Growth, grain yield and nitrogen use efficiency of Mediterranean wheat in soils amended with municipal sewage sludge

The application of sewage sludge (SS) to agricultural land can improve soil fertility and physical properties, and enhance crop production. This field study was conducted for two consecutive growing seasons to investigate the influence of SS application on winter wheat growth, grain yield, N accumulation, translocation and use, and on trace elements concentrations in soil and wheat plants under Mediterranean conditions. Treatments consisted of three rates of SS, i.e. 20, 40, and 60 Mg dry weight ha(-1) year(-1), one rate of inorganic fertilizer (IF, 120 kg N ha(-1) year(-1) plus 80 kg P2O5 ha(-1) year(-1)), and an unamended control. The application of SS resulted in tall plants with high early dry matter and N accumulation similar to or significantly higher than those obtained with IF. The lowest SS application rate resulted in grain yield similar to that obtained with IF. Nitrogen use efficiency (NUE) in SS treatments was mainly determined by uptake efficiency, which decreased with increasing SS application rate. Values of NUE and biomass production efficiency with the lowest SS rate were similar to those obtained with IF. SS application resulted in increased concentrations of total and DTPA-extractable trace elements in the soil after the first year, but concentrations were much lower than the regulation limits. Concentrations of Cu, Mn and Zn in wheat plants did not exceed those obtained with IF. Overall, SS could be considered for use as a fertilizer in wheat production systems in the area, serving also as an alternative method of SS disposal

Integrating remote sensing and GIS for prediction of rice protein contents

In this study, protein content (PC) of brown rice before harvest was established by remote sensing (RS) and analyzed to select the key management factors that cause variation of PC using a GIS database. The possibility of finding out the key management factors using GreenNDVI was tested by combining RS and a GIS database. The study site was located at Yagi basin (Japan) and PC for seven districts (85 fields) in 2006 and nine districts (73 fields) in 2007 was investigated by a rice grain taste analyzer. There was spatial variability between districts and temporal variability within the same fields. PC was predicted by the average of GreenNDVI at sampling points (Point GreenNDVI) and in the field (Field GreenNDVI). The accuracy of the Point GreenNDVI model (r 2 > 0.424, RMSE 0.250, RMSE < 0.298%). A general-purpose model (r 2 = 0.392, RMSE = 0.255%) was established using 2 years data. In the GIS database, PC was separated into two parts to compare the difference in PC between the upper (mean + 0.5SD) and lower (mean − 0.5SD) parts. Differences in PC were significant depending on the effective cumulative temperature (ECT) from transplanting to harvest (Factor 4) in 2007 but not in 2006. Because of the difference in ECT depending on vegetation term (from transplanting to sampling), PC was separated into two groups based on the mean value of ECT as the upper (UMECT) and lower (LMECT) groups. In 2007, there were significant differences in PC at LMECT group between upper and lower parts depending on the ECT from transplanting to last top-dressing (Factor 2), the amount of nitrogen fertilizer at top-dressing (Factor 3) and Factor 4. When the farmers would have changed their field management, it would have been possible to decrease protein contents. Using the combination of RS and GIS in 2006, it was possible to select the key management factor by the difference in the Field GreenNDVI