33 resultados para Ergodic Rates


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A field study was established to evaluate oxadiargyl and pendimethalin during the wet seasons in Bangladesh in 2012 and 2013. The study evaluated the following treatments: oxadiargyl applied at 80, 120, and 160 g ai ha−1; pendimethalin at 800, 1200, and 1600 g ai ha−1; partial weedy; and weed-free. Rice plant density was greatly affected by weed control treatment. Lower density and lower uniformity of the rice plant stand occurred as a result of increased rates of herbicides. Increased rates of pendimethalin were more toxic than increased rates of oxadiargyl. Both herbicides effectively controlled Digitaria ciliaris, Echinochloa colona, and Phyllanthus niruri; however, they were unable to control Murdannia nudiflora. Oxadiargyl controlled Cyperus rotundus across rates by 31–55%, but pendimethalin was completely ineffective on it, and higher rates of both herbicides had no effect in controlling this weed. Both herbicides at higher rates reduced total weed biomass significantly. Among herbicide treatments, the highest yield (3.7–4.0 t ha−1) was recorded in plots treated with oxadiargyl at 160 g ai ha−1 and the lowest yield (2.4–2.8 t ha−1) was in plots treated with pendimethalin at 1600 g ai ha−1. Results from our study suggest that a higher rate of oxadiargyl can increase yield by suppressing weeds in dry-seeded rice systems. Similar to the results of oxadiargyl, pendimethalin at higher rates also greatly suppressed weeds; however, yield decreased due to phytotoxicity to rice seedlings.

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This guide provides information on how to match nutrient rate to crop needs by varying application rates and timing between blocks, guided by soil tests, crop class, cane variety, soil type, block history, soil conditioners and yield expectations.

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Fisheries management agencies around the world collect age data for the purpose of assessing the status of natural resources in their jurisdiction. Estimates of mortality rates represent a key information to assess the sustainability of fish stocks exploitation. Contrary to medical research or manufacturing where survival analysis is routinely applied to estimate failure rates, survival analysis has seldom been applied in fisheries stock assessment despite similar purposes between these fields of applied statistics. In this paper, we developed hazard functions to model the dynamic of an exploited fish population. These functions were used to estimate all parameters necessary for stock assessment (including natural and fishing mortality rates as well as gear selectivity) by maximum likelihood using age data from a sample of catch. This novel application of survival analysis to fisheries stock assessment was tested by Monte Carlo simulations to assert that it provided unbiased estimations of relevant quantities. The method was applied to the data from the Queensland (Australia) sea mullet (Mugil cephalus) commercial fishery collected between 2007 and 2014. It provided, for the first time, an estimate of natural mortality affecting this stock: 0.22±0.08 year −1 .