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1.
草莓呼吸旺盛,果皮薄易受伤,难以贮藏。利用近冰点温度贮藏可以明显地抑制草莓的呼吸作用,结合小袋包装的气密性,改善了包装内部的气体组成,提高草莓果实周围的相对湿度并减少空气对流,从而抑制了草莓在贮藏过程中糖分、水分的损耗,减少了糖酸比值的下降。保持了一定的感观指标,可使草莓的贮藏时间延长。  相似文献   
2.
This paper explores the feasibility of particle-based detection and grading of seed vigor based on a self-built seed single-granulation device using near infrared spectroscopy (NIRS). Sweet corn with uniform kernel size was used for this study. The seed samples were divided into three types, they were normal seeds, artificially aged seeds and heat-damaged seeds. A 2-part spectral acquisition of each seed were performed, one for the collection of seeds that fall into the detection zone within the separation pipe, another was on the static platform, whose collection was performed on 5 faces of each seed. Partial least squares discriminant analysis (PLS-DA) was used to classify the original data of the seeds. In the 2 parts, the discriminant results of the unprocessed normal seeds and the artificial accelerated aging seeds, the untreated normal seeds and the heat-damaged seeds showed that classification accuracy was higher than 98%. The research indicates that the spectral data of different positions of seeds can reflect their activity information, and it is feasible to detect and classify seeds in real time in the detection area of the separation pipeline.  相似文献   
3.
近红外光谱是一种快速光谱分析的新方法,伴随着光谱技术与化学计量法的发展,近红外光谱已广泛应用于农业、食品、医药、石油化工等行业,极大地提高了各行业信息化水平。基于近红外光谱在家禽养殖领域的应用现状,本文总结了近红外光谱技术的发展及其在饲料成分检测和禽肉检测中的应用。在饲料检测和家禽肉类检测方面,通过将禽肉样品的光谱信息与质量指标的参考值相关联,建立了预测饲料和待测肉类高精度、高稳定性的数学模型。与传统方法相比,近红外光谱技术具有信息量大、数据计算速度快等优点。本文还归纳了近红外光谱技术在饲料品质检测和肉类品质检测的应用现状,指出了近红外光谱在家禽养殖领域的大规模应用推广的可能性。同时指出近红外光谱技术存在的问题和未来发展方向,结果表明近红外光谱技术在饲料和畜产品检测领域具有良好的发展前景和应用价值。  相似文献   
4.
氨基酸是蛋白质的基本组成单位,是人体必需的重要营养物质。彩色小麦被认为是一类新型的营养保健小麦品种,但对其籽粒中氨基酸含量的研究很少。本研究首次利用高效液相色谱法比较分析了种植于三个环境中的彩色小麦近等基因系(蓝粒小麦科兴611,紫粒小麦科兴617和白粒小麦轮回亲本济麦22)籽粒中多种氨基酸的含量。结果表明,蓝粒小麦科兴611的必需氨基酸含量、非必需氨基酸含量及总氨基酸含量均显著地高于紫粒小麦科兴617和白粒亲本济麦22。紫粒小麦科兴617和白粒小麦济麦22相比,必需氨基酸含量、非必需氨基酸含量及总氨基酸含量相近,甚至低于济麦22。因此,蓝粒小麦籽粒氨基酸含量高的性状,有益于满足人类营养需求,同时可作为育种材料改良小麦品种的氨基酸含量,尤其是提高限制性氨基酸的含量,进而提高小麦的营养品质。  相似文献   
5.
ABSTRACT

We compared the protein and oil contents, seed yields, and natural abundance of 15N (σ15N) of seeds from the plants of the cultivar Enrei, which has moderate nodulating ability (Enrei) with those of its two near-isogenic lines (NILs), a super-nodulating genotype of Enrei, i.e., En-b0-1, and a non-nodulating genotype of Enrei, i.e., En1282. Plants of these three genotypes were grown on four types of field plots with different types of urea coated slow-release nitrogen (N) fertilizers (CUSLNFs) which delivered N in different manners during plant growth . The seed yield of the En1282 plants was similar to that of the Enrei plants but much greater than that of the En-b0-1 plants when the plants were grown on the field to which a CUSLNF with a long lifespan was applied. The amounts of protein per seed were positively correlated with those of oil per seed in the case of En1282 plants irrespective of the field N conditions. The seed protein contents were proportional to the seed weight in both En1282 and Enrei plants. Such a relationship was not observed in the En-b0-1 plants, and the protein and oil contents in the seeds of En-b0-1 plants were negatively correlated with each other. These observations suggested that the N supply to maturing seeds was a key to the protein contents in the En1282 and Enrei plants and that the C supply to maturing seeds was a key to the protein contents in the En-b0-1 plants. The comparison of the σ15N values, protein contents, and seed yields of seeds from En1282 plants suggested that the Enrei plants assimilated considerable amounts of N from the soil during the late plant growth. We concluded that high N2 fixation activity depressed the amounts of oil per seed and changed the protein and oil contents in soybean seeds.  相似文献   
6.
在Visual C++环境中采用面向对象技术,开发了PCA-MBP-NIR定量分析模型软件。通过40份小麦样品的原始光谱、加噪光谱(信噪比为14dB)与含水率所建立的PLS-NIR与PCA-MBP-NIR模型,对10份未知小麦样品的原始光谱、加噪光谱分别进行含水率的PLS-NIR与PCA-MBP-NIR预测分析。分析表明,对于含噪声的光谱,与PLS建模相比,使用PCA-MBP-NIR对未知样品预测结果具有更高的相关系数,更低的预测误差标准差。  相似文献   
7.
基于近红外傅里叶特征提取方法的土壤含水率检测   总被引:2,自引:1,他引:1  
以湖北地区的3种土壤为研究对象,利用偏最小二乘法建立了处理后样品的土壤含水率分析模型,模型预测值与标准值的决定系数为0.995,交叉验证预测均方差为0.801%,模型预测决定系数为0.992,预测均方差为0.912%,利用该模型预测黄土高原地区黄绵土含水率误差均大于4%.利用近红外光谱傅里叶变换特征提取方法对湖北地区黄棕壤、稻田土和潮土建立土壤含水率PLS预测模型,模型决定系数为0.988,交叉验证预测均方差为1.106%,且该模型预测黄绵土的误差均在2%左右,精度较传统模型有较大提高.  相似文献   
8.
A combination of near infrared spectroscopy (NIR) instrumental measurements and sensory analysis was investigated to predict solids soluble content (SSC, assessed as Brix) and to classify preference in table grape cv Italia. SSC was monitored in each berry of whole bunches in order to evaluate intra-bunch distribution and variability. NIR spectra were recorded in the spectral region 12,000–4000 cm−1 (833–2500 nm) using a set of 682 berries. The Partial Least Square (PLS) model based on cross-validation provided acceptable value for the main statistical parameters (coefficient of determination of cross-validation, r2: 0.85; standard error of cross-validation, SECV: 1.08; residual predictive deviation, RPD: 2.6) and was confirmed by external validation performed with 115 independent berries (coefficient of determination of prediction, rp2: 0.82; standard error of prediction, SEP: 0.83). For consumer testing, the selected PLS model was used to predict the Brix value in 400 berries and Discriminant Analysis (DA) was then carried out to classify berries in terms of preference by relating NIR data to consumer judgment. The three defined preference clusters of berries were fully classified obtaining 100% membership. In cross-validation the value decreased especially for class 1 (78.5%) and 3 (75%) whereas class 2 obtained comparable values (98.7%). According to our results, NIR technology appears to be a promising technique for predicting SSC and obtaining information with regard to consumer preference in ‘Italia’ table grape for application of efficient and low cost on-line instruments in the fruit industry.  相似文献   
9.
We examined the relationships between the absorptional characteristics in the near infrared region and the chemical changes of decomposing beech (Fagus crenata) and pine (Pinus densiflora) litters. Spectra as well as the concentrations of chemical substances approached each other and converged with decomposition, although both initial characteristics differed markedly between beech and pine. This indicated that the fundamental chemical structures were almost the same, although their organochemical composition differed. Specific absorption bands for lignin, polysaccharide, and protein were identified at 2,140 and 1,670 nm, 2,270, 1,720, 1,590, and 1,216 nm, and 2,350 nm, respectively. Absorbance at 1,670 nm, peculiar band of aromatics, showed a positive correlation with lignin concentration, which suggested the relative increment of aromatics due to condensed lignin in decomposing litters. Absorbance at 2,140 nm, characterized as the C–H bond in HRC = CHR, showed a negative correlation with lignin concentration, which suggested the decrements of some structures such as side-chains in lignin polymers unrelated to aromatics. Absorbance at 2,270, 1,720, and 1,216 nm, specified to O–H/C–O/C–H bonds in saccharide, might reflect the change of polysaccharide during decomposition because they showed a positive correlation to polysaccharide concentration. In the same way, absorbance at 2,350 nm, identified to the C–H/CH2 bonds in protein, showed a negative correlation to nitrogen concentration in decomposing litters, which might indicate that the C–H/CH2 bonds in protein decreased with decomposition due to microbial consumption of carbon in protein. Our findings suggested the possibility that the spectral changes indicate the litter digestibility during decomposition and that also explain the compositional change in decomposing litters.  相似文献   
10.
Near-infrared (NIR) spectroscopy has been demonstrated as a means for rapid nondestructive determination of the chemical composition and final pulp yield of Eucalyptus camaldulensis in Thailand tree plantations. Multiple linear regression (MLR) analysis and partial least squares (PLS) analysis were introduced to develop statistical models in terms of calibration equations for total pulp yield, screened pulp yield, and contents of -cellulose, pentosans, and lignin in wood. In MLR analysis, a reasonably good calibration equation was found only for pentosans (standard error of prediction (SEP): 0.98%). The PLS analysis improved the accuracy of prediction for every criterion variable, especially for pentosans (SEP: 0.91%) and lignin (SEP: 0.52%). Also, in the case of screened pulp yield, we were able to use such a statistical result as an indicator of the characteristics of the pulp and paper. Thus, NIR spectroscopy could be satisfactorily used as an effective assessment technique for Eucalyptus camaldulensis plantation trees.  相似文献   
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