The influence of the soil matrix on nitrogen mineralisation and nitrification III. Predictive utility of traditional variables and process location within the pore system

Soil Research ◽  
1999 ◽  
Vol 37 (1) ◽  
pp. 137 ◽  
Author(s):  
D. T. Strong ◽  
P. W. G. Sale ◽  
K. R. Helyar
Keyword(s):  
Soil Ph ◽  
Organic N ◽  
Organic Substrates ◽  
Small Field ◽  
N Mineralisation ◽  
Field Plot ◽  
Pore System ◽  
Undisturbed Soil ◽  
Soil Matrix ◽  
Drying And Rewetting

Regression analysis was used to examine the importance of organic nitrogen (%N), soil water content (θv), soil pH, and C: N ratio for predicting N mineralisation in a small field plot. Undisturbed soil cubes (c. 1·7 cm3) were collected from the soil surface and received treatments of drying and rewetting, urea, substrate derived from clover leachate, or no amendment, and were incubated at either –10 or –30 kPa for 20 days. The data confirm the hypothesis that within a small field plot, θv and %N explain most of the variation in net N mineralisation and nitrification. The pore size classes of 0·6–10 and 10–30 µm made disproportionately small and large contributions to N mineralisation, respectively, apparently due to non-uniform distribution of organic N through the pore system. When soluble N substrate was added to the soils, both these pore classes appeared to support mineralisation. We concluded that prior to sampling, the microbial biomass had been more active in the pores 0·6–10 µm, and had nearly exhausted the organic substrates in this pore class, whereas this was not so for the 10–30 µm pore class. Drying and rewetting increased the importance of %N as a predictor of N mineralisation, probably because this treatment disrupted physical protective mechanisms of organic N. Soil pH was generally not a useful predictor of N mineralisation and often seemed to be a dependent rather than an independent variable in relation to nitrification. Neither was C: N ratio a useful predictor of N transformation processes, and this was probably related to physical regulatory mechanisms in the soil.

The influence of the soil matrix on nitrogen mineralisation and nitrification. I. Spatial variation and a hierarchy of soil properties

Soil Research ◽  
1998 ◽  
Vol 36 (3) ◽  
pp. 429 ◽  
Author(s):  
D. T. Strong ◽  
P. W. G. Sale ◽  
K. R. Helyar
Keyword(s):  
Soil Properties ◽  
Water Content ◽  
Organic N ◽  
Small Field ◽  
N Mineralisation ◽  
Mineral N ◽  
Conceptual Tool ◽  
Soil Matrix ◽  
Total N ◽  
Soil Variables

Natural heterogeneity of soil properties was used to explore their influence on nitrogen (N) mineralisation and nitrification in undisturbed small soil volumes (soil cells; c. 1 · 7 cm3 ) sampled from a small field plot (2 m by 3 m). Soil cells (840) were randomly ascribed to 1 of 6 treatments in which soils were retained continuously moist (M10 and M30 treatments) and amended with organic N from clover (Cl10 and Cl30 treatments), dried and rewetted (DW10), or treated with urea (Ur10) (subscripts indicate soil incubation at matric potential - 10 or - 30 kPa). After 20 days of incubation at 24C, each soil cell was analysed for NO-3 -N, NH + 4 -N, pH, bulk density (BD), volumetric water content (θv), water content at - 490 kPa (θv490), and pH buffer capacity (pHBC). On 25 soil cells from each treatment, % clay, % silt, % sand, total N (% N), organic carbon (% C), and 7 cations and anions were also determined. Net N mineralisation and net nitrification occurred in all treatments, and the total mineral N at the end of the incubation was 497, 81, 73, 31, 27, and 31 µg N/g in the Ur10 Cl10, Cl30, M10, M30, and DW10 treatments, respectively. Net N mineralisation in the M30 treatment was 84% of that in the M10 treatment, and net N mineralisation in the Cl30 treatment was 86% of that in the Cl10 treatment. Fluctuations in soil pH varied markedly between treatments and over time, and it was apparent that alkaline processes were occurring in all soil cells. The heterogeneity between soil samples was substantial for all of the soil variables. Soil variables were classified in a hierarchy from the least to the most fundamental based on their stability through time. This ranking provides a conceptual tool for understanding interrelationships between soil properties and for interpreting results of regression analyses. The sampling approach adopted in this study was designed to harness the natural heterogeneity of soil properties in the small field site while keeping other properties and environmental factors, that usually vary over larger distances, constant. Both the extent of heterogeneity of soil properties and the nature of their correlations with NO-3 -N suggested that this technique would be useful in the exploration of how soil properties influence N mineralisation and nitrification.

The influence of the soil matrix on nitrogen mineralisation and nitrification. IV.Texture

Soil Research ◽  
1999 ◽  
Vol 37 (2) ◽  
pp. 329 ◽  
Author(s):  
D. T. Strong ◽  
P. W. G. Sale ◽  
K. R. Helyar
Keyword(s):  
Negative Relationship ◽  
Negative Influence ◽  
Organic N ◽  
N Mineralisation ◽  
Linear Regression Models ◽  
Undisturbed Soil ◽  
Soil Matrix ◽  
Total N ◽  
Material Texture ◽  
Microbial Attack

Small undisturbed soil volumes (c. 1·7 cm3) were collected from the surface of a small field plot. Soil volumes were treated with clover-derived substrate, dried and rewetted, or retained continuously moist from the field. These soil volumes were then incubated for 20 days at a matric water potential of either –10 or –30 kPa. At the end of the incubation the soil was analysed for volumetric water content (θv), NO-3 -N, NH+4 -N, total N (%N), and percentages of sand, silt, and clay. The texture terms were included in linear regression models, together with %N and θv as predictors of N mineralisation and nitrification. Clay and sand were often observed to have a significant influence on N mineralisation and nitrification, but silt rarely appeared to influence these processes. In soils retained continuously moist, %clay had a negative relationship with N mineralisation and nitrification, but this relationship was positive in soils that had been dried and rewetted. The results suggest that during periods of relatively high moisture content, soils that are higher in clay are able to protect organic N more effectively from microbial attack. However, on drying and rewetting, the protective mechanisms of clay are undermined, the relatively large protected reservoirs of organic N in high clay soils become more vulnerable to microbial attack, and these soils therefore experience a greater flush of N mineralisation than soils with lower clay levels. The negative influence of clay in the continuously moist soils was not as clearly observed in the soils incubated at –10 kPa as in soils incubated at –30 kPa, suggesting that the decomposition of organic N resident in larger pores (10–30 µm neck diameter) may not be as strongly regulated by clay as that resident in smaller pores. When soils were treated with clover-derived substrate, clay had a positive relationship with N mineralisation and nitrification rates. This may have been because clay limited the diffusion of partially decomposed organics away from the decomposing microbial population, thereby helping to facilitate more complete decomposition of the organic material. Texture had very little influence on the nitrification of urea-derived ammonium.

The influence of the soil matrix on nitrogen mineralisation and nitrification. II. The pore system as a framework for mapping the organisation of the soil matrix

Soil Research ◽  
1998 ◽  
Vol 36 (5) ◽  
pp. 855 ◽  
Author(s):  
D. T. Strong ◽  
P. W. G. Sale ◽  
K. R. Helyar
Keyword(s):  
Organic Matter ◽  
Pore Size ◽  
Organic N ◽  
Strong Positive Correlation ◽  
Pore System ◽  
Undisturbed Soil ◽  
Soil Matrix ◽  
Terminal Electron Acceptor ◽  
Microbial Decomposition ◽  
Organic C

Large numbers of small undisturbed soil volumes (1·7 cm3 ) were collected from the surface layer of a 2 m by 3 m field plot on a red earth near Wagga Wagga, New South Wales. The hypothesis tested was that an analysis of relationships between the volume of different pore size classes and various soil properties, measured on these soil volumes, can provide an understanding of soil organisation within the framework of the pore system. Three discrete findings were presented in confirmation of the hypothesis. (1) A non-uniform distribution of organic N through the pore system was indicated by the data analysis. Soil organic N tended to be concentrated in pores <0·6 µm and in pores 10-30 µm, but not in the intermediate pore size class (pores 0·6-10 µm). Concentrations of organic N in pores <0·6 µm are probably because of physical protection from microbial decomposition, but concentrations of organic N in pores 10-30 µm are probably because these pores are infrequently water-filled, and this limits bacterial activity more severely than in the pores 0·6-10 µm. Currently available assays for potentially mineralisable N cannot account for the effect of substrate location within the pore system, and a characterisation of the soil for the distribution of N in pores may enhance their utility. Soil disturbance is likely to alter organic matter distribution through the pore system and alter mineralisation dynamics. (2) Observations of pore size distributions before and after wetting suggested that soils which were high in organic matter and clay tended to have a greater volume of pores 0 ·6-30 µm which are unstable to drying and rewetting. It is proposed that these unstable pores 0 ·6-30 µm had been produced by the movement and alignment of clay particles during the growth of microbial colonies. (3) The volume of pores <0·6 µm had a relatively strong negative correlation with pH and a relatively strong positive correlation with Mn2+ . A mechanism based on redox chemistry principles was proposed to explain these relationships. It was suggested that the volume of pores <0·6 µm is related to the potential anaerobicity of the soil volume. In anaerobic conditions, the terminal electron acceptor for organic C oxidation may be MnO2 instead of O2, and in these circumstances, considerably more H+ would be consumed than in aerobic conditions. It is suggested that this alkaline effect extends into regions of the matrix where N mineralisation and nitrification are occurring, and stimulates these processes. The greater nitrification which may result from such a chain of events may, over time, effect greater acidification in those soil volumes which have greater microporosity.

Use of natural heterogeneity in a small field site to explore the influence of the soil matrix on nitrogen mineralisation and nitrification

Soil Research ◽  
1997 ◽  
Vol 35 (3) ◽  
pp. 579 ◽  
Author(s):  
D. T. Strong ◽  
P. W. G. Sale ◽  
K. R. Helyar
Keyword(s):  
Soil Properties ◽  
Multiple Regression ◽  
Multiple Regression Equation ◽  
Regression Equations ◽  
Small Field ◽  
Undisturbed Soil ◽  
Soil Matrix ◽  
Ph Buffering ◽  
Functional Relationships ◽  
Physical Scale

The influence of soil properties on microbiological processes is often examined by comparing the behaviour of taxonomically disparate soils. One of the limitations of this approach is that the results can be confounded by the unmeasured properties which vary between soils of different type or between soils which have had different climatic and management histories. This study tested the hypothesis that the heterogeneity between 100 small contiguous undisturbed soil cubes (about 1·7 cm3), sampled from the surface of a very small field plot (14 by 14 cm), was sufficiently large to use for the exploration of how soil properties influence biological processes. After incubation of the soil for 35 days, the coefficients of variation for nitrate (NO3), ammonium (NH4), gravimetric water content (θg), bulk density (BD), pH buffering capacity (pHBC), and pH were 28, 39, 27, 10, 13, and 2%, respectively. A multiple regression equation predicting nitrate concentration had an r2 value of 0·89 and significantly included 4 predictor variables, with only pH being non-significant. These analyses confirmed the hypothesis. When the values of measured soil properties of adjoining soil cubes were meaned to estimate values for larger soil volumes, the multiple regression equations for predicting NO3 concentration explained more of the variation (r2 values as high as 0·99). However, information concerning the influence of certain soil properties on N mineralisation and nitrification was lost, with only pHBC and BD remaining significant in the regression model. It was concluded that at a given physical scale of investigation, the structure of the spatial variability may determine whether or not a relationship between 2 variables is observed. Smaller samples are more likely to identify functional relationships which may exist between measured variables at the microscale.

The influence of the soil matrix on nitrogen mineralisation and nitrification V. Microporosity and manganese

Soil Research ◽  
1999 ◽  
Vol 37 (2) ◽  
pp. 345 ◽  
Author(s):  
D. T. Strong ◽  
P. W. G. Sale ◽  
K. R. Helyar
Keyword(s):  
Linear Models ◽  
Positive Influence ◽  
Important Variable ◽  
N Mineralisation ◽  
Mineral N ◽  
Soil Matrix ◽  
Drying And Rewetting ◽  
O2 Diffusion ◽  
O2 Supply ◽  
Mn Oxides

Small soil cubes of dimensions 12 by 12 by 12 mm were collected from the surface of a red earth. Treatments were addition of clover substrate or urea, drying and rewetting, or no amendment, after which soils were incubated at either –10 or –30 kPa. Each soil cube was analysed for NO-3 -N, NH+4 -N, total soil N (%N), volumetric water content (θv), microporosity (volume of pores <0·6 µm), and Mn 2+ concentration. Multiple regression analysis was used to determine if microporosity and Mn 2+ contributed uniquely to linear models in which %N and qv were also used to predict N mineralisation and nitrification. In soils incubated at –10 kPa, both microporosity and Mn 2+ had a strong positive influence on N mineralisation and nitrification, whereas in soils incubated at –30 kPa no such influence could be observed. These and other observations suggest that when soils with high microporosity were incubated at –10 kPa, O2 supply to the microbial biomass was limited and the reduction of Mn oxides to divalent Mn was enhanced. Increased substitution of Mn oxides for O2 as terminal electron acceptors in the microbially mediated oxidation of carbon substrates considerably increases H+ consumption. We propose that in the wetter soil (–10 kPa), this process relieves pH stress experienced by N mineralising and nitrifying organisms, thereby increasing their activity, but that in the drier soil (–30 kPa), O2 diffusion is less restricted and this mechanism does not operate appreciably. The influence of microporosity on clover-amended soils was to decrease levels of mineral N and this was attributed to greater denitrification in soils with high microporosity. Neither microporosity nor Mn2+ was an important variable in the prediction of mineral N in the urea-treated soils. This work highlights the interaction of physical, chemical, and biological components of the soil which give rise to microbial microsites and diffusion gradients which are important determinants of soil function.

CORN RESPONSE AND SOIL NITROGEN TRANSFORMATIONS FOLLOWING VARIED APPLICATION OF POULTRY MANURE TREATED TO MINIMIZE ODOR

1975 ◽  
Vol 55 (1) ◽  
pp. 29-34 ◽  
Author(s):  
K. A. MACMILLAN ◽  
T. W. SCOTT ◽  
T. W. BATEMAN
Keyword(s):  
Soil Ph ◽  
Dry Matter ◽  
Poultry Manure ◽  
Organic N ◽  
Nitrogen Transformations ◽  
Inorganic N ◽  
N Source ◽  
Soil Inorganic N ◽  
Ph Conditions ◽  
Soil Nitrogen Transformations

The response of corn (Zea mays L.) to manure that had been treated to minimize odor was investigated in a greenhouse trial with two silt loam soils of pH 4.2 and 7.1. Pretreatment of manure resulted in sources initially high in organic N and NH4+, but low in NO3−. One pretreatment gave high initial NO2− concentrations. In soil at pH 4.2, NH4+ was the major N source utilized by corn grown to 36 days, and dry matter yields were superior to those from soil at pH 7.1 where soluble NO3− was the major source of N. At pH 7.1, NO2− remained in significant quantities and decreased dry matter yields at 6 wk. Soil inorganic N concentrations varied between soils and was attributed to soil pH differences. Rate of NO2− disappearance decreased with increase in soil pH, and NH4+ accumulation increased with decrease in soil pH, whereas NO3+ production was favored by neutral pH conditions. Some NO3− production was observed in pH 4.2 soil after 36 days' incubation

A preliminary study to predict net nitrogen mineralisation in a flooded rice soil using anaerobic incubation

1994 ◽  
Vol 34 (7) ◽  
pp. 995 ◽  
Author(s):  
JF Angus ◽  
M Ohnishi ◽  
T Horie ◽  
RL Williams
Keyword(s):  
N Uptake ◽  
Order Reaction ◽  
Zero Order ◽  
Organic N ◽  
N Mineralisation ◽  
Anaerobic Incubation ◽  
Flooded Soil ◽  
Order Model ◽  
First Order ◽  
Net Mineralisation

Complementary field and laboratory studies were conducted to determine whether laboratory measurements of net nitrogen (N) mineralisation under anaerobic conditions could be used to predict field rates in a flooded soil and N uptake by a rice crop. The laboratory experiment consisted of measurements of ammonium accumulation at 10, 20, 30, and 40�C for 7, 14, and 28 days of anaerobic incubation. There was no accumulation of ammonium at 10�C, but increasing ammonification rate at temperatures of 20�C was observed, except for a slower rate at 40�C after 14 days. Two models were tested on the data: a zero-order reaction in which rate of mineralisation was a linear function of temperature; a first-order reaction in which net N mineralisation rate was a proportion of a depleting pool of labile organic N. In the second model, the rate was also linearly related to temperature. Both models fitted the laboratory data well (R2 = 0.94 and 0.97, respectively), but the second model accounted better for mineralisation at 40�C for the 28-day incubation. These models were then run, using daily mean temperatures over a rice-growing season, to predict net mineralisation in the field. The predictions were compared with measured net N mineralisation in a flooded soil and N uptake by the crop measured throughout the season in the field from which the incubated soil was sampled. Net N mineralisation and crop uptake increased throughout the season, reaching maximum values of 115 and 111 kg N/ha at maturity. The zero-order and first-order models both predicted net N mineralisation accurately until the middle of the season, after which the zero-order model overestimated net N mineralisation but the first-order model predicted the reduction in the rate of net N mineralisation with reasonable accuracy. The close agreement between the laboratory incubations and field measurements of net mineralisation and crop N uptake suggest that incubation tests may provide useful information for including in a model to assist rice growers' decisions about N fertiliser.

Variability Among Aflatoxin Test Results on Runner Peanuts Harvested From Small Field Plots1

2004 ◽  
Vol 31 (1) ◽  
pp. 59-63 ◽  
Author(s):  
T. B. Whitaker ◽  
J. W. Dorner ◽  
F. G. Giesbrecht ◽  
A. B. Slate
Keyword(s):  
Standard Deviation ◽  
High Performance ◽  
Weighted Average ◽  
Aflatoxin Contamination ◽  
Small Field ◽  
Test Results ◽  
Field Plot ◽  
Aflatoxin Concentration ◽  
Production Practices ◽  
Standard Production

Abstract An experiment was conducted to determine the variability associated with aflatoxin contamination of peanuts from plants grown in specified row lengths. Runner peanuts (cv. Georgia Green) were planted in 10, 76.2 m rows (20 seed/m) and grown using standard production practices. Plants were exposed to natural late-season drought conditions making the peanuts susceptible to preharvest aflatoxin contamination. Plants were mechanically dug, inverted, and separated into 500 plots of 1.5 m single rows. Peanuts from each numerically identified plot were harvested with a mechanical picker, dried to 8% kernel moisture (wet basis), shelled, and analyzed for aflatoxin by high performance liquid chromatography (HPLC). The average kernel mass and weighted average aflatoxin concentration for all plots was 131 g and 2278 ng/g, respectively. The kernel mass varied among the 500 plots from a low of 4 g to a maximum of 283 g. The aflatoxin concentration among the 500 plots varied from a low of 0 ng/g to a maximum of 32,142 ng/g. The standard deviation among the 500 plot aflatoxin values was 4061. The standard deviation among sample concentrations for this field study was very similar to previous studies that measured the standard deviation among sample concentrations taken from bulk farmers' stock lots. Increasing plot length decreased the standard deviation among plot aflatoxin values as predicted by statistical theory. For example, increasing plot row length by a factor of four, or from 1.5 to 6 m, decreased the standard deviation by a factor of two, or from 4061 to 2031. A regression equation was developed to predict the effect of plot row length on the variability among aflatoxin plot values. This information is useful for designing field plot experiments to test various strategies for reducing or preventing preharvest aflatoxin contamination.

On the Survival of Heterodera marioni Infection Out-of-doors in England

1937 ◽  
Vol 15 (2) ◽  
pp. 75-76 ◽  
Author(s):  
Mary T. Franklin
Keyword(s):  
Climatic Conditions ◽  
Small Field ◽  
Potato Tubers ◽  
Field Plot

Potato tubers infected with Heterodera marioni having been received at this Institute, it was decided to attempt to infect a small field plot with this eelworm for experimental purposes. The tubers were planted in the plot but the infection never became established. This was thought to be due to the heavy nature of the soil, since H. marioni has been recorded as a field parasite in Britain (Triffitt, 1931), and it is therefore unlikely that climatic conditions were the cause of its failure to become established in this instance. In order to verify this, and to find out how long this parasite can survive in soil in the absence of a host, the following experiment was carried out.

Carbon mineralisation and pore size classes in undisturbed soil cores

Soil Research ◽  
2013 ◽  
Vol 51 (1) ◽  
pp. 14 ◽  
Author(s):  
Liesbeth Bouckaert ◽  
Steven Sleutel ◽  
Denis Van Loo ◽  
Loes Brabant ◽  
Veerle Cnudde ◽  
...  
Keyword(s):  
Organic Matter ◽  
Pore Network ◽  
Order Kinetic ◽  
Soil Cores ◽  
Undisturbed Soil ◽  
Soil Matrix ◽  
X Ray ◽  
C Mineralisation ◽  
The Impact ◽  
Undisturbed Soil Cores

Soil pore network effects on organic matter turnover have, until now, been studied indirectly because of lack of data on the 3D structure of the pore network. Application of X-ray computed tomography (X-ray CT) to quantify the distribution of pore neck size and related pore sizes from undisturbed soil cores, with simultaneous assessment of carbon (C) mineralisation, could establish a relationship between soil organic matter (SOM) decomposition and soil pore volumes. Eighteen miniature soil cores (diameter 1.2 cm, height 1.2 cm) covering a range of bulk densities were incubated at 20°C for 35 days. Respiration was modelled with a parallel first- and zero-order kinetic model. The cores were scanned at 9.44 µm resolution using an X-ray CT scanner developed in-house. Correlation analysis between the slow pool C mineralisation rate, ks, and pore volume per pore neck class yielded significant (P < 0.05) positive correlations: r = 0.572, 0.598, and 0.516 for the 150–250, 250–350, and >350 µm pore neck classes, respectively. Because larger pores are most probably mainly air-filled, a positive relation with ks was ascribed to enhanced aeration of smaller pores surrounding large pores. The weak and insignificant relationship between the smallest pore neck class (<9.44 µm) and ks could be explained by obstructed microbial activity and mobility or diffusion of exo-enzymes and hydrolysis products as a result of limited oxygen availability. This study supports the hypothesis that the impact of soil structure on microbial processes occurs primarily via its determination of soil water distribution, which is possibly the main driver for the location of C mineralisation in the soil matrix.

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