Crop residue application at low rates could improve soil phosphorus cycling under long-term no-tillage management

2021 ◽  
Vol 57 (4) ◽  
pp. 499-511
Author(s):  
Guohui Wu ◽  
Kai Wei ◽  
Zhenhua Chen ◽  
Dongqi Jiang ◽  
Hongtu Xie ◽  
...  
Keyword(s):  
Crop Residue ◽  
Soil Phosphorus ◽  
Phosphorus Cycling ◽  
No Tillage

scholarly journals Soil Bacterial Diversity and Potential Functions Are Regulated by Long-Term Conservation Tillage and Straw Mulching

2020 ◽  
Vol 8 (6) ◽  
pp. 836
Author(s):  
Chang Liu ◽  
Lingling Li ◽  
Junhong Xie ◽  
Jeffrey A. Coulter ◽  
Renzhi Zhang ◽  
...  
Keyword(s):  
Information Processing ◽  
Bacterial Community ◽  
Crop Residue ◽  
Soil Bacterial Community ◽  
Community Diversity ◽  
No Tillage ◽  
Organic C ◽  
Soil Bacterial ◽  
Residue Retention

Soil physiochemical properties are regulated by cropping practices, but little is known about how tillage influences soil microbial community diversity and functions. Here, we assessed soil bacterial community assembly and functional profiles in relation to tillage. Soils, collected in 2018 from a 17-year field experiment in northwestern China, were analyzed using high-throughput sequencing and the PICRUSt approach. The taxonomic diversity of bacterial communities was dominated primarily by the phyla Proteobacteria (32–56%), Bacteroidetes (12–33%), and Actinobacteria (17–27%). Alpha diversity (Chao1, Shannon, Simpson, and operational taxonomic unit (OTU) richness) was highest under no-tillage with crop residue removed (NT). Crop residue retention on the soil surface (NTS) or incorporated into soil (TS) promoted the abundance of Proteobacteria by 16 to 74% as compared to conventional tillage (T). Tillage practices mainly affected the pathways of soil metabolism, genetic information processing, and environmental information processing. Soil organic C and NH4–N were the principal contributors to the diversity and composition of soil microbiota, whereas soil pH, total nitrogen, total P, and moisture had little effect. Our results suggest that long-term conservation practices with no-tillage and crop residue retention shape soil bacterial community composition through modifying soil physicochemical properties and promoting the metabolic function of soil microbiomes.

scholarly journals Effects of Management and Hillside Position on Soil Organic Carbon Stratification in Mediterranean Centenary Olive Grove

Agronomy ◽  
2021 ◽  
Vol 11 (4) ◽  
pp. 650
Author(s):  
Jesús Aguilera-Huertas ◽  
Beatriz Lozano-García ◽  
Manuel González-Rosado ◽  
Luis Parras-Alcántara
Keyword(s):  
Organic Carbon ◽  
Soil Organic Carbon ◽  
Soil Quality ◽  
Management Practices ◽  
Soil Management ◽  
Olive Grove ◽  
No Tillage ◽  
Short Term ◽  
Degradation Degree

The short- and medium—long-term effects of management and hillside position on soil organic carbon (SOC) changes were studied in a centenary Mediterranean rainfed olive grove. One way to measure these changes is to analyze the soil quality, as it assesses soil degradation degree and attempts to identify management practices for sustainable soil use. In this context, the SOC stratification index (SR-COS) is one of the best indicators of soil quality to assess the degradation degree from SOC content without analyzing other soil properties. The SR-SOC was calculated in soil profiles (horizon-by-horizon) to identify the best soil management practices for sustainable use. The following time periods and soil management combinations were tested: (i) in the medium‒long-term (17 years) from conventional tillage (CT) to no-tillage (NT), (ii) in the short-term (2 years) from CT to no-tillage with cover crops (NT-CC), and (iii) the effect in the short-term (from CT to NT-CC) of different topographic positions along a hillside. The results indicate that the SR-SOC increased with depth for all management practices. The SR-SOC ranged from 1.21 to 1.73 in CT0, from 1.48 to 3.01 in CT1, from 1.15 to 2.48 in CT2, from 1.22 to 2.39 in NT-CC and from 0.98 to 4.16 in NT; therefore, the soil quality from the SR-SOC index was not directly linked to the increase or loss of SOC along the soil profile. This demonstrates the time-variability of SR-SOC and that NT improves soil quality in the long-term.

Long-term effects of no tillage and Ca-amendment on the activity of soil proteases and β-glucosidase in a Mediterranean agricultural field

2019 ◽  
Vol 95 ◽  
pp. 103135 ◽  
Author(s):  
Eduardo Vazquez ◽  
Marta Benito ◽  
Alberto Masaguer ◽  
Rafael Espejo ◽  
Eugenio Díaz-Pinés ◽  
...  
Keyword(s):  
No Tillage ◽  
Agricultural Field ◽  
Long Term Effects

Phosphorus mobility and degree of saturation in oxisol under no-tillage after long-term dairy liquid manure application

2018 ◽  
Vol 177 ◽  
pp. 45-53 ◽  
Author(s):  
Felipe Youssef Abboud ◽  
Nerilde Favaretto ◽  
Antonio Carlos Vargas Motta ◽  
Gabriel Barth ◽  
Gabriel Democh Goularte
Keyword(s):  
Degree Of Saturation ◽  
No Tillage ◽  
Liquid Manure ◽  
Manure Application

scholarly journals Geostatistical analysis of crop yield maps in a long term no tillage system

Bragantia ◽  
2010 ◽  
Vol 69 (suppl) ◽  
pp. 9-18 ◽  
Author(s):  
Osvaldo Guedes Filho ◽  
Sidney Rosa Vieira ◽  
Marcio Koiti Chiba ◽  
Célia Regina Grego
Keyword(s):  
Crop Yield ◽  
Crop Yields ◽  
Spherical Model ◽  
Exponential Model ◽  
Spatial And Temporal Variability ◽  
No Tillage ◽  
Yield Data ◽  
The North ◽  
Tillage System

It is known, for a long time, that crop yields are not uniform at the field. In some places, it is possible to distinguish sites with both low and high yields even within the same area. This work aimed to evaluate the spatial and temporal variability of some crop yields and to identify potential zones for site specific management in an area under no-tillage system for 23 years. Data were analyzed from a 3.42 ha long term experimental area at the Centro Experimental Central of the Instituto Agronômico, located in Campinas, Sao Paulo State, Brazil. The crop yield data evaluated included the following crops: soybean, maize, lablab and triticale, and all of them were cultivated since 1985 and sampled at a regular grid of 302 points. Data were normalized and analyzed using descriptive statistics and geostatistical tools in order to demonstrate and describe the structure of the spatial variability. All crop yields showed high variability. All of them also showed spatial dependence and were fitted to the spherical model, except for the yield of the maize in 1999 productivity which was fitted to the exponential model. The north part of the area presented repeated high values of productivity in some years. There was a positive cross correlation amongst the productivity values, especially for the maize crops.

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