surface and subsurface) soil property, while the variability of P content (CV=105.9 and 119.8%) was higher than the rest of the soil properties. The lowest range value was obtained for P content (113 and 134 m) and the longest-range value was for available K content (5899 and 6099 m) of soils. Spatial distribution maps helped to identify and deliniate the zones need to be limed, deficient in available P and compacted zones within the study area. Sustainable management strategies in a farm can be planned and implemented using the information obtained from spatial structures and maps of major soil characterics.
•No-till and reduced tillage systems improved the quality of surface soil.•Strategic tillage improved soil functions and overall quality compared to no till.•High organic matter content did not ...significantly improve water relation function.•Productivity function in reduced tillage is higher than conventional and no tillage.
Agricultural practices should be carefully monitored for long-term impacts on soil quality to avoid further deterioration in ecosystem services provided by soils. The aim of this study was to evaluate and compare the effects of two conventional (CT), three reduced (RT) and two no-till (NT) tillage practices on soil quality of a clayey soil in a ten-year experiment using Soil Management Assessment Framework (SMAF). The field experiment was established in 2006 with six tillage methods, and winter wheat (Triticum aestivum L.), soybean (Glycine max. L.) – grain corn (Zea mays L.) crop rotation. The NT plots were divided into two parts, i.e., half of them were plowed with a moldboard plow during November 2015, and this practice was defined as strategic tillage (ST), while the remaining half was left undisturbed (NT). Disturbed and undisturbed soil samples were collected at three depths (0−10, 10−20 and 20−30 cm) from experimental plots in 2016. Fourteen soil quality indicators, including physical, chemical and biochemical properties were determined to assess soil quality. Soil productivity, water relations (WR), resistance and resilience (RR), and physical stability and support (PSS) functions defined in SMAF were calculated. The RR and PSS function scores were significantly higher at 0−10 cm depth under conservational tillage methods (RT and NT) compared to CT methods. Low nutrient content, compaction, aggregate size and stability values in 10−30 cm depth decreased the functioning potential. The RR function at 0−10 cm depth in NT method was 103 % and 72 % higher than CT-1 and CT-2, respectively. All soil functions under RT and NT methods decreased with depth. The ST significantly increased PSS and WR functions in all sampling depths and overall soil quality in 10−20 and 20−30 cm depths compared to long-term NT method. The comparison of soil functions and overall soil quality indices helped to identify the effects of different tillage practices on functional potential of the soil. Furthermore, soil quality assessment using soil functions provides an overview to distinguish the pros and cons of tillage practices on sustainability of the crop production.
Assessment of land suitability is a prerequisite for the conservation and maintenance of land productivity and the improvement of land use and management systems. This study assessed land suitability ...for rapeseed (Brassica napus L.) production using topography, climate, and soil data by analytical hierarchy process (AHP) and the Mamdani Fuzzy Inference System (MFIS). The study area covers 3737 km2 of land in the Diyarbakir province of southeastern Turkiye. The weights of topography, soil and climate factors in AHP were determined by expert opinions and the information in related literature. They were included in the whole process, mainly membership functions and rule base stages in the MFIS. The highest weighted factor was slope (0.264), followed by altitude (0.121), annual average temperature (0.114) and soil texture (0.112). The MFIS-based land suitability assessment indicated that the proportions of moderately (S2), marginally (S3) and currently not suitable (N1) land classes in the study area were 71.35%, 18.75% and 9.9%, respectively. The AHP results showed that 98.94% of the land was S3, and 1.06% was N1. The compatibility of AHP and MFIS methods in N1 land units was 96.05%, while the agreement for S2 and S3 land classes was not sufficiently high. The suitability of rapeseed cultivation has been more sensitively assessed by the fuzzy continuous classification obtained by the MFIS method.
•Boolean logic separated moderately suitable land units according to distinct boundaries and ignored gradual transition zones.•Fuzzy logic-based land suitability assessment determines the membership degree of factors in sustainability classes.•Fuzzy logic approach generates precise land suitability classes, reflecting agricultural productivity.•Fuzzy logic provides optimal solutions in complex decision-making under uncertainty.
Information on spatial distribution and potential sources of heavy metals in agricultural lands is very important for human health and food safety. In this study, pollution degree of lead (Pb), ...cadmium (Cd), and nickel (Ni) in Yüksekova Plain, located on the border in the southeastern part of Turkey, was evaluated by geoaccumulation index (Igeo), modified contamination factor (mCdeg), and Nemerow pollution index (PI
Nemerow
) combined with spatial autocorrelation using deep learning algorithms. A total of 304 soil samples were collected from two different depths (0–20 and 20–40 cm) in the study area, which covered 17.5 thousand ha land. Covariates were determined for spatial distribution models of Pb, Cd, and Ni by factor analysis (FA). Spatial distribution models for surface soils were developed using pedovariables (silt, sand, clay lime, organic matter, electrical conductivity, pH, Ca, and Na) determined by the FA and Igeo and mCdeg values by artificial neural network (ANN) and adaptive neuro-fuzzy inference system (ANFIS) models. The estimation success of models for different depths was assessed by root mean square error (RMSE), mean absolute percent error (MAPE), and Taylor diagrams. The RMSE and MAPE values showed a strong correlation between heavy metal contents and the covariates. The RMSE values of ANN-Ni
0-20
, ANN-Ni
20-40
, ANN-Pb
0-20
, ANN-Cd
0-20
, and ANN-Cd
20-40
models (0.01240, 0.07257, 0.0039, 0.00045, 0.00044, and 0.04607, respectively) confirmed the success of the models. Likewise, the MAPE values between 0.2 and 8.5% indicated that all models were very good predictors. In addition, the Taylor diagrams showed that the estimation performance of ANFIS and ANN models are compatible. The Igeo
Ni
and Igeo
Pb
values in both models at both depths indicated that strongly to extremely polluted (4–5) areas are quite high in the study area, while the Igeo
Cd
values revealed that unpolluted areas are widespread. The mC
deg
index value showed a moderate to high contamination at the first depth, while very high contamination at the second depth in most of the study area. Spatial distribution of PI
Nemerow
revealed that moderate pollution (2–3) is common in both soil depths of the study area. The PI
Nemerow
of subsurface layer was between 0.91 and 1 (warning limit class) in a small part of the study area. The results showed that vertical mobility of heavy metals is closely related to pedovariables. In addition, the ANN and ANFIS models are capable of exhibiting the heterogeneity in the spatial distribution pattern of high variation in the data. Thus, the locations with extreme contamination have been accurately determined. The pollution indices calculated considering the commonly used international reference values revealed that heavy metal pollution in some part of the study area reached the detrimental levels for human health and food safety. The results suggested that the pollution indices were more successful than simple heavy metal concentrations in interpreting the pollution risk levels. High-resolution spatial information reported in this study can help policy makers and authorities to reduce heavy metal emissions of pollutants or, if possible, to eliminate the pollution.
•Strategic tillage decreased MWD at surface soil by 7.2% compared to no-till.•Higher WFPS (<60%) in no till and reduced tillage may cause to nitrogen losses.•Strategic tillage increased macro and ...total porosity compared to no till.•Strategic tillage reduced water content in 0–20 cm depth compared to no till.
Long-term no-till or reduced tillage may decline functioning ability of soils due to surface/subsurface compaction and/or stratification of plant nutrients. A long-term (ten years) field experiment was established in 2006 in the Çukurova region of Turkey to evaluate the impact of tillage on the physical properties of a soil under a Mediterranean climate. The tillage systems investigated included two conventional (CT-1 and CT-2), three reduced (RT-1, RT-2 and RT-3) and two no-till (NT and ST), including strategic/occasional tillage. Nine-year old undisturbed no-till plots were divided into two categories and half of these plots were plowed by a moldboard plow in November 2015, and this practice was defined as strategic tillage (ST), while remaining half of the plots left undisturbed. Soil samples were collected from disturbed and undisturbed plots of NT as well as plots under other tillage systems from three soil depths (i.e., 0–10, 10–20 and 20–30 cm) in November 2016. The crop rotation at the experimental areas was winter wheat (Triticum aestivum L.), soybean (Glycine max. L.) – grain maize (Zea mays L.) – winter wheat. Soil samples were analyzed for aggregate stability (AS), mean weight diameter (MWD), bulk density (BD), water filled pore space (WFPS), water content at field capacity (FC), permanent wilting point (PWP), available water content (PAW), micropores (MiP), macropores (MaP), total porosity (TP), and penetration resistance (PR). The ST decreased MWD of surface soil compared to NT by 7.2%, while MWD under ST was higher than NT by 78.0% and 103.6% for 10–20 and 20–30 cm depths, respectively. The NT and RT resulted higher BD and PR, and lower MaP and TP than CT and ST in all three depths, though the values were generally not limiting for crop growth. The ST significantly (P < 0.01) decreased BD and PR within 30 cm of soil surface. However, water content at FC, PWP and also PAW in 0–10 and 10–20 cm depths were significantly reduced with ST compared to NT. The ST significantly (P < 0.01) increased the MaP and TP compared to NT which favors better aeration and water movement. The mean WFPS under NT, RT-2 and RT-3 systems in 0–10 cm and with all tillage systems (except ST in 10–20 cm) in subsurface layers were higher than 60%, which is considered a threshold for nitrogen losses as N2O fluxes. Implementation of ST into conservational practices under Mediterranean climate could be a viable management option to overcome some of the disadvantages of long-term conservation tillage and thereby to improve physical soil conditions for crop growth, air and water movement.
Arazi kullanımı, ana materyal ve topoğrafyaya bağlı olarak büyük
değişkenlik gösteren toprak özelliklerinin mesafeye bağlı değişkenlikleri;
toprağın verimliliği, kalitesi ve genel olarak ...sürdürülebilirliğini önemli
düzeyde etkilemektedir. Bu çalışma; yaklaşık 1900 hektar genişliğindeki
Gökhöyük Tarım İşletmesi arazilerinin bir kısım toprak özelliklerinin mesafeye
bağlı değişkenliklerini belirlemek, haritalamak ve işletme arazilerinin
sürdürülebilir kullanımlarını etkileyecek sorunların tespit edilerek çözüm
önerilerini ortaya koymak amacı ile gerçekleştirilmiştir. Bu amaçla, çalışma
alanını temsil edecek şekilde 63 noktadan ve 4 farklı derinlikten (0-30, 30-60,
60-90 ve 90-120 cm) toprak ve 19 noktadan da taban suyu örnekleri alınmıştır.
Toprak örneklerinde elektriksel iletkenlik (EC), pH, kil, kum ve silt
içerikleri ile hidrolik iletkenlik değerleri; taban suyu örneklerinde ise pH ve
EC değerleri belirlenmiştir. Klasik istatistik ve jeoistatistik yöntemler ile
çalışılan özelliklerin, arazideki genel durumu ve mesafeye bağlı
değişkenlikleri karakterize edilmiştir. Araştırma sonucuna göre, yüksek kil
içeriğine sahip olan hem yüzey hem de yüzey altı topraklarında hidrolik
iletkenlik değerleri (<20 mm h-1) oldukça düşük bulunmuştur. Bitki
besin elementi alımı üzerine önemli bir etkisi olan pH değerlerinin tüm
derinliklerde ve arazinin önemli bir kısmında 8.5’in üzerinde; çalışma alanının
orta kısmında bir hatta yer alan toprakların 60-120 cm derinliğinde EC
değerleri (>4 dS m-1) sorun oluşturabilecek düzeylerde olduğu
tespit edilmiştir. Bu bölgedeki su örneklerinin de EC değerleri 20 dS m-1’nin
üzerinde olduğu görülmüştür. Kurak ve sıcak dönemlerde tuz içeriği yüksek taban
suyunun kapilarite ile yüzeye taşınması, toprağın üretkenlik fonksiyonuna zarar
verebilir. Toprak özelliklerinin mesafeye bağlı değişimini gösteren haritaların
kullanımı ile çiftlik arazisinde bitkisel üretimin geliştirilmesine ve toprak
kalitesinin iyileştirilmesine katkı sağlayacak kararların doğru bir şekilde
alınması mümkün olabilecektir.
Spatial variability of soil properties which
vary greatly depending on land use, parent material and topography
significantly affects soil fertility, quality, and overall sustainability. This
study was carried out to determine and map the spatial variability of some of
soil properties in Gökhöyük Agricultural Farm, which is approximately 1900 ha,
and to identify the problems that may affect the sustainable use of the land
and to propose solutions. For this purpose, soil samples representing the study
area were collected from 63 points and 4 different depths (0-30, 30-60, 60-90
and 90-120) along with 19 water samples from 1.5-2.0 m depths. Electrical
conductivity (EC), pH, clay, sand, silt contents and hydraulic conductivity
values of soil samples, and pH and EC values of the groundwater samples were
determined from 19 points. The general status and spatial variability of soil
properties studied were characterized by classical statistics and
geostatistical methods. According to the results of the study, the hydraulic
conductivity values (<20 mm h-1) were found to be very low in
both surface and subsoil soils having high clay content. The pH values, which
have a significant effect on plant nutrient availability, were higher than 8.5
at all depths in a significant portion of the study area. The EC values of
soils (60-120 cm depth) located in the middle part of the study area were high (>4 dS m-1),
to be considered as problematic. The EC values of water samples in this
location were above 20 dS m-1. Highly saline ground water that
transported to the soil surface with capillarity in the dry and hot seasons can
harm the productivity function of soils. Spatial distribution maps of the soil
properties will enable to make the accurate decisions which will contribute to
the development of plant production and improvement of soil quality in the farm
land.
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