Starter Fertilizer Effects On Soybean Grain Yield and Quality

Fertilizing soybeans (Glycine max (L.) Merrill) is not an entirely new concept; for a number of years, scientists have investigated the effect of nitrogen (N) fertilizer on yield and quality of soybeans. The objective of this research was to investigate the effect of starter fertilizer N rates and sources on soybean yield, protein, and oil content in the cool soils of the Northern Great Plains. A field experiment was established within a two-year corn (Zea mays L.) soybean rotation. Using a split-plot design with four replications. Whole plots were no-till (NT) and conventional tillage (CT) and the split plots were starter fertilizer (two sources x four rates) treatments. Nitrogen sources were either ammonium nitrate (AN) or urea (UR) each applied at 0,7.8, 15.7, and 23.5 kg N ha-1. Grain yields were higher for 2000 growing season compared to 2001 largely due to differences in rainfall. A yield reduction resulted from the 7.8 kg N ha-1 rate during 2000. Maximum yield occurred at the 23.5 kg N ha-1 AN treatment. Application of UR had no significant effect on grain yield regardless of N rate. The only yield difference for the 2001 season was between the tillage treatments. Similar to 2000 data the 7.8 kg N ha-1 AN treatment had the lowest yield with maximum yield occurring at the 23.5 kg N ha-l AN treatment. but the difference was not significant. We speculate that the former results could be due to a decrease in nodulation in the early growth stages and subsequent decrease in N fixation. Perhaps the 15.7 and 23.5 kg treatments provided enough soil N to overcome a delay in nodulation. Similar to the yield data, the 7.8 kg N ha-l AN rate had the lowest N concentration, with the 15.7 kg N ha-1 AN rate having the highest. Oil content was significantly affected by tillage and N rate with the NT resulting in higher oil content. There was no significant difference for N concentration or oil content for 2001. Although there were few significant differences in the 2001 growing season and the differences in the 2000 were small, it is important to note that applying N as starter has the potential to increase soybean yield and quality when soil temperatures are cool

On-site variety discrimination of tomato plant using visible-near infrared reflectance spectroscopy*

The use of visible-near infrared (NIR) spectroscopy was explored as a tool to discriminate two new tomato plant varieties in China (Zheza205 and Zheza207). In this study, 82 top-canopy leaves of Zheza205 and 86 top-canopy leaves of Zheza207 were measured in visible-NIR reflectance mode. Discriminant models were developed using principal component analysis (PCA), discriminant analysis (DA), and discriminant partial least squares (DPLS) regression methods. After outliers detection, the samples were randomly split into two sets, one used as a calibration set (n=82) and the remaining samples as a validation set (n=82). When predicting the variety of the samples in validation set, the classification correctness of the DPLS model after optimizing spectral pretreatment was up to 93%. The DPLS model with raw spectra after multiplicative scatter correction and Savitzky-Golay filter smoothing pretreatments had the best satisfactory calibration and prediction abilities (correlation coefficient of calibration (R c)=0.920, root mean square errors of calibration=0.196, and root mean square errors of prediction=0.216). The results show that visible-NIR spectroscopy might be a suitable alternative tool to discriminate tomato plant varieties on-site