Agricultural Tillage Practices Research Articles

Soil Surface Roughness Characteristics Under Different Agricultural Tillage Practices—A Case Study in the Black Soil Region of Northeast China

Soil Surface Roughness Characteristics Under Different Agricultural Tillage Practices—A Case Study in the Black Soil Region of Northeast China

Effects of no-tillage on greenhouse gas emissions in maize fields in a semi-humid temperate climate region

Agricultural tillage practices have a significant impact on the generation and consumption of greenhouse gases (GHGs), the primary causes of global warming. Two tillage systems, conventional tillage (CT) and no-tillage (NT), were compared to evaluate their effects on GHG emissions in this study. Averaged from 2018 to 2020, significant decreases of CO2 and N2O emissions by 7.4% and 51.1% were observed in NT as compared to those of CT. NT was also found to inhibit the soil CH4 uptake. In this study, soil was a source of CO2 and N2O but a sink for CH4. The effect of soil temperature on the fluxes of CO2 was more pronounced than that of soil moisture. However, soil temperature and soil moisture had a weak correlation with CH4 and N2O flux variations. As compared to CT, NT did not affect maize yields but significantly reduced global warming potential (GWP) by 8.07%. For yield-scaled GWP, no significant difference was observed in NT (9.63) and CT (10.71). Taken together, NT was an environment-friendly tillage practice to mitigate GHG emissions in the soil under the tested conditions.

Efficiencies of best management practices in reducing nitrate pollution of the Sebdou River, a semi‐arid Mediterranean agricultural catchment (North Africa)

AbstractA major problem facing the water sector in Algeria is deteriorating water quality, which is strongly influenced by nutrient inputs to agricultural watersheds. To mitigate the effects of agricultural activities and enhance water quality, this study considered the impact of different best management practices (BMPs) in agriculture. The objective of the research was to evaluate the impacts of various agricultural BMPs on nitrate losses in the Sebdou catchment in north‐west Africa using the Soil and Water Assessment Tool (SWAT) model in order to identify and recommend the most appropriate BMP. The study was carried out in two parts: first, the SWAT model was calibrated and validated to simulate discharge and nitrate losses at the outlet of the catchment, and second, the calibrated model was used to assess the effects of BMPs on nitrate losses. The hydrological modelling fitted well with the observed data for the calibration and validation periods (NSE between 0.63 and 0.65 and R2 between 0.80 and 0.92). Nitrate simulation was also satisfactory (NSE = 0.58 and R2 = 0.58), with the average nitrate exports at the outlet varying between 136 and 149 t N year−1. Agricultural tillage practices were the main N input and plant uptake was the main N output. The simulation results of BMP scenarios (contour farming, strip cropping and terracing) showed a significant decrease in nitrate quantity in soil, nitrate yield in surface run‐off and nitrate exports. The maximum reduction was observed from the use of parallel terraces, which reduced nitrate in soil by 17% (41 kg ha−1) and decreased nitrate flux exportation to below 133 t N year−1 (a reduction of about 11%). This study provided useful information for implementation of the most effective agricultural BMPs in the catchment for stakeholders who are interested in soil and water management.

Arbuscular Mycorrhizal Fungi in Agriculture

Arbuscular mycorrhizal (AM) fungi are biotrophic symbionts forming close relationships with an estimated 80% of terrestrial plants suitable as their host. Via an established AM fungal–host relationship, soil-bound nutrients are made available to the host plant through root cortical arbuscules as the site of exchange. At these sites, photosynthetic carbohydrates are provided to the AM fungus—carbohydrates that cannot be produced by the fungus. AM fungal–host symbiosis is very sensitive to soil disturbance, for example, agricultural tillage practices can damage and reduce AM fungal abilities to interact with a host and provide plant growth-promoting properties.

Effects of conservation tillage on soil microbial community and the function of soil carbon cycling

Agricultural tillage practices significantly affect the structure and function of soil micro-bial community, as well as its control over soil carbon cycling. Conservation tillage practice based on no-tillage and crop straw returning is an important measure to improve soil carbon sequestration and fertility, in which soil microorganisms play a key role. Although many previous studies focus on the structure and function of microbial communities under conservation tillage, our overall understanding of soil microbial responses at community level upon conservation tillage is still lacking, due to the complexity of the soil, environmental factors and the different selections of microbial research methods. Furthermore, previous studies paid more attention to the role of soil microorganisms as decomposers and the contribution of plant-derived carbon to the formation of soil carbon pool, but ignored the contribution of microbial-derived carbon to the formation and stability of soil carbon pool. We summarized the paradigm shift in soil organic matter formation and stability theories, reviewed the research methods of soil microbial community, focused on the effects of conservation tillage on soil microbial biomass, community diversity and composition, carbon metabolism, as well as microbial-derived carbon storage, and proposed suggestions for future study, aiming to provide support for future studies regarding microbial responses and its control over soil carbon dynamics in agroecosystem.

Comparative effects of long-term conventional tillage and no-till systems on greenhouse gas emissions in continuous maize monoculture soil in a semi-arid temperate climate

Agricultural tillage practices play an important role in the production and consumption of greenhouse gases (GHGs) that contribute substantially to the global warming. To explore GHG diffusion characteristic and seek for environment-friendly tillage methods, four tillage systems consisting of continuous rotary tillage (CR), continuous no tillage (CN), ploughing-rotary tillage (PR), and ploughing-no tillage (PN) were designed, and vertical variations of GHG concentrations under different tillage systems were investigated. Mean CO2 concentration in the soil profile was increased significantly with the increase of soil depth. Higher soil moisture promoted CO2 production. However, the influence of soil temperature on the content of CO2 was not obvious. The concentrations of CH4 in soil at 0–20-cm depth were greater than that of 20–40 cm, which was mainly affected by fertilization. The trend of N2O concentration variation in soil was consistent with that of CO2. The diffusion flux of CO2 in soil was all positive, and it changes greatly in the whole growth cycle of maize, which had obvious correlation with precipitation. The CH4 diffusion flux decreased with the increase of soil depth, and the change trend of 0–20-cm soil layer diffusion flux was consistent with the gas concentration. The 20–40-cm soil layer fluctuated greatly, which was mainly affected by water content, and the whole value was negative after jointing. The trend of N2O diffusion flux was similar to that of CH4. In the whole maize growth period, except for CH4 in 20–40-cm soil layer, the cumulative diffusion fluxes of greenhouse gases in each treatment were all positive, indicating that the whole farmland soil was the emission source of greenhouse gases. The effect of three greenhouse gases on greenhouse effect was CO2 > N2O > CH4, and the comprehensive warming potential of different tillage methods was CN > CR > PR> PN. So PN is the best tillage mode to reduce GHG emissions in soil profile under the test conditions.

Effect of tillage and straw return on carbon footprints, soil organic carbon fractions and soil microbial community in different textured soils under rice–wheat rotation: a review

Measuring the influence of long-term agricultural tillage practices on soil organic carbon (SOC) is of great importance to farmers and policymakers. Different management practices affected SOC mainly at the soil surface level. The different fractions of SOC viz. total SOC, particulate organic carbon, soil microbial biomass carbon, and potentially mineralizable carbon, were reported to be strongly correlated over a diversity of soils and management systems. Frequent tillage deteriorates soil structure and weakens soil aggregates, causing them to be susceptible to decay. The mixing of residues/surface retention into the soil increases SOM mineralization due to greater exposure to microbial decomposers and optimal moisture and temperature. Increased efficiency of N fertilizers use can result in reduced carbon footprints of field crops, because the contribution of N fertilizers is 36–52% of total emissions while increased soil C sequestration reduces the carbon footprint, because the input carbon as CO2 from atmospheric is converted into the plant biomass and eventually deposited to the soil. Decreasing soil tillage integrated with crop residues retention can increases SOC and decreases carbon footprint, and the mixing of key agricultural practices could increase the crop yields, reduce the emissions and carbon footprint respectively.

Hyperspectral image classification for mapping agricultural tillage practices

An efficient classification framework for mapping agricultural tillage practice using hyperspectral remote sensing imagery is proposed, which has the potential to be implemented practically to provide rapid, accurate, and objective surveying data for precision agricultural management and appraisal from large-scale remote sensing images. It includes a local region filter [i.e., Gaussian low-pass filter (GLF)] to extract spatial-spectral features, a dimensionality reduction process [i.e., local fisher’s discriminate analysis (LFDA)], and the traditional k-nearest neighbor (KNN) classifier, and is denoted as GLF-LFDA-KNN. Compared to our previously used local average filter and adaptive weighted filter, the GLF also considers spatial features in a small neighborhood, but it emphasizes the central pixel itself and is data-independent; therefore, it can achieve the balance between classification accuracy and computational complexity. The KNN classifier has a lower computational complexity compared to the traditional support vector machine (SVM). After classification separability is enhanced by the GLF and LFDA, the less powerful KNN can outperform SVM and the overall computational cost remains lower. The proposed framework can also outperform the SVM with composite kernel (SVM-CK) that uses spatial-spectral features.

Assessment of spectral indices for cover estimation of senescent vegetation

Quantification of dry plant matter (crop residue, senesced foliage, non-photosynthetic vegetation, or plant litter) surface cover (f R) is important for assessing agricultural tillage practices, carbon sequestration, rangeland health, or brush fire hazards. The Cellulose Absorption Index (CAI) and the Shortwave Infrared Normalized Difference Residue Index (SINDRI) are two spectral indices that can remotely estimate f R. CAI and SINDRI utilize three and two spectral bands, respectively, so SINDRI is expected to be less expensive to implement in future satellite sensors. We assessed the contrast of CAI and SINDRI with respect to soil reflectance spectra. Estimating f R with CAI is possible for all soils. However, a number of soil samples had positive SINDRI values due to various soil minerals, such as gibbsite and antigorite, which would be interpreted as high f R, and could limit its usefulness in some areas. Therefore, SINDRI is less applicable for estimating f R, even with reduced implementation costs.

Tillage-induced compaction: Effects on physical properties of agricultural loamy soils

Soil compaction due to agricultural tillage practices is a global concern and has profound implications on soil conservation and management with consequent effects on soil productivity. To assess the influence of tillage induced compaction on physical properties, we carried out a comparative study in agricultural loamy soils under tillage and no till manipulation by determining physical properties. Soil texture was determined using Bouyous method while the core method was used for soil bulk density and porosity. The soil water retention curve and infiltration rate was measured using pressure plate apparatus and double ring infiltrometer, respectively. The results shows that tilled (1.68 to 1.77 g/cm3) was more prone to compaction than non tilled soils (1.42 to 1.56 g/cm3) and consequently the porosity was also affected with the tilled soil having relatively less percentage of pore space. The mean infiltration rate was 1.25 and 2.75 mm/min for tilled and non-tilled areas, respectively. The lower rate in tilled soil was attributable to compaction which reduces the pore spaces with restriction of air and water movement. Similarly lower soil water content at field capacity and increased permanent wilting in tilled soils was also attributable to reduction of the pores associated with compaction. Key words: Compaction, infiltration, physical properties, tillage, loamy soils.

Greenhouse gas emission from direct seeding paddy field under different rice tillage systems in central China

Agricultural tillage practices play an important role in the production and/or consumption of green house gas (GHG) that contributes substantially to the observed global warming. Central China is one of the world's major rice producing areas but a few studies have tried to characterize the mechanisms of GHG release from rice paddy field and quantify global warming (GWPs) based on GHGs emission on this region. In this study four tillage systems consisting of no-tillage with no fertilizer (NT0), conventional tillage with no fertilizer (CT0), no-tillage with compound fertilizer (NTC) and conventional tillage with compound fertilizer (CTC) applications in rice (Oryza sativa L.) cultivation were compared in terms of the carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O) emissions from different tillage systems of the subtropical region of China during the rice growing season in 2008. GWPs based on CO2, CH4 and N2O's cumulative emissions were also compared. Tillage and fertilization had no influence on CO2 emissions. No-tillage had no effect on N2O emissions but significantly affected CH4 emissions. Application of fertilizer significantly affected CH4 and N2O emissions. Higher CH4 emissions and lower N2O emissions were observed in CTC than in NTC. Cumulative CH4 emission flux in NTC was 51.68 g CH4 m−2 while it was 65.96 g CH4 m−2 in CTC, 28% (p < 0.05) higher than that in NTC. Cumulative N2O emission flux in CTC was 561.00 mg N2O m−2, and was 741.71 mg N2O m−2 in NTC, 33% (p < 0.05) higher than that in CTC. There was no significant difference in N2O emissions between NT0 and CT0 systems, but significant in CH4 emissions. GWP of CTC was 26011.58 kg CO2 ha−1, which was 12% higher than that in NTC (23361.3 kg CO2 ha−1), therefore our findings show that no-tillage system was an effective strategy to reduce GWP from rice paddies in central China and thus can serve as a good agricultural system for environmental conservation.

Optimal classification methods for mapping agricultural tillage practices

The classification of agricultural tillage systems has proven challenging in the past using traditional classification methods due to the similarity of spectral reflectance signatures of soils and senescent crop residues. In this study, five classification methods were examined to determine the most suitable classification algorithm for the identification of no-till (NT) and traditional tillage (TT) cropping methods: minimum distance (MD), Mahalanobis distance, Maximum Likelihood (ML), spectral angle mapping (SAM), and the cosine of the angle concept (CAC). A Landsat ETM+ image acquired over southern Michigan and northern Indiana was used to test these classification methods. Each classification method was validated with 293 ground truth sampling locations collected commensurate with the satellite overpass. Classification accuracy was then assessed using error matrix analysis, Kappa statistics, and tests for statistical significance. The results indicate that of the classification routines examined, the two spectral angle methods were superior to the others. The cosine of the angle concept algorithm outperformed all the other classification routines for tillage practice identification and mapping, yielding an overall accuracy of 97.2% (Kappa=0.959).

Use of Multispectral Ikonos Imagery for Discriminating between Conventional and Conservation Agricultural Tillage Practices

There is a global concern about the increase in atmospheric concentrations of greenhouse gases. One method being discussed to encourage greenhouse gas mitigation efforts is based on a trading system whereby carbon emitters can buy effective mitigation efforts from farmers implementing conservation tillage practices. These practices sequester carbon from the atmosphere, and such a trading system would require a low-cost and accurate method of verification. Remote sensing technology can offer such a verification technique. This paper is focused on the use of standard image processing procedures applied to a multispectral Ikonos image, to determine whether it is possible to validate that farmers have complied with agreements to implement conservation tillage practices. A principal component analysis (PCA) was performed in order to isolate image variance in cropped fields. Analyses of variance (ANOVA) statistical procedures were used to evaluate the capability of each Ikonos band and each principal component to discriminate between conventional and conservation tillage practices. A logistic regression model was implemented on the principal component most effective in discriminating between conventional and conservation tillage, in order to produce a map of the probability of conventional tillage. The Ikonos imagery, in combination with ground-reference information, proved to be a useful tool for verification of conservation tillage practices.

THE EFFICIENCY OF SEQUESTERING CARBON IN AGRICULTURAL SOILS

Agricultural tillage practices are important human‐induced activities that can alter carbon emissions from agricultural soils and have the potential to contribute significantly to reductions in greenhouse gas emission (Lal et al., The Potential of U.S. Cropland, 1998). This research investigates the expected costs of sequestering carbon in agricultural soils under different subsidy and market‐based policies. Using detailed National Resources Inventory data, we estimate the probability that farmers adopt conservation tillage practices based on a variety of exogenous characteristics and profit from conventional practices. These estimates are used with physical models of carbon sequestration to estimate the subsidy costs of achieving increased carbon sequestration with alternative subsidy schemes.

The efficiency of sequestering carbon in agricultural soils

Agricultural tillage practices are important human-induced activities that can alter carbon emissions from agricultural soils and have the potential to contribute significantly to reductions in greenhouse gas emission (Lal et al., The Potential of U.S. Cropland, 1998). This research investigates the expected costs of sequestering carbon in agricultural soils under different subsidy and market-based policies. Using detailed National Resources Inventory data, we estimate the probability that farmers adopt conservation tillage practices based on a variety of exogenous characteristics and profit from conventional practices. These estimates are used with physical models of carbon sequestration to estimate the subsidy costs of achieving increased carbon sequestration with alternative subsidy schemes.

Identification of Agricultural Tillage Practices from C-Band Radar Backscatter

Une experience fut menee a Lethbridge, Alberta, avec un diffusometre sous differents types de labour. Les objectifs etaient de tester des methodologies utilisees dans les etudes radar en agriculture, de determiner la capacite des mesures de rugosite et de retrodiffusion a differencier entre les types de labour, et d'evaluer l'utilisation de deux angles d'incidence pour etablir les contributions respectives de l'humidite du sol et de la rugosite de surface au signal retrodiffuse total. Les resultats experimentaux suggerent que l'irrigation a un effet de lissage significatif sur la rugosite des surfaces et que la direction de visee du radar par rapport a l'orientation des labours est importante lors de la differenciation des types de labour. La retrodiffusion en bande C prise aux angles d'incidence (θ) de 40°-50° peut etre utilisee pour differencier les classes de labours. Les correlations entre le signal retrodiffuse et les parametres de surface indiquent que l'humidite du sol a la surface (0-2,5 cm) peut etre predite correctement aux faibles angles d'incidence (θ=20°) et que la rugosite (RMS) peut etre predite avec precision aux grands angles d'incidence (θ=50°). L'inclusion de la rugosite de surface et de la teneur en eau dans un modele de regression multiple a augmente la valeur des coefficients de correlation. L'utilisation de deux modeles de regression multiple avec la retrodiffusion en bande C mesuree a deux angles d'incidence a augmente la precision des estimations pour la rugosite et l'humidite, bien que dans l'ensemble, l'amelioration a ete faible. Les resultats de cette etude sont significatifs pour l'application des donnees de RADARSAT a la cartographie de la teneur en eau et des pratiques de labour.

Litter Placement Effects on Microbial and Organic Matter Dynamics in an Agroecosystem

Two different agricultural tillage practices were used to study how changes in the structure of the soil—litter system affected litter decomposition rates, microbial community composition, and soil organic matter dynamics. Surface straw placement results in spatial separation of carbon—rich litter (C:N ratio 80:1) and mineralized soil nitrogen. In contrast, when the litter is plowed into the soil, straw carbon and soil nitrogen are in intimate contact. Our field studies in Colorado showed that fungal biomass in surface—straw treatments was 144% of that in the incorporated—straw treatments, probably because fungi, with their extensive hyphal networks, are able to utilize both the surface straw carbon and the available soil nitrogen. Field studies using 14C—labeled wheat straw showed that a greater proportion of added 14C was retained in the surface—straw treatment than in the incorporated—straw treatment. Maximum net N immobilization was higher and litter decomposition was slower in the surface straw than in the incorporated straw placements both with and without experimental nitrogen addition. Slower litter decomposition of the surface litter may contribute to reduced soil organic matter losses. Soil organic matter losses may also be reduced in no—till systems as a result of the increase in the ratio of fungal to bacterial activity because of the greater growth efficiency of fungi and the accumulation of carbon in the less decomposable fungal biomass. The surface placement of straw in no—till agriculture allowed management of microclimate and microbial populations so that losses of soil organic matter and nutrients were minimized.