Prediction of macronutrients in plant leaves using chemometric analysis and wavelength selection

Purpose

Fast and real-time prediction of leaf nutrient concentrations can facilitate decision-making for fertilisation regimes on farms and address issues raised with over-fertilisation. Cacao (Theobroma cacao L.) is an important cash crop and requires nutrient supply to maintain yield. This project aimed to use chemometric analysis and wavelength selection to improve the accuracy of foliar nutrient prediction.

Materials and methods

We used a visible-near infrared (400–1000 nm) hyperspectral imaging (HSI) system to predict foliar calcium (Ca), potassium (K), phosphorus (P) and nitrogen (N) of cacao trees. Images were captured from 95 leaf samples. Partial least square regression (PLSR) models were developed to predict leaf nutrient concentrations and wavelength selection was undertaken.

Results and discussion

Using all wavelengths, Ca (R²_CV?=?0.76, RMSE_CV?=?0.28), K (R²_CV?=?0.35, RMSE_CV?=?0.46), P (R²_CV?=?0.75, RMSE_CV?=?0.019) and N (R²_CV?=?0.73, RMSE_CV?=?0.17) were predicted. Wavelength selection increased the prediction accuracy of Ca (R²_CV?=?0.79, RMSE_CV?=?0.27) and N (R²_CV?=?0.74, RMSE_CV?=?0.16), while did not affect prediction accuracy of foliar K (R²_CV?=?0.35, RMSE_CV?=?0.46) and P (R²_CV?=?0.75, RMSE_CV?=?0.019).

Conclusions

Visible-near infrared HSI has a good potential to predict Ca, P and N concentrations in cacao leaf samples, but K concentrations could not be predicted reliably. Wavelength selection increased the prediction accuracy of foliar Ca and N leading to a reduced number of wavelengths involved in developed models.

     

Predicting Soil Organic Carbon and Total Nitrogen in the Russian Chernozem from Depth and Wireless Color Sensor Measurements

Color sensor technologies offer opportunities for affordable and rapid assessment of soil organic carbon (SOC) and total nitrogen (TN) in the field, but the applicability of these technologies may vary by soil type. The objective of this study was to use an inexpensive color sensor to develop SOC and TN prediction models for the Russian Chernozem (Haplic Chernozem) in the Kursk region of Russia. Twenty-one dried soil samples were analyzed using a Nix Pro? color sensor that is controlled through a mobile application and Bluetooth to collect CIEL*a*b* (darkness to lightness, green to red, and blue to yellow) color data. Eleven samples were randomly selected to be used to construct prediction models and the remaining ten samples were set aside for cross validation. The root mean squared error (RMSE) was calculated to determine each model’s prediction error. The data from the eleven soil samples were used to develop the natural log of SOC (lnSOC) and TN (lnTN) prediction models using depth, L*, a*, and b* for each sample as predictor variables in regression analyses. Resulting residual plots, root mean square errors (RMSE), mean squared prediction error (MSPE) and coefficients of determination (R², adjusted R²) were used to assess model fit for each of the SOC and total N prediction models. Final models were fit using all soil samples, which included depth and color variables, for lnSOC (R² = 0.987, Adj. R² = 0.981, RMSE = 0.003, p-value < 0.001, MSPE = 0.182) and lnTN (R² = 0.980 Adj. R² = 0.972, RMSE = 0.004, p-value < 0.001, MSPE = 0.001). Additionally, final models were fit for all soil samples, which included only color variables, for lnSOC (R² = 0.959 Adj. R² = 0.949, RMSE = 0.007, p-value < 0.001, MSPE = 0.536) and lnTN (R² = 0.912 Adj. R² = 0.890, RMSE = 0.015, p-value < 0.001, MSPE = 0.001). The results suggest that soil color may be used for rapid assessment of SOC and TN in these agriculturally important soils.     

Mechanisms behind the stimulation of nitrification by N input in subtropical acid forest soil

Purpose

Input of N as NH₄ ⁺ is known to stimulate nitrification and to enhance the risk of N losses through NO₃ ^? leaching in humid subtropical soils. However, the mechanisms responsible for this stimulation effect have not been fully addressed.

Materials and methods

In this study, an acid subtropical forest soil amended with urea at rates of 0, 20, 50, 100 mg N kg^?1 was pre-incubated at 25 °C and 60 % water-holding capacity (WHC) for 60 days. Gross N transformation rates were then measured using a ¹⁵N tracing methodology.

Results and discussion

Gross rates of mineralization and nitrification of NH₄ ⁺-N increased (P?<?0.05), while gross rate of NO₃ ^? immobilization significantly decreased with increasing N input rates (P?<?0.001). A significant relationship was established between the gross nitrification rate of NH₄ ⁺ and the gross mineralization rate (R ²?=?0.991, P?<?0.01), so was between net nitrification rate of NH₄ ⁺ and the net mineralization rate (R ²?=?0.973, P?<?0.05).

Conclusions

Stimulation effect of N input on the gross rate of nitrification of NH₄ ⁺-N in the acid soil, partially, resulted from stimulation effect of N input on organic N mineralization, which provides pH-favorable microsites for the nitrification of NH₄ ⁺ in acid soils (De Boer et al., Soil Biol Biochem 20:845–850, 1988; Prosser, Advan Microb Physiol 30:125–181, 1989). The stimulated gross nitrification rate with the decreased gross NO₃ ^? immobilization rate under the elevated N inputs could lead to accumulation of NO₃ ^? and to enhance the risk of NO₃ ^? loss from humid forest soils.

     

Effect of organic residue amendment on mineralization of sulfur in flooded rice soils under laboratory conditions

Abstract

This study was undertaken to assess the mineralization of sulfur (S) in laboratory conditions of three rice soils (Joydebpur, Faridpur, and Thakurgaon), receiving the following treatments: 1) control, 2) rice straw (Oryza sativa L.), and 3) pea vine (Pisum sativum L.). The organic residue (25 mg g^‐1) was added and mixed with soil and glass beads (1:1, soil to bead ratio) and placed into a Pyrex leaching tube. The soils were flooded and incubated at 35°C, after which they were leached with deionized water at 1, 2,4, 8, and 12 weeks for analysis of SO₄ and other chemical properties in the leachates. Potentially mineralizable S (S_o) and C (C_o) pools and first‐order rate constants (K_s for S and K_c for C) in soils amended with rice straw and pea vine under flooded conditions were estimated using an exponential equation. The S_o and K_s varied considerably among the soils and types of added organic residues, and their values in rice straw and pea vine ranged from 8.70 to 29.55 and 0.124 to 0.732 mg S kg^‐1 wk^‐1, respectively. Except for the Thakurgaon soil, the S_o and K_s values in Joydebpur and Faridpur soils were higher in the unamended treatments. Higher S_o values in the unamended soils were probably due to less microbial activity to mineralize organic S from organic residues. The results indicate that the amount of SO₄ in flooded soils amended with organic residues are dependent on soil type, nature of organic residues, and time of incubation. The C_o and K_c values under flooded incubation were higher in residue amended soils than in unamended soils. Pea vine treated soils had higher C_o and K_c values than the soils treated with rice straw.     

Net sulfur mineralization potential in Swedish arable soils in relation to long-term treatment history and soil properties

The long-term treatment effect (since 1957–1966) of farmyard manure (FYM) application compared with crop residue incorporation was investigated in five soils (sandy loam to silty clay) with regards to the net sulfur (S) mineralization potential. An open incubation technique was used to determine accumulated net S mineralization (S_AccMin) and a number of soil physical and chemical properties were determined. Treatments and soil differences in S_AccMin, as well as correlations with soil variables, were tested with single and multivariate analyses. Long-term FYM application resulted in a significantly (p = 0.012) higher net S mineralization potential, although total amounts of C, N, and S were not significantly (p < 0.05) increased. The accumulated S mineralization differed significantly (p < 0.05) between soils within this treatment. The measured soil variables were not significantly correlated to S_AccMin. Conclusively, different treatment histories influenced the quality (e.g., chemical composition) and cycling rate of the organic S pool, rather than its size.     

NEEDLE S FRACTIONS AND S TO N RATIOS AS INDICES OF SO2 DEPOSITION

Needles of Scots pine (Pinus sylvestris L.) from 25 and 40 sampling plots in southern and northern Finland, respectively, that had earlier been analysed for total sulphur concentration (S_t) were reanalysed for foliar sulphate sulphur (SO₄–S) and total nitrogen (N_t). Organic sulphur content (S_o) was calculated as the difference between S_t and SO₄–S. Current (c) and previous-year (c+1) needles were collected from southern Finland in December 1989 and c – c+2 needles from northern Finland in September-October 1990/September 1992. The results show that the S_t concentration and S_t/N_t ratio in Scots pine needles are good indices of dry deposition of SO₂ in general, while SO₄–S concentrations and SO₄–S/S_o ratios can be used in areas with low N supply from the soil and/or low wet deposition of N. The normal S_t concentration in needles of Scots pines growing on a podzol with low N supply is considered to be 500–700 μg g^-1 and that of SO₄–S 100–200 μg g^-1. An increase of 100 μg g^-1 in needle S_t may be attributed to a rise of 1.4 μg m^-3 in ambient SO₂ concentration in areas with relatively low SO₂ concentrations (>15 μg m^-3). A critical level of 5 μg m^-3 as an annual and growing season mean is proposed for forestry in northern Europe (north of 60°N).     

硫肥对双低油菜产量与品质的影响

在澳大利亚新南威尔士州缺硫土壤上进行了硫、氮不同水平组合对双低油菜(Canola)的影响试验。结果表明,试验条件下施用硫肥可显著提高油菜产量及含油量。低硫(S10)或无硫(So)条件下,一定量的氮肥(N80)可提高子粒内的含硫量,但高硫条件下,高量氮肥则降低含硫量。植株体内的含硫量随生育进程趋于降低。施硫处理在抽苔期出现一吸硫高峰,而对照呈指数下降;但在开花期与角果充实期则保持相对稳定。氮肥对生长前期(莲座期与抽苔期)植株(茎、叶)含硫量的影响不显著,而中、后期(开花、角果充实期),则随施氮量的增加而显著降低。高量氮肥(N160)会降低子粒内的硫代葡萄糖甙含量;施硫,特别是在高施硫量条件下,其含量则明显增加,但仍远低于子粒硫代葡萄糖甙40mol/g的标准,因而不会影响脱油饼粕的饲喂质量。     

Application of VNIR and machine learning technologies to predict heavy metals in soil and pollution indices in mining areas

Purpose

Soil pollution indices are an effective tool in the computation of metal contamination in soil. They monitor soil quality and ensure future sustainability in agricultural systems. However, calculating a soil pollution index requires laboratory measurements of multiple soil heavy metals, which increases the cost and complexity of evaluating soil heavy metal pollution. Visible and near-infrared spectroscopy (VNIR, 350–2500 nm) has been widely used in predicting soil properties due to its advantages of a rapid analysis, non-destructiveness, and a low cost.

Methods

In this study, we evaluated the ability of the VNIR to predict soil heavy metals (As, Cu, Pb, Zn, and Cr) and two commonly used soil pollution indices (Nemerow integrated pollution index, NIPI; potential ecological risk index, RI). Three nonlinear machine learning techniques, including cubist regression tree (Cubist), Gaussian process regression (GPR), and support vector machine (SVM), were compared with partial least squares regression (PLSR) to determine the most suitable model for predicting the soil heavy metals and pollution indices.

Results

The results showed that the nonlinear machine learning models performed significantly better than the PLSR model in most cases. Overall, the SVM model showed a higher prediction accuracy and a stronger generalization for Zn (R²_V?=?0.95, RMSE_V?=?6.75 mg kg^?1), Cu (R²_V?=?0.95, RMSE_V?=?8.04 mg kg^?1), Cr (R²_V?=?0.90, RMSE_V?=?6.57 mg kg^?1), Pb (R²_V?=?0.86, RMSE_V?=?4.14 mg kg^?1), NIPI (R²_V?=?0.93, RMSE_V?=?0.31), and RI (R²_V?=?0.90, RMSE_V 3.88). In addition, the research results proved that the high prediction accuracy of the three heavy metal elements Cu, Pb, and Zn and their significant positive correlations with the soil pollution indices were the reason for the accurate prediction of NIPI and RI.

Conclusion

Using VNIR to obtain soil pollution indices quickly and accurately is of great significance for the comprehensive evaluation, prevention, and control of soil heavy metal pollution.

     

Sulphur mineralization kinetics as influenced by soil properties

A 10-week laboratory study, using an open incubation technique, was carried out to determine net sulphur (S) mineralization potentials of soil samples obtained from some representative soils in Tuscany, Italy. The time-course of organic S mineralization in the soils was analyzed by fitting the experimental values to three kinetic models (first-order, first-order E, zero-order). The first-order model was found to be the most suitable because it provided the best fit to the experimental data and for its simplicity. Potentially mineralized S (S ₀) values ranged from a minimum of 13.6 to a maximum of 50.7 mg kg⁻¹ soil and the mineralization rate k varied from 0.111 to 0.615 week⁻¹. It was also positively related to organic C, N, and S, protease, arylsulphatase, and dehydrogenase activities. The mineralization rate did not show any significant relationship with soil properties.     

Spatial and seasonal variations in soil respiration in a temperate deciduous forest with fluctuating water table

Our objectives were to determine both spatial and temporal variations in soil respiration of a mixed deciduous forest, with soils exhibiting contrasting levels of hydromorphy. Soil respiration (R_S) showed a clear seasonal trend that reflected those of soil temperature (T_S) and soil water content (W_S), especially during summer drought. Using a bivariate model (RMSE=1.03), both optimal soil water content for soil respiration (W_SO) and soil respiration at both 10 °C and optimal soil water content (R_S10) varied among plots, ranging, respectively, from 0.25 to 0.40 and from 2.30 to 3.60 μmol m⁻² s⁻¹. Spatial variation in W_SO was related to bulk density and to topsoil N content, while spatial variation in R_S10 was related to basal area and the difference in pH measured in water or KCl suspensions. These results offer promising perspectives for spatializing ecosystem carbon budget at the regional scale.     

Sulfur mineralization in two soils amended with organic manures,crop residues,and green manures

The mineralization of sulfur (S) was investigated in a Vertisol and an Inceptisol amended with organic manures, green manures, and crop residues. Field‐moist soils amended with 10 g kg^—1 of organic materials were mixed with glass beads, placed in pyrex leaching tubes, leached with 0.01 M CaCl₂ to remove the mineral S and incubated at 30 °C. The leachates were collected every fortnight for 16 weeks and analyzed for SO₄‐S. The amount of S mineralized in control and in manure‐amended soils was highest in the first week and decreased steadily thereafter. The total S mineralized in amended soils varied considerably depending on the type of organic materials incorporated and soil used. The cumulative amounts of S mineralized in amended soils ranged from 6.98 mg S (kg soil)^—1 in Inceptisol amended with wheat straw to 34.38 mg S (kg soil)^—1 in Vertisol amended with farmyard manure (FYM). Expressed as a percentage of the S added to soils, the S mineralized was higher in FYM treated soils (63.5 to 67.3 %) as compared to poultry manure amended soils (60.5 to 62.3 %). Similarly the percentage of S mineralization from subabul (Leucaena leucocephala) loppings was higher (53.6 to 55.5 %) than that from gliricidia (Gliricidia sepium) loppings (50.3 to 51.1 %). Regression analysis clearly indicated the dependence of S mineralization on the C : S ratio of the organic materials added to soil. The addition of organic amendments resulted in net immobilization of S when the C : S ratio was above 290:1 in Vertisol and 349:1 in Inceptisol. The mineralizable S pool (S_o) and first‐order rate constant (k) varied considerably among the different types of organic materials added and soil. The S_o values of FYM treated soils were higher than in subabul, gliricidia, and poultry manure treated soils.     

Effects of vertical distribution of soil inorganic nitrogen on root growth and subsequent nitrogen uptake by field vegetable crops

Information is needed about root growth and N uptake of crops under different soil conditions to increase nitrogen use efficiency in horticultural production. The purpose of this study was to investigate if differences in vertical distribution of soil nitrogen (N_inorg) affected root growth and N uptake of a variety of horticultural crops. Two field experiments were performed each over 2 years with shallow or deep placement of soil N_inorg obtained by management of cover crops. Vegetable crops of leek, potato, Chinese cabbage, beetroot, summer squash and white cabbage reached root depths of 0.5, 0.7, 1.3, 1.9, 1.9 and more than 2.4 m, respectively, at harvest, and showed rates of root depth penetration from 0.2 to 1.5 mm day^?1 °C^?1. Shallow placement of soil N_inorg resulted in greater N uptake in the shallow‐rooted leek and potato. Deep placement of soil N_inorg resulted in greater rates of root depth penetration in the deep‐rooted Chinese cabbage, summer squash and white cabbage, which increased their depth by 0.2–0.4 m. The root frequency was decreased in shallow soil layers (white cabbage) and increased in deep soil layers (Chinese cabbage, summer squash and white cabbage). The influence of vertical distribution of soil N_inorg on root distribution and capacity for depletion of soil N_inorg was much less than the effect of inherent differences between species. Thus, knowledge about differences in root growth between species should be used when designing crop rotations with high N use efficiency.     

Effect of organic residue amendment on mineralization of nitrogen in flooded rice soils under laboratory conditions

Abstract

This study was undertaken to assess the mineralization of nitrogen (N) in rice soils amended with organic residues under flooded condition. A lab incubation study with a 3x3 factorial design (two replications) was conducted with three rice soils (Joydebpur, Faridpur, and Thakurgaon) receiving the following treatments: 1) control, 2) rice straw (Oryza sativa L.), or 3) pea vine (Pisum sativum L.). The organic residue (25 mg straw g^‐1 soil) was mixed with soil and glass beads (1:1, soil to beads ratio), and transferred into a Pyrex leaching tube, flooded and then incubated at 35°C for up to 12 weeks. The soils in the leaching tubes were leached (while maintaining flooded condition) at 1,2,4, 8, and 12 weeks with deionized water for determination of NH₄‐N, NO₃‐N, pH, and Eh. Nitrogen mineralization in soils amended with rice straw was somewhat different than that of soils treated with pea vine. Soil treated with rice straw had a higher N mineralization rate than soils treated with pea vine, which was due to a lower carbon (C):N ratio for rice straw. The potentially mineralizable N pool (N_o) in soils amended with rice straw and pea vine under flooded conditions, estimated using a 1st order exponential equation, were 7 to 15 times, and 3 to 9 times greater for rice straw N_o values and pea vine, respectively, than the control. The K_N values for unamended soils ranged from 0.35 to 0.52 mg N kg^‐1 wk^‐1 and rice straw and pea vine treated soils were from 0.75 to 1.22 and 0.46 to 0.58 mgN kg^‐1 wk^‐1. The lower N_o and K_N values in pea vine treatments suggested there was greater immobilization of N than in rice straw treatments.     

Spatial patterns of soil respiration in a spruce-fir valley forest,Northeast China

Purpose

The quantification of spatial patterns of soil respiration (R_S) is an important step in modelling soil carbon budgets. This study aims to characterise the spatial variability of R_S using traditional and geostatistical analyses in a mature temperate forest during the growing season, with emphases on temporal variation in the spatial patterns and soil properties and stand structural parameters driving the variability of R_S.

Materials and methods

R_S, soil temperature and soil water content were sampled at 780 positions in a 9.12-ha permanent plot in a spruce-fir valley forest in the spring, summer and autumn of 2015. Furthermore, edaphic properties were measured adjacent to each sampling point, and all trees with DBH (diameter at breast height of tree) greater than 1 cm were mapped in the plot.

Results and discussion

R_S showed strong spatial variation across the three measurement campaigns, with the autocorrelation length ranging from 10 to 17 m. The spatial variability of R_S in the spring period was relatively higher than that of summer and autumn. Soil water content was confirmed to be the primary factor driving spatial R_S, followed by soil temperature, soil organic carbon, total nitrogen, C:N, pH and the maximum DBH within radius of 4 m of sampling points. The multiple regression model fitted by soil properties and stand structural parameters could account for 11–32% of the spatial variation of R_S. However, the involved factors in the regression model varied with season, and soil temperature was more important in controlling the spatial variability of R_S in the spring period.

Conclusions

The study highlights that soil water content and soil temperature play the most important role in determining the spatial patterns of R_S across the growing season.

     

A comparison of trenched plot techniques for partitioning soil respiration

Partitioning the soil surface CO₂ flux (R_S) flux is an important step in understanding ecosystem-level carbon cycling, given that R_S is poorly constrained and its source components may have different sensitivities to climate change. Trenched plots are an inexpensive but labor-intensive method of separating the R_S flux into its root (autotrophic) and soil (heterotrophic) components. This study tested if various methods of plant suppression in trenched plots affected R_S fluxes, quantified the R_S response to soil temperature and moisture changes, and estimated the heterotrophic contribution to R_S. It was performed in a boreal black spruce (Picea mariana) plantation, using a randomized complete block design, during the 2007 and 2008 growing seasons. Trenched plots had significantly lower R_S than control plots, with differences appearing ∼100 days after trenching; spatial variability doubled immediately after trenching but then declined throughout the experiment. Most trenching treatments had significantly lower (by ∼0.5 μmol CO₂ m⁻² s⁻¹) R_S than the controls, and there was no significant difference in R_S among the various trenching treatments. Soil temperature at 2 cm explained more R_S variability than did 10-cm temperature or soil moisture. Temperature sensitivity (Q₁₀) declined in the control plots from ∼2.6 (at 5 °C) to ∼1.6 (at 15 °C); trenched plots values were higher, from 3.1 at 5 °C to 1.9 at 15 °C. We estimated R_S for the study period to be 241 ± 40 g C m⁻², with live roots contributing 64% of R_S after accounting for fine root decay, and 293 g C m⁻² for the entire year. These findings suggest that laborious hand weeding of trenched plot vegetation may be replaced by other methods, facilitating future studies of this large and poorly-understood carbon flux.     

Major controlling factors and prediction models for mercury transfer from soil to carrot

Purpose

Soil-plant transfer models are needed to predict levels of mercury (Hg) in vegetables when evaluating food chain risks of Hg contamination in agricultural soils.

Materials and methods

A total of 21 soils covering a wide range of soil properties were spiked with HgCl₂ to investigate the transfer characteristics of Hg from soil to carrot in a greenhouse experiment. The major controlling factors and prediction models were identified and developed using path analysis and stepwise multiple linear regression analysis.

Results and discussion

Carrot Hg concentration was positively correlated with soil total Hg concentration (R ²?=?0.54, P?<?0.001), and the log-transformation greatly improved the correlation (R ²?=?0.76, P?<?0.001). Acidic soil exhibited the highest bioconcentration factor (BCF) (ratio of Hg concentration in carrot to that in soil), while calcareous soil showed the lowest BCF among the 21 soil types. The significant direct effects of soil total Hg (Hg_soil), pH, and free Al oxide (Al_OX) on the carrot Hg concentration (Hg_carrot) as revealed by path analysis were consistent with the result from stepwise multiple linear regression that yielded a three-term regression model: log [Hg_carrot]?=?0.52log [Hg_soil]???0.06pH???0.64log [Al_OX]???1.05 (R ²?=?0.81, P?<?0.001).

Conclusions

Soil Hg concentration, pH, and Al_OX content were the three most important variables associated with carrot Hg concentration. The extended Freundlich-type function could well describe Hg transfer from soil to carrot.     

Near infrared reflectance spectroscopy: A tool to characterize the composition of different types of exogenous organic matter and their behaviour in soil

In addition to total organic carbon and nitrogen, potential organic carbon mineralization under controlled laboratory conditions and indicators such as the indicator of remaining organic carbon in soil (I_ROC), based on Van Soest biochemical fractionation and short-term carbon mineralization in soil, are used to predict the evolution of exogenous organic matter (EOM) after its application to soils. The purpose of this study was to develop near infrared reflectance spectroscopy (NIRS) calibration models that could predict these characteristics in a large dataset including 300 EOMs representative of the broad range of such materials applied to cultivated soils (plant materials, animal manures, composts, sludges, etc.). The NIRS predictions of total organic matter and total organic carbon were satisfactory (R²_P = 0.80 and 0.85, ratio of performance to deviation, RPD_P = 2.2 and 2.6, respectively), and prediction of the Van Soest soluble, cellulose and holocellulose fractions were acceptable (R²_P = 0.82, 0.73 and 0.70, RPD_P = 2.3, 1.9 and 1.8, respectively) with coefficients of variation close to those of the reference methods. The NIRS prediction of carbon mineralization during incubation was satisfactory and indeed better regarding the short-term results of mineralization (R²_P = 0.78 and 0.78, and RPD_P = 2.1 and 2.0 for 3 and 7 days of incubation, respectively). The I_ROC indicator was predicted with fairly good accuracy (R²_P = 0.79, RPD_P = 2.2). Variables related to the long-term C mineralization of EOM in soil were not predicted accurately, except for I_ROC which was based on analytical and well-identified characteristics, probably because of the increasing interactions and complexity of the factors governing EOM mineralization in soil as a function of incubation time. This study demonstrated the possibility of developing NIRS predictive models for EOM characteristics in heterogeneous datasets of EOMs. However, specific NIRS predictive models still remain necessary for sludges, organo-mineral fertilizers and liquid manures.     

Kinetics of C and N mineralization, N immobilization and N volatilization of organic inputs in soil

C and N mineralization data for 17 different added organic materials (AOM) in a sandy soil were collected from an incubation experiment conducted under controlled laboratory conditions. The AOM originated from plants, animal wastes, manures, composts, and organic fertilizers. The C-to-N_AOM ratios (η_AOM) ranged from 1.1 to 27.1. Sequential fibre analyses gave C-to-N ratios of soluble (η_Sol), holocellulosic (η_Hol) and ligneous compounds (η_Lig) ranging from 1.1 to 57.2, 0.8 to 65.2, and 3.5 to 25.3, respectively. Very different patterns of net AOM-N mineralization were observed: (i) immobilization for four plant AOM; (ii) moderate mineralization (4-15% AOM-N) for composts; (iii) marked mineralization (11-27% AOM-N) for 1 animal AOM, 1 manure and 2 organic fertilizers; and (iv) high rates of transformations with possible gaseous losses for some N-rich AOM.The Transformation of Added Organics (TAO) model proposed here, described AOM-C mineralization (28 °C, 75% WHC) from three labile (L′), resistant (R) and stable (S) compartments with the sole parameters P′_L and P_S=fractions of very labile and stable compounds of AOM, respectively. Dividing the C-compartments by their C-to-N estimates supplied the remaining N_AOM fraction (RAONF). A P_im parameter split the TAO nitrogen fraction (TAONF=added N-RAONF) into two compartments, immobilized (imN) and inorganic (inorgN) N. A P_im>0 value meant that all the TAONF plus a fraction (P_im−1) of native soil inorganic N was immobilized. Additional N mineralization was predicted when necessary from imN by first order kinetics (constant k_remin). The TAO version with two parameters P_im and k_remin allowed us to predict very different patterns of N mineralization and N immobilization. In a few cases, a further first order kinetic law (constant k_v) was added to predict N volatilization from inorgN. Two hypotheses were tested: (i) η_L′, η_R, η_S (C-to-N of L′, R and S)=η_Sol, η_Hol, η_Lig, respectively, (ii) η_L′=η_R=η_S=η_AOM. The first hypothesis was validated by these data, and the second was a good approximation of the former one. In all the cases, predictions were in good agreement with measured values.     

Biochemical Oxygen Demand Relationships in Typical Agricultural Effluents

Understanding the variables controlling biochemical oxygen demand (BOD) of effluents from agricultural systems is essential for predicting and managing the water quality risks associated with agricultural production. In this study, short- and long-term oxygen demand behaviors of waters from primarily agricultural sources and their relationships with other parameters were evaluated. A total of 46 water samples were generated from diverse organic sources commonly associated with agricultural activities and analyzed for BOD and other various water quality parameters. Short-term BOD (BOD₂ and BOD₅) were significantly correlated with total organic carbon (TOC), particulate organic carbon (POC), and dissolved organic carbon (DOC) (R ²?=?0.62–0.77, p?<?0.001), likewise to total nitrogen, total Kjeldahl nitrogen, and nitrite–nitrogen (NO₂–N) (R ²?=?0.40–0.55, p?<?0.001). Long-term BOD (BOD₆₀) was generally poorly correlated with these C and N fractions. Phosphate (PO₄–P) exhibited a positive and linear relationship with both short- and long-term BOD, whereas chloride (Cl) tended to inhibit oxygen demand. Multivariate combinations of each of TOC, POC, and DOC with NO₂–N, and Cl or PO₄–P improved the predictions of both short- and long-term BOD. The ultimate BOD (BOD_u) derived from the first-order kinetics was highly correlated with BOD₆₀ (R ²?=?0.81, p?<?0.001) whereas BOD₆₀ was correlated with BOD₅ (R ²?=?0.60, p?<?0.001). Overall the results indicated that C and N forms along with PO₄–P and Cl were the dominant factors controlling the oxygen demand behaviors of agricultural effluents.     

Effect of Repeated Applications of Elemental Sulfur on Microbial Population,Sulfate Concentration,and pH in Soils

Abstract

Though there exists a wide spectrum of sulfur‐oxidizing microorganisms in soils, the oxidation rate of soil‐applied elemental sulfur (S⁰) is regularly limited because of a restricted population size. An incubation experiment was conducted to determine the effect of repeated S⁰ applications on different microbial populations, sulphate (SO₄ ^2?)‐S concentration, and soil pH. Elemental sulfur was applied repeatedly at a rate of 15 mg S g^?1 soil in a 15‐day interval cycle of 7 times. After each cycle, 7.5 mg lime (CaCO₃) g^?1 soil was applied to adjust the soil pH to an optimum range. Soil pH and 0.025 M potassium chloride (KCl)–extractable SO₄ ^2?‐S were determined every 3 days. The population of Thiobacillus spp. and aerobic heterotrophic sulfur‐oxidizing bacteria were counted 3 and 15 days after each S⁰ application. The results showed that the soil pH decreased rapidly from an initial value of 7.6 to 5.3, 15 days after the first S⁰ application. Lime applications successfully counterbalanced the acidifying effect of S⁰ oxidation, and soil pH values were maintained in the optimum range with a pH of about 6.4. The 0.025 M KCl–extractable SO₄ ^2?‐S content increased with repeated applications of S⁰, showing a maximum value of 3,800 mg S kg^?1 soil after the sixth S⁰ application. Thereafter, the SO₄ ^2?‐S concentration decreased significantly. The Thiobacillus spp.count increased consistently with repeated S⁰ applications. The number of Thiobacillus spp. at the first application of S⁰ was significantly lower than the count after all other applications. A maximum Thiobacillus spp. count of 1.0 · 10⁸ g^?1 soil was observed after the seventh application of S⁰. The fastest S⁰ oxidation rate was found after the second application of S⁰. The population of aerobic heterotrophic sulfur‐oxidizing bacteria increased also with repeated S⁰ applications, showing a maximum count of 5.0 · 10⁴ g^?1 soil after the fourth S⁰ application. Thereafter, the population declined steadily. Significant relationships between SO₄ ^2?‐S concentration and count of Thiobacillus spp. (R²=0.85, p<0.01) and aerobic heterotrophic sulfur‐oxidizing bacteria (R²=0.63, p<0.01) were found. Based on these results, it may be concluded that repeated S⁰ applications decrease soil pH, increase Thiobacillus spp. counts, and thus increase extractable SO₄ ^2?‐S concentration in soils. The results further suggest that soils that receive regular S⁰ applications have a higher Thiobacillus spp. count and thus have conjecturally a higher S⁰ oxidation potential than soils that have never received S⁰. This again indicates a priming effect of S⁰ oxidation by Thiobacillus spp., which needs to be confirmed under field conditions.