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首页> 外文期刊>Applied Spectroscopy: Society for Applied Spectroscopy >Prediction of Potential Mushroom Yield by Visible and Near-Infrared Spectroscopy Using Fresh Phase II Compost
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Prediction of Potential Mushroom Yield by Visible and Near-Infrared Spectroscopy Using Fresh Phase II Compost

机译:使用新鲜的II期堆肥通过可见和近红外光谱预测潜在的蘑菇产量

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摘要

Potential mushroom (Agaricus bisporus) yield of phase II compost is determined by interactions of key quality parameters including dry matter, nitrogen dry matter, ammonia, pH, conductivity, thermophilic microorganisms, C:N ratio, fiber fractions, ash, and certain minerals. This study was aimed at generating robust visible and near-infrared (Vis-NIR) calibrations for predicting potential yield, using spectra from fresh phase II compost. Four compost comparative trials were carried out during the winter and summer months of 2001-2003, under controlled experimental conditions employing six commercially prepared composts, with eight replicate (8 bag) plots per treatment (48 X 8 velence 384). The substrates were prepared by windrow or bunker phase I, followed by phase II production. The fresh samples were scanned for Vis-NIR (400-2498 nm) spectra, averaged, transformed, and regressed against the recorded yield by employing a modified partial least squares algorithm. The best calibration model generated from the database explained 84percent of yield variation within the data set with a standard error of calibration of 13.75 kg/tonne of fresh compost. The model was successfully tested for robustness with yield results obtained from a validation trial, carried out under similar experimental conditions in early 2004, and the standard error of prediction was 18.21 kg/tonne, which was slightly higher than the mean experimental error (17.94 kg/tonne) of the trial. The accuracy of the model is acceptable for estimating potential yield by classifying phase II substrate as poor (180-220 kg), medium (220-260 kg), and high (260-300 kg) yielding compost. The yield prediction model is being transferred to a new instrument based at Loughgall for routine evaluation of commercial phase II samples.
机译:II期堆肥的潜在蘑菇(双孢蘑菇)产量由关键质量参数(包括干物质,氮干物质,氨,pH,电导率,嗜热微生物,C:N比,纤维级分,灰分和某些矿物质)的相互作用确定。这项研究旨在使用新鲜的II期堆肥产生的光谱生成可靠的可见光和近红外(Vis-NIR)标定,以预测潜在产量。在2001-2003年冬季和夏季,在受控的实验条件下,采用六种商业制备的堆肥,进行了四次堆肥比较试验,每种处理有八个重复(8袋)地块(48 X 8 velence 384)。通过第一阶段的料堆或料仓制备基材,然后进行第二阶段的生产。扫描新鲜样品的Vis-NIR(400-2498 nm)光谱,取均值,进行转化,然后采用修正的偏最小二乘法对记录的收率进行回归分析。由数据库生成的最佳校准模型解释了数据集中84%的产量变化,其标准校准误差为13.75千克/吨新鲜堆肥。该模型已成功进行了稳健性测试,并从2004年初在相似的实验条件下进行的验证试验获得了产量结果,预测的标准误差为18.21千克/吨,略高于平均实验误差(17.94千克)。 / tonne)。该模型的准确性可用于通过将II期底物分类为低产(180-220 kg),中产(220-260 kg)和高产(260-300 kg)堆肥来估计潜在产量。产量预测模型将被转移到Loughgall的新仪器上,用于常规评估商业II期样品。

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