Leticia Sonon

Release of Nitrogen and Phosphorus from Poultry Litter Amended with Acidified Biochar

Application of poultry litter (PL) to soil may lead to nitrogen (N) losses through ammonia (NH3) volatilization and to potential contamination of surface runoff with PL-derived phosphorus (P). Amending litter with acidified biochar may minimize these problems by decreasing litter pH and by retaining litter-derived P, respectively. This study evaluated the effect of acidified biochars from pine chips (PC) and peanut hulls (PH) on NH3 losses and inorganic N and P released from surface-applied or incorporated PL. Poultry litter with or without acidified biochars was surface-applied or incorporated into the soil and incubated for 21 d. Volatilized NH3 was determined by trapping it in acid. Inorganic N and P were determined by leaching the soil with 0.01 M of CaCl2 during the study and by extracting it with 1 M KCl after incubation. Acidified biochars reduced NH3 losses by 58 to 63% with surface-applied PL, and by 56 to 60% with incorporated PL. Except for PH biochar, which caused a small increase in leached NH4 +-N with incorporated PL, acidified biochars had no effect on leached or KCl-extractable inorganic N and P from surface-applied or incorporated PL. These results suggest that acidified biochars may decrease NH3 losses from PL but may not reduce the potential for P loss in surface runoff from soils receiving PL.

Salt Concentration and Measurement of Soil pH

The measured value of soil pH depends in part on the laboratory procedures used, such as the soil–solution ratio and soil solution electrolyte composition. One of the most significant factors affecting the measured value of soil pH is the electrolyte concentration of the soil solution. Since electrolyte concentration of agricultural soils can vary greatly during the year and between years, the date of sampling can result in highly variable pH values for samples with the same percentage of base saturation when soil pH is measured in deionized water. For example, we found a different relationship between extractable calcium (Ca) and pH (1:1 in deionized water) for about 18,000 soil samples from the same geographic area taken during winter of 2 years, differing in winter rainfall. On average, samples taken during the wetter year had higher pH for a given value of extractable Ca, consistent with a reduced ionic strength (more leaching) in the wet year. In a comparison of pH in water with pH in 0.01 M calcium chloride (CaCl2) for 1,186 soil samples received from clients, the median difference in pH was 0.67. It is notable that 20% of the samples had a difference of >0.8 and 10% had a difference of >0.9 pH units. Some samples with differences larger than the median may not receive a lime recommendation when needed because of the erroneously high pH reading in water caused by low ionic strength. The stability of pH readings in 0.01 M CaCl2 essentially eliminates this problem.

Implementation of Soil Lime Requirement by a Single‐Addition Titration Method

Abstract Buffers for determining a soils lime requirement (LR) sometimes contain hazardous chemicals. Our objective was to implement a single‐addition titration with calcium hydroxide [Ca(OH)2] to determine the LR of soils. The soil pH buffering capacity is calculated from the rise in pH from a single addition of base. The LR is calculated from the soil pH buffering capacity, the target pH, and initial soil pH. The LR of 531 randomly selected client samples determined by single‐addition titration were slightly higher than by the Adams–Evans (AE) buffer procedure when LRs were less than 1800 lb per acre. The new procedure recommended about 11% less lime than AE at LRs greater than 1800 lb per acre. Independent evaluations of samples that gave the most widely different LR revealed that the single‐addition titration was more accurate and more precise than the AE buffer.

Comparison of Conductimetric and Colorimetric Methods with Distillation–Titration Method of Analyzing Ammonium Nitrogen in Total Kjeldahl Digests

The distillation–titration method (DTM) is a standard procedure used by most laboratories to measure ammonium-nitrogen (NH4-N) in the total Kjeldahl N (TKN) digests of various kinds of agricultural and environmental samples. These samples may have TKN contents ranging from less than 100 ppb to as high as percentage levels. However, the DTM procedure generally leads to a very low throughput because it is labor intensive and time-consuming. At the current practical quantitation limit (PQL) of 300 ppb established at the Feed and Environmental (FEW) Laboratory, University of Georgia, the DTM procedure is less applicable to low TKN surface water samples. In this study, we therefore compared the performance of diffusion conductivity method (DCM) and colorimetric method (CM) with DTM in measuring NH4-N in the TKN digests of 29 different samples representing surface waters, lagoons, manures, poultry litters, and environmental wastes. Acceptable accuracy and precision were achieved for various QC samples by all three methods. For widely different sample matrices and TKN contents, the NH4-N in the TKN digests measured by DCM and CM both agreed well with that measured by DTM. However, the linear working range of CM is limited within 0.2 to 5.0 ppm, whereas DCM is linear at a wider range of 0.01 to 2000 ppm. With DCM, the PQL of TKN is at 13 ppb, much less than the 300 ppb in DTM and 520 ppb in CM. Both DCM and CM require increasing the pH of the working TKN digest to a highly alkaline range. To meet such pH requirement, the minimum dilution need for DCM is twofold, where as that CM is fourfold. Because of greater mandatory dilution requirement coupled with a greater PQL, CM may often fail to measure NH4-N in the working TKN digest of some low TKN surface water samples. On the other hand, with some environmental waste samples containing TKN at percentage level, CM would require multistep dilution of the digests prior to measurement, thus allowing dilution-related error as well as requiring additional labor. In contrast, DCM can measure both low TKN surface waters and high TKN environmental wastes without any major limitations. Moreover, DCM may work well without any adjustment of sample background in the calibration standards. Thus DCM appears to be an attractive alternative to the labor-intensive and time-consuming DTM for measuring NH4-N in the TKN digests of various kinds of agricultural and environmental samples in the analytical services laboratories.

Prediction of calorific values, moisture, ash, carbon, nitrogen, and sulfur content of pine tree biomass using near infrared spectroscopy

Loblolly (Pinus taeda) and slash (Pinus elliottii) pine tree biomass are significant renewable energy resources for bioenergy industries in the Southeastern United States. There is a great need for evaluation of their properties (relevant to production and evaluation-screening for bioenergy extraction) by rapid but accurate analytical methods like near infrared reflectance (NIR) spectroscopy. However, no attempts have been made so far to develop useful NIR spectroscopic calibration models for analyzing biomass of these two species. In this study, acceptable NIR spectroscopic calibration models were developed for: gross calorific value, GCV (n = 181; R2 = 0.83; ratio of standard error of cross-validation to deviation, RSCD = 2.32; ratio of standard error of cross-validation to inter-quartile distance, RSCIQ = 2.68); net calorific value, NCV (n = 184; R2 = 0.83; RSCD = 2.31; RSCIQ = 2.69); ash-free calorific value, AFCV (n = 184; R2 = 0.83; RSCD = 2.24; RSCIQ = 2.49); moisture (n = 181; R2 = 0.85; RSCD = 2.54; RSCIQ = 2.30); ash (n = 180; R2 = 0.86; RSCD = 2.65; RSCIQ = 2.62); total carbon, C (n = 101; R2 = 0.95; RSCD = 3.01; RSCIQ = 5.66); total nitrogen, N (n = 87; R2 = 0.95; RSCD = 4.24; RSCIQ = 4.76); and total sulfur, S (n = 83; R2 = 0.97; RSCD = 4.17; RSCIQ = 3.05) contents of these biomasses though the calibration models for NCV and AFCV are indirect calibration. Prediction of the independent validation sets yielded good agreement between the NIR spectroscopic predicted values and the laboratory reference values for each of: GCV (n = 92; r2 = 0.89; ratio of performance to deviation; RPD = 3.01; ratio of performance to inter-quartile distance, RPIQ = 3.16); NCV (n = 91; r2 = 0.83; RPD = 2.43; RPIQ = 3.06); AFCV (n = 91; r2 = 0.80; RPD = 2.25; RPIQ = 2.83); moisture (n = 92; r2 = 0.82; RPD = 2.38; RPIQ = 2.40); ash (n = 89; r2 = 0.81; RPD = 2.30; RPIQ = 2.66); C (n = 43; r2 = 0.90; RPD = 3.14; RPIQ = 3.23); N (n = 44; r2 = 0.95; RPD = 4.33; RPIQ = 5.96); and S (n = 42; r2 = 0.93; RPD = 3.67; RPIQ = 3.24) contents, indicating that all eight calibration models had good quantitative information. The standard errors of prediction for all models were less than twice the corresponding standard error of laboratory. Therefore, precise, accurate, and rapid analysis of calorific values and C, N, S contents of these biomasses can be done using these novel NIR spectroscopic calibration models developed.

Near-infrared spectroscopic models for analysis of winter pea (Pisum sativum L.) quality constituents: Near-infrared spectroscopic models for analysis of winter pea

BACKGROUND Winter pea (Pisum sativum L.) grows well in a wide geographic region, both as a forage and cover crop. Understanding the quality constituents of this crop is important for both end uses; however, analysis of quality constituents by conventional wet chemistry methods is laborious, slow and costly. Near infrared reflectance spectroscopy (NIRS) is a precise, accurate, rapid and cheap alternative to using wet chemistry for estimating quality constituents. We developed and validated NIRS calibration models for constituent analysis of this crop. RESULTS Of the 11 constituent models developed, nine constituents including moisture, dry-matter, total-nitrogen, crude protein, acid detergent fiber, neutral detergent fiber, AD-lignin, cellulose and non-fibrous carbohydrate had low standard errors and a high coefficient of determination (R2 = 0.88-0.98; 1 - VR, which is the coefficient of determination during cross-validation = 0.77-0.92) for both calibration and cross-validation, indicating their potential for quantitative predictability. The calibration models for ash (R2 = 0.65; 1 - VR = 0.46) and hemicellulose (R2 = 0.75; 1 - VR = 0.50) also appeared to be adequate for qualitative screening. Predictions of an independent validation set yielded reliable agreement between the NIRS predicted values and the reference values with low standard error of prediction (SEP), low bias, high coefficient of determination (r2 = 0.82-0.95), high ratios of performance to deviation (RPD = SD/SEP; 2.30-3.85) and high ratios of performance to interquartile distance (RPIQ = IQ/SEP; 2.57-7.59) for all 11 constituents. CONCLUSION Precise, accurate and rapid analysis of winter pea for major forage and cover crop quality constituents can be performed at a low cost using the NIRS calibration models developed.

A Comparison of Diffusion-Conductimetric and Distillation-Titration Methods in Analyzing Ammonium- and Nitrate-Nitrogen in the KCl-Extracts of Georgia Soils

ABSTRACT Soil mineral (or inorganic) nitrogen (SMN), which primarily exists as exchangeable and soluble ammonium (NH4+) and the nitrate (NO3−) ions, represents readily available nitrogen for plant growth. Over the years a 2M potassium chloride (KCl) solution has become the extraction solution of choice for extracting SMN. In the research and service laboratories, either distillation-titration method (DTM) or colorimetric method (CM) is virtually the standard to measure NH4+- and NO3−-N in the 2M KCl soil extracts. However, being a time-consuming and labor intensive method, DTM generally has a very low throughput. Likewise, CM is affected by interferences from pH variation, color, turbidity, presence of organic species, and some other constituents in the extracts. In contrast, diffusion conductivity method (DCM) is a less expensive and high throughput one, which is also relatively free from common interferences. In this study, we, therefore, compared the extraction efficiency of various KCl concentrations and performance of diffusion conductivity method (DCM) with DTM in measuring NH4+-N and NO3−-N in KCl extracts of 32 agricultural soils of Georgia. A 0.2M KCl solution extracted statistically similar amounts of NH4+-N and NO3−-N as did 2M KCl, suggesting that a 10-fold dilute KCl solution than the standard 2M KCl might be good enough to extract and estimate the most of SMN. For the analyses of NH4+- and NO3−-N in the KCl extracts, the DCM produced results statistically similar to those produced by DTM. The deviation between the results given by DCM and DTM was no more than ±10%. Thus, DCM appears to be an attractive alternative to the labor intensive and time-consuming DTM for measuring NH4+- and NO3−-N in the KCl extract of soils in the research and service laboratories.

The Effect of Drought on Lignin Content and Digestibility of Tifton-85 and Coastal Bermudagrass ( Cynodon dactylon L.) Hays Produced in Georgia

Digestibility of “Tifton 85” Bermudagrass has been noted to be higher than most other Bermudagrass cultivars. However, the superior digestibility of Tifton-85 has not been verified based on samples from producers, nor is it known how water availability might affect this comparison. Recent past weather conditions in Georgia allowed this comparison. Much of Georgia was in severe drought in 2007 and 2008. In contrast, there was less/no drought in 2006 and 2009. In each of these years, producers submitted a substantial number of Tifton-85 and Coastal forage samples to our laboratory for lignin and “Digestible Neutral Detergent Fiber (dNDF48)” analyses. Over all years, Tifton-85 had lower lignin content than coastal. However, Tifton-85 had significantly lower lignin content only in drought free 2006 and 2009, whereas the lignin content of Coastal was unaffected by drought in 2007 and 2008. The lignin of Tifton-85 increased during these two drought years. Despite this, the dNDF48 for Tifton-85 was significantly higher than coastal in all four years, suggesting that drought had hardly any effect on the digestibility of Tifton-85. Apparently, the type of lignin in Tifton-85 is different from that in coastal. Higher dNDF48 for Tifton-85 has been attributed to its lower concentrations of ether-linked ferulic acid than in Coastal. Decreased ether bonding in lignin results in higher digestion.

Efficiency of Commercial Agricultural-Grade Limestone

The University of Georgia (GA) lime recommendation equation includes a multiplier of 1.5 to account for agricultural (ag) lime that is less reactive than reagent-grade calcium carbonate (CaCO3). Research has not been conducted with ag lime to arrive at this multiplier with GA soils typical of the coastal plain or with ag limes available in GA. These ag limes may differ in their reactivity from others tested previously. The efficiency of five dolomitic ag limes were compared to reagent-grade CaCO3 on two GA soils with different pH-buffering capacities. Reactions other than acid neutralization by lime affected pH, especially in the soil with low pH-buffering capacity. Results from the soil with high pH-buffering capacity yielded multipliers of 1.17, 1.16, 1.48, 1.34, and 1.73 for ag limes 1 through 5, respectively, with an average multiplier of 1.38. Based on these results, continued use of a multiplier of 1.5 is appropriate.