Hydrolysis characteristics of tissue fractions resulting from mechanical separation of corn stover

Corn stover has potential as a resource for both fiber and chemical needs if separation strategies can be developed to deal with its heterogeneity. Relative hydrolysis characteristics were assessed for pith (sclerenchyma and parenchyma) and fiber (collenchyma) tissue fractions derived from mechanical separation of corn stover to determine whether classification by tissue type resulted in fractions with different hydrolysis response. The physical characteristics of the tissue fractions were analyzed. The hydrolysis behavior of the fractions was evaluated under both acidic and basic conditions. The results from the hydrolysis experiments are compared with previously reported compositional analysis for the tissue fractions.     

Multi-dimensional chromatography using on-line coupled microcolumn liquid chromatography—capillary gas chromatography for quantitative pesticide residue analysis

Highly selective separations can be achieved by utilizing different separation modes in a multi-dimensional (on-line coupled) chromatographic system. The application of such a system utilizing microcolumn liquid chromatography coupled on-line to capillary gas chromatography for the determination of 2-(1,1-dimethylethyl)-5-pyrimidinol, a pesticide metabolite, in various corn matrices at the ng g^?1 level is described. A comparative quantitative study with conventional manual sample pretreatments followed by capillary gas chromatography-mass spectrometry indicated equivalence between the two techniques. The system offers the advantages of reduced sample handling steps and analysis time, high potential for automation and adequate sensitivity.     

Methodology for estimating removable quantities of agricultural residues for bioenergy and bioproduct use

A methodology was developed to estimate quantities of crop residues that can be removed while maintaining rain or wind erosion at less than or equal to the tolerable soil-loss level. Six corn and wheat rotations in the 10 largest corn-producing states were analyzed. Residue removal rates for each rotation were evaluated for conventional, mulch/reduced, and no-till field operations. The analyses indicated that potential removable maximum quantities range from nearly 5.5 million dry metric t/yr for a continuous corn rotation using conventional till in Kansas to more than 97 million dry metric t/yr for a corn-wheat rotation using no-till in Illinois.     

LC and SPE Determination of Chlorophacinone in Corn Grains, Soil and Rat Plasma

A liquid chromatographic method was used for the analysis of chlorophacinone in corn, soil and rat plasma. Sample preparation differed from corn, soil and serum. Simple liquid extraction procedures were applied to soil and corn; solid phase extraction using Oasis HLB cartridges and easy protocol was used for plasma. Liquid chromatography was on X-terra C18 column. The mobile phase used did not contain ion-pairing reagent, it was constituted with methanol/ammonium bicarbonate (0.01 M, pH = 7), 70/30, v/v at 1 mL min⁻¹. UV detection was by using photodiode detector operating at 282 nm. Complete validation of the proposed procedure for corn, soil and serum was made.     

Increasing the Value of Hominy Feed as a Coproduct by Fermentation

Hominy feed is a low value ($83.7/metric ton) coproduct of the corn dry milling process that accounts for nearly 35% of the starting corn quantity. The average composition of hominy feed on a dry basis is 56.9% starch, 25.2% neutral detergent fiber, 11.1% protein, and 5.3% fat. Starch in hominy feed can be fermented to ethanol thus increasing its levels of protein and fat. The increase in protein and fat percentages may increase the market competitiveness and price of hominy feed. Hydrolysis and fermentation were performed on nine hominy feed samples collected from three corn dry milling plants in the USA. The original hominy feed samples and postfermentation solids were analyzed for starch, protein, fat, and fiber content. Compared to the original hominy feed, the percentage increase in protein, fat and fiber in postfermentation solids of nine samples ranged from 10.4 to 21.3, 6.78 to 10.6, and 12.6 to 28.7% (dry basis), respectively. Ethanol yields varied from 271.7 to 380.2 l/metric ton for the nine hominy feed samples. These results indicate that the value of hominy feed as an animal feedstock can potentially be increased with fermentation and can produce more profit per metric ton than currently being derived by its sale as a low protein feed ingredient.     

高光谱成像技术检测玉米种子成熟度

成熟度是影响种子活力的重要因素之一,是种子质量的重要指标。种子分级时将成熟种子和未成熟种子区分开来可提高种子批活力,使种子批活力具有一致性。采用400~1 000 nm波段范围的高光谱成像技术研究成熟和未成熟玉米种子,找出二者区分度最高的特征波段图像,通过图像处理方法进行种子分类。选用主成分分析(PCA)法分析高光谱图像,分析差异最明显的PC2主成分图像的各波段权重系数并提取出特征波段(501 nm)。从70粒成熟度较低玉米种子样本高光谱图像上选取成熟和未成熟两类感兴趣区域,采用偏最小二乘回归(PLSR)法分析两类感兴趣区域的平均光谱,选取与成熟度相关的敏感波段(518 nm)。采用波段比运算并结合KW检验,分析两类感兴趣区域的平均光谱,找出差异最大的最优波段比(640 nm/525 nm)。以864粒玉米种子为研究对象,提取特征波段对应的单波段图像和最优波段比对应的波段比图像,采用图像处理技术分析图像并判别。结果表明：采用单波段灰度图像分割容易将玉米种子冠部的浅色部分误识别为种子成熟度较低的区域,识别准确率低;而采用640 nm/525 nm的波段比图像可以减轻这种不利影响,平均正确识别率为93.9%。该方法可以有效识别未成熟的玉米种子,为进一步开发在线分级装备提供了依据。     

一种玉米苗期冠层叶片营养诊断动态光谱指数

为了有效的解决玉米苗期冠层叶片营养状态车载动态诊断过程中,土壤干扰信息无法剔除的问题,本文提出了一种动态测量用光谱指数MPRI,根据MPRI的构成和特点、论述了利用MPRI辨识土壤与冠层光谱信息的机理,构建了基于MPRI的玉米苗期冠层叶片叶绿素含量的预测模型,通过车载式作物长势检测系统平台,运用模型对玉米苗期冠层叶片营养状态进行动态诊断与评估,取得良好的效果。研究表明：在车载动态条件下测量玉米苗期冠层叶片营养状态时,土壤的MPRI呈正值而玉米冠层的MPRI呈负值,因此使用光谱指数MPRI能够有效识别土壤背景与冠层叶片光谱信息。设定固定的阈值,能够较为准确和便捷的去除土壤背景光谱信息。基于MPRI构建的冠层叶片叶绿素含量的动态测量预测模型,能够准确的表征冠层叶片的叶绿素含量,模型决定系数R2达0.72,动态测量中对植株冠层的识别率达80%。与其他常用的指数相比,在车载动态测量环境下,光谱指数MPRI具有土壤背景信息识别速度快、正确率高,模型预测精度良好等特点,为玉米苗期冠层营养状态的诊断提供了新的途径。     

巯基棉分离富集-FAAS法测定爆玉米花中痕量铅

本文借助巯基棉分离富集技术,以火焰原子吸收光谱法（ＦＡＡＳ）测定爆玉米花中痕量铅。该方法采用巯基棉做分离富集剂,简便易行,并能有效的消除共存元素的干扰,回收率为９７．５％－１０６．０％。     

维药玉米须的微量元素分析

用原子吸收分光光度法测定维药玉米须中的K,Na, Ca, Fe, Cu, Co, Ni, Zn, Mn, Mg, Cr等11种微量元素。结果表明：玉米须含有丰富的人体必需的微量元素,其中K,Co, Zn, Cu, Fe的含量更显著。探讨了微量元素与玉米须的药效关系,通过本实验为玉米须的进一步研究和综合开发利用提供了新的科学依据。     

基于近红外光谱技术和人工神经网络的玉米品种鉴别方法研究

提出了一种采用近红外光谱技术结合人工神经网络对玉米品种进行鉴别的方法。在3 800～10 000 cm-1(波长1 000～2 632 nm)范围内采集四种玉米单粒完整籽粒的近红外漫反射光谱,经Savitky-Golay平滑和多重散 射校正预处理后,对数据进行主成分分析,再结合人工神经网络技术进行品种鉴别。主成分分析表明,前8个主成分的累积贡献率达到99.602%。以前8个主成分作为网络输入,品种类型作为输出,建立三层LMBP神经网络模型。每个品种 各取30粒共120个样本用于建模,10粒共40个样本用于预测。模型对建模集120个样本鉴别率为100%,对预测集40个样本的鉴别率为95%。实验结果说明该方法能快速无损地鉴别玉米品种,为玉米的品种鉴别提供了一种新方法。