Nitrogen and/or phosphorus fertilization effects on organic carbon and mineral contents in the rhizosphere of field grown sorghum

The effects of nitrogen (N) and/or phosphorus (P) fertilizers on the nutritional status in the rhizosphere were studied by monitoring throughout the growth period the concentrations of organic carbon (C), inorganic N, NaHCO₃ extractable P, exchangeable K, Ca, and Mg in sorghum (Sorghum bicolor L. Moench) down in an Alfisol field, and of all these elements except for extractable P, and exchangeable Ca in a Vertisol field in semi-arid tropical India. These concentrations were compared between the rhizosphere soil and bulk soil of sorghum grown in both fields.

Organic C content of the rhizosphere soil increased with plant age and was significantly higher than that in the bulk soil throughout the growth of sorghum, but it was not affected by the rates of N or P fertilizer. Inorganic N concentration in the rhizosphere soil was significantly higher than that in the bulk soil until maturity in sorghum. The content of available P in the rhizosphere soil was significantly higher than in the bulk soil after the middle of the growth stage. Its average concentration in the rhizosphere soil across growth stages was significantly higher than in the bulk soil, which contradicts the observation in many reports that there is a depletion of P in the rhizosphere soil. The concentration of three exchangeable cations, K, Ca, and Mg, showed different patterns in the rhizosphere and the bulk soils. The concentration of K was almost constantly higher in the rhizosphere soil than in the bulk soil, Ca concentration was not different between the two soils, and Mg concentration was significantly higher in the bulk soil than in the rhizosphere soil. The reasons for these discrepancies cannot be explained at present. The concentrations of these cations were not affected by the rate of N or P fertilizer except for Mg at a later growth stage. The differences between rhizosphere and bulk soils in Alfisol were similar to those in Yertisol with respect to the concentration of organic C, inorganic N, and exchangeable K and Mg.     

Diversity of entomopathogenic bacteria associated with the white grub, Brahmina coriacea

A survey of potato fields located in the south-eastern region of Himachal Pradesh (India) was carried out in order to find out the natural pathogens infecting the white grub, Brahmina coriacea. About 88 % population of the infected grubs were found to exhibit symptoms of natural bacterial infection during the years 2007–2008. Hence, we attempted to isolate and characterize the most potent bacteria for the management of B. coriacea and tested their insecticidal activity. In this study, ten different bacterial isolates belonging to genera Bacillus, Psychrobacter, Paracoccus, Paenibacillus, Mycobacterium, Staphylococcus and Novosphingobium were isolated from B. coriacea. Bacterial species were identified based on morphology, biochemical tests and homologies of 16S rRNA gene sequences. Pathogenicity tests for all isolated bacteria at 1.0 × 10⁸ cfu/ml of broth were performed on late first instar grubs. Among the bacteria tested, Bacillus cereus induced highest mortality level of 51.85 % within 7 days of treatment followed by Psychrobacter pulmonis (33.33 %), Bacillus psychrodurans (25.93 %), Bacillus pumilus (25.93 %), Paenibacillus tylopili (22.22 %) and Novosphingobium capsulatum (18.52 %). Mortality levels were further increased up to 100 % by B. cereus followed by 88.89 % by P. pulmonis after 30 days of treatment. Our results indicate that B. cereus, P. pulmonis, B. psychrodurans, B. pumilus, P. tylopili and N. capsulatum may be valuable biological control agents for white grubs, B. coriacea.     

Number of Samples Required for the Estimation of Residual Soil Nitrate-Nitrogen: a Risk Based Analysis

A field experiment was conducted to determine the number of soil samples required to estimate the average residual soil nitrate (NO₃ ^-) in a given field under no-till and conventional tillage conditions. Four soil sampling devices (a 20.3-cm power earth auger, a 5.1-cm hand earth auger, a 3.2-cm soil probe, and a 1.9-cm soil probe) were used to collect soil samples from 35 locations each within the conventionally tilled and no-till fields. Soil samples were analyzed for soil water contents and NO₃ ^- concentrations in the soil for various depths. Simple graphs and tables were constructed which could be used by farmers and other professionals for estimating the average residual soil NO₃ ^- contents at a given confidence level or with a certain degree of risk. The confidence interval was taken as the difference between the highest and lowest value of the quartile range of the observed data. The results of this study indicated that the number of soil samples required to estimate the average residual soil NO₃ ^- contents increased as the degree of risk decreased. This study also indicated that the number of soil samples required for making a reasonable estimate of the residual soil NO₃ ^- contents were greater for a no-till field compared with the conventional tillage field.     

Strengthening Analytical Support in Agricultural Research

The need for analytical support in agricultural research and development has long been recognized, especially for soil fertility evaluation and management, assessment of crop and food quality, and selection and breeding of nutritious food staples. In addition, the demand for analytical research support in the general areas of agriculture interfacing with human health and environmental quality has greatly increased in recent years. The trend for increased demand for analytical support will most likely continue in the future. To meet such diverse, increasing demands for analytical support, we need to upgrade infrastructure facilities and simultaneously teach and train students and young researchers in the use of modern analytical tools. This is prerequisite to providing timely, efficient, and effective analytical support, as such support is the key to monitoring, assessing, and maintaining soil, food, and environmental quality and to breeding nutritious food staples.     

Effect of Lime Application on the Movement of Atrazine and Nitrate-Nitrogen Through Undisturbed-Saturated Soil Columns

Adsorption studies of Cr(III) on biogas residual slurry (BRS) were caried out under varying conditions of shaking time (5–180 min), metal ion concentration (10–40 mg L^-1), adsorbent concentration (1.0 to 8.0 g L^-1) and initial pH (1.5–5.0). Adsorption follows Langmuir isotherm, being endothermic in nature. For a Cr(III) concentration of 10 mg L^-1, a maximum removal of 85% by 4 g L^-1 of adsorbent was obtained at an initial pH ≥ 3.0. Desorption of Cr(III) from the spent adsorbent has also been investigated. Removal of Cr(III) from tannery wastewater by BRS was testified.     

Response of interspecific and sativa upland rices to Mali phosphate rock and soluble phosphate fertilizer

In West Africa, two-thirds of upland rice is grown on acidic phosphorus (P)-deficient soils. Phosphorus is one of the most limiting-nutrients affecting crop productivity. A three-year field experiment was conducted on a Ferralsol in Côte d'Ivoire to study the response of four interspecific rice cultivars and a sativa (control cultivar) to Tilemsi phosphate rock (PR) and soluble triple superphosphate (TSP) fertilizer. PR was applied at 0, 150, 300, and 450 kg ha^?1 P once in the first year and residual effects were measured in the following years. TSP (0, 50, 100 and 150 kg ha^?1 P) was applied yearly. More significant yield increasing (38%) was observed in the second year. Annual application of 50 kg P ha^?1 as TSP or a one-time application of 150 kg P ha^?1 as PR was the optimum rate for the production of all cultivars. Higher rates of P from TSP (100 and 150 kg P ha^?1) gave 2–3 times greater residual P in soil than the optimum rate, inducing no further response of rice. Two interspecific cultivars were identified as the most acid- and low P-tolerant cultivars for improving rice production in West Africa humid forest zone.     

Comparing multivariate regression and artificial neural network to predict barley production from soil characteristics in northern Iran

In this study artificial neural network (ANN) models were designed to predict the biomass and grain yield of barley from soil properties; and the performance of ANN models was compared with earlier tested statistical models based on multivariate regression. Barley yield data and surface soil samples (0–30 cm depth) were collected from 1 m² plots at 112 selected points in the arid region of northern Iran. ANN yield models gave higher coefficient of determination and lower root mean square error compared to the multivariate regression, indicating that ANN is a more powerful tool than multivariate regression. Sensitivity analysis showed that soil electrical conductivity, sodium absorption ratio, pH, total nitrogen, available phosphorus, and organic matter consistently influenced barley biomass and grain yield. A comparison of the two methods to identify the most important factors indicated that while in the ANN analysis, soil organic matter (SOM) was included among the most important factors; SOM was excluded from the most important factors in the multivariate analysis. This significant discrepancy between the two methods was apparently a consequence ofthe non-linear relationships of SOM with other soil properties. Overall, our results indicated that the ANN models could explain 93 and 89% of the total variability in barley biomass and grain yield, respectively. The performance of the ANN models as compared to multivariate regression has better chance for predicting yield, especially when complex non-linear relationships exist among thefactors. We suggest that for further potential improvement in predicting thebarley yield, factors other than the soil properties considered such as soil micronutrient status and soil and crop management practices followed during the growing season, need to be included in the models.     

N-Application Methods and Precipitation Pattern Effects on Subsurface Drainage Nitrate Losses and Crop Yields

Diverting the infiltrating water away from the zone of N application can reduce nitrate–nitrogen (NO₃–N) leaching losses to groundwater from agricultural fields. This study was conducted from 2001 through 2005 to determine the effects of N-application methods using a localized compaction and doming (LCD) applicator and spoke injector on NO₃–N leaching losses to subsurface drainage water and corn (Zea mays L.)–soybean (Glycine max L.) yields. The field experiments were conducted at the Iowa State University’s northeastern research center near Nashua, Iowa, on corn–soybean rotation plots under chisel plow system having subsurface drainage ‘tile’ system installed in 1979. The soils at the site are glacial till derived soils. The N-application rates of 168 kg-N ha^?1 were applied to corn only for both the treatments each replicated three times in a randomized complete block design. For combined 5 years, the LCD N-applicator in comparison with spoke injector showed lower flow weighted NO₃–N concentrations in tile water (16.8 vs. 20.1 mg L^?1) from corn plots, greater tile flow (66 vs. 49 mm), almost equivalent NO₃–N leaching loss with tile water (11.5 vs. 11.3 kg-N ha^?1) and similar corn grain yields (11.17 vs. 11.37 Mg ha^?1), respectively, although treatments effects were found to be non-significant (p?=?0.05) statistically. The analysis, however, revealed that amount and temporal distribution of the growing season precipitation also affected the tile flow, NO₃–N leaching loss to subsurface drain water, and corn–soybean yields. Moreover, the spatial variability effects from plot to plot in some cases, resulted in differences of tile flow and NO₃–N leaching losses in the range of three to four times despite being treated with the same management practices. These results indicate that the LCD N-applicator in comparison with spoke injector resulted in lower flow weighted NO₃–N concentrations in subsurface drain water of corn plots; however, strategies need to be developed to reduce the offsite transport of nitrate leaching losses during early spring period from March through June.