Impact of variable nitrogen fertilisation on arthropods in cotton in Georgia, USA

Reducing fertiliser applications can reduce production costs for cotton (Gossypium hirsutum L.) growers, as well as nitrogen (N) leaching into the soil and contamination of surface and ground water. But altered N fertilisation may also affect pests and their natural enemies. In this study, plots with four different levels of fertiliser input (0, 45, 90 and 135 kg ha⁻¹ N) were used to investigate the influence of N on cotton pest and beneficial arthropod populations, and on cotton yield in Tifton, GA, USA. We predicted that (1) N fertilisation will correlate positively with cotton plant growth; (2) increased N fertilisation will increase pest populations because plants with more N will be more nutritious for and attractive to herbivores; (3) populations of beneficial arthropods and predation of pests will decline with increased N fertilisation because of reduced plant signaling; (4) increased N fertilisation will increase pest mortality due to parasitoids because of increased host quality. Cotton plant growth was enhanced by N fertilisation but yield was unaffected. N fertilisation significantly affected some pest arthropods but inconsistently. Mirids were most abundant in the high N treatment in 1 year of the study and cotton aphids were most abundant in the highest N treatment in the other year of the study. Arthropod predators were generally more abundant in the high N treatment but only spiders and Geocoris spp. were significantly affected by N treatment, with highest numbers present in the highest N treatment but the significant differences were each only in a single year. The greatest mortality of sentinel pest eggs (Spodoptera exigua) due to predation occurred under low N conditions. N fertilisation had no significant effects on parasitism of feral or sentinel caterpillars.     

运用线性拟合法评定水中总磷的测量不确定度

采用Top—Down不确定度评定理念，利用实验室日常质控数据，结合标准样品的线性校准方法（线性拟合法），评定水中总磷的测量不确定度，并将评定结果与GUM评定法相比较，相对偏差≤20％。指出线性拟合法适用于测量系统校准函数成线性，且实验总残差符合常数剩余标准差假定情况下的不确定度评定。