Developing nutrient profile models: a systematic approach

OBJECTIVE: Nutrient profiling can be defined as the 'the science of categorising foods according to their nutritional composition'. The purpose of the present paper is to describe a systematic and logical approach to nutrient profiling. DESIGN: A seven-stage decision-making process is proposed and, as an illustration of how the approach might operate in practice, the development of a nutrient profiling model for the purpose of highlighting breakfast cereals that are 'high in fat, sugar or salt' is described. RESULTS: The nutrient profile model developed for this paper calculates scores for foods using a simple equation. It enables breakfast cereals to be compared with each other and with other foods eaten at breakfast. CONCLUSION: Nutrient profiling is not new, but hitherto most nutrient profiling models have been developed in an unsystematic and illogical fashion. Different nutrient profiling models are needed for different purposes but a key requirement should be that they are developed using a systematic, transparent and logical process. This paper provides an example of such a process; approaches to validating nutrient profiling models are described elsewhere.     

Testing nutrient profile models using data from a survey of nutrition professionals

OBJECTIVE: To compare nutrient profile models with a standard ranking of 120 foods. DESIGN: Over 700 nutrition professionals were asked to categorise 120 foods into one of six positions on the basis of their healthiness. These categorisations were used to produce a standard ranking of the 120 foods. The standard ranking was compared with the results of applying eight different nutrient profile models to the 120 foods: Models SSCg3d and WXYfm developed for the UK Food Standards Agency, the Nutritious Food Index, the Ratio of Recommended to Restricted nutrients, the Naturally Nutrient Rich score, the Australian Heart Foundation's Tick scheme, the American Heart Association's heart-check mark and the Netherlands tripartite classification model for foods. Rank correlation was assessed for continuous models, and dependence was assessed for categorical models. RESULTS: The continuous models each showed good correlation with the standard ranking (Spearman's rho = 0.6-0.8). The categorical models achieved high chi(2) results, indicating a high level of dependence between the nutrition professionals' and the models' categorisations (P < 0.001). Models SSCg3d and WXYfm achieved higher scores than the other models, implying a greater agreement with the standard ranking of foods. CONCLUSIONS: The results suggest that Models SSCg3d and WXYfm rank and categorise foods in accordance with the views of nutrition professionals.     

非均匀土壤剖面的Green-Ampt模型

给出了相应条件下的Green-Ampt模型,入渗量、入渗速率、湿润层深度以及入渗时间的具体表达式,并对1次实测灌水入渗过程进行了模拟,结果表明,Green-Ampt模型计算的入渗时土壤水分剖面与水流连续议程的计算结果存在较大差别,但这种差别经过再分布后逐渐消失。在作较长时段的土壤水分动态模拟时利用Green-Ampt模型模拟入渗过程是适用的,特别是在已知入渗总量而未知入渗强度过程的情况下具有优越性。     

基于多光谱图像技术的番茄营养素诊断模型

为了快速、准确估测番茄营养水平和生长状态,利用多光谱图像分析技术研究了温室番茄营养素含量和图像特征的相关性。在日光条件下采集了温室番茄叶片多光谱图像,并采用多尺度Retinex算法有效地解决了叶片平整度差异造成的图像质量退化问题。从颜色模型、比值植被指数和归一化差值植被指数出发,自定义了49个多光谱图像特征参数。结合相关性分析和系统聚类分析消除了多光谱图像特征参数的多重共线性,并提取了4个能反映叶绿素含量(SPAD指数)和全氮含量预测模型,其中SPAD指数模型的决定系数(R2)为0.8668,均方根误差(RMSE)为3.997;全氮模型的R2为0.7284,RMSE为0.5130。     

水稻适宜养分指标动态的知识模型研究

在分析研究水稻栽培理论与技术资料的基础上,通过定量描述水稻群体地上部植株氮、磷、钾养分积累量和养分浓度动态与品种类型、生态环境因子和生产技术水平之间的动态关系,以生理发育时间为主线,建立了系统化和广适性的水稻适宜群体地上部植株养分指标的动态知识模型。本模型可为不同条件和产量目标下水稻栽培过程中的苗情诊断与生长调控提供定量化的养分指标动态体系。利用南京和常德2个不同生态点的常年逐日气象资料和品种资料对所建知识模型进行了实例分析,养分积累动态和养分浓度动态的RMSE分别为8.97.kg/hm2和0.32%,表明本知识模型对不同条件下的水稻植株养分指标适宜动态具有较好的预测性和指导性。     

Characterization of model melanoidins by the thermal degradation profile

Different types of model melanoidins were thermally degraded, with subsequent identification of the volatiles produced, to obtain and compare the thermal degradation profile of various melanoidins. At first, the volatiles produced from heated glucose/glycine standard melanoidins were compared with glucose/glutamic acid and L-(+)-ascorbic acid/glycine standard melanoidins. In the headspace of heated glucose/glycine melanoidins, mainly furans, were detected, accompanied by carbonyl compounds, pyrroles, pyrazines, pyridines, and some oxazoles. Heating of L-(+)-ascorbic acid/glycine melanoidins resulted in relatively more N-heterocycles, while from glucose/glutamic acid melanoidins no N-heterocycles were formed. In a second part, a chemical treatment was applied to glucose/glycine melanoidins prior to the thermal degradation. Acid hydrolysis was performed to cleave glycosidically linked sugar moieties from the melanoidin skeleton. Nonsoluble glucose/glycine melanoidins were also subjected to an oxidation. The results indicate that the thermal degradation profile is a useful tool in the characterization of different types of melanoidins.     

水稻土有效养分与其校正系数的数学模型

土壤有效养分校正系数是测土配方施肥中的主要参数。根据"3414"试验数据,利用Excel数据分析方法,建立土壤有效养分与校正系数之间的回归方程式。结果表明,水稻试验区土壤碱解氮、速效磷和速效钾与校正系数都有极显著回归关系,最佳数学模型为幂函数,曲线分别为yN=11.831x-0.722 8;yP=22.726x-0.956 3;yK=58.436x-1.000 5。曲线又可用二条直线描述,计算土壤有效养分校正系数。     

Extended probability model for dry matter and nutrient accumulation by crops

Accumulation of dry matter and plant nutrients by crops over the growing season is important to resource management for agricultural production and for meeting environmental standards. It is becoming more common in agricultural and environmental management to use mathematical models to describe such systems. In this article, an extended probability model was used to characterize accumulation of dry matter and plant nutrient uptake, both of which exhibited sigmoid behavior with time. Data from field studies included corn (Zea mays L.), tobacco (Nicotiana tabacum), and soybean (Glycine max). For the case of corn, it was shown that maximum total plant dry matter at maturity agreed very closely for the three sites. The ratio of the paramters mean time to standard deviation of the distribution was very similar for dry matter and plant nutrient accumulations, with an average of 3.6 for Wooster, OH and 3.5 for Clayton, NC. The ratio was 4.3 for water reuse at Tallahassee, FL. For tobacco, the ratio was also very similar for dry matter and plant nitrogen (N) and potassium (K), and was 3.2 at Raleigh, NC. The ratio was 2.9 for leaf area of soybeans grown at Gainesville, FL. Data for dry matter and plant nutrient accumulation followed the sigmoid shape of the model rather well. The model also produced the “hump”; often observed in plant nutrient concentration during early stages of growth. The probability model suggests that for the crops studied, growth rate followed a gaussian distribution over the season, at least to first approximation.     

Spatial prediction of soil nutrient in a hilly area using artificial neural network model combined with kriging

It is widely recognized that using correlated environmental factors as auxiliary variables can improve the prediction accuracy of soil properties. In this study, a radial basis function neural network (RBFNN) model combined with ordinary kriging (OK) was proposed to predict spatial distribution of four soil nutrients based on the same framework used by regression kriging (RK). In RBFNN_OK, RBFNN model was used to explain the spatial variability caused by the selected auxiliary factors, while OK was used to express the spatial autocorrelation in RBFNN prediction residuals. The results showed that both RBFNN_OK and RK presented prediction maps with more details. However, RK does not always obtain mean errors (MEs) which were closer to 0 and lower root mean square errors (RMSEs) and mean relative errors (MREs) than OK. Conversely, MREs of RBFNN_OK were much closer to 0 and its RMSEs and MREs were relatively lower than OK and RK. The results suggest that RBFNN_OK is a more unbiased method with more stable prediction performance as well as improvement of prediction accuracy, which also indicates that artificial neural network model is more appropriate than regression model to capture relationships between soil variables and environmental factors. Therefore, RBFNN_OK may provide a useful framework for predicting soil properties.     

养分专家系统在双季常规稻模式下的减氮效应

近年来,双季稻区的常规稻种植规模在不断扩大。同时,氮肥施用过多也是生产中的突出问题,因此,在双季常规稻种植模式下养分专家系统推荐施肥的减氮效应研究具有重要意义。试验于2019和2020年在江西省进贤县温圳镇进行,早晚稻均为常规稻品种,分别为江早361和湘晚籼12号,开展双季种植,在养分专家推荐施肥(NE)的基础上,设置不施氮肥处理(NE-100%N)、氮肥减量25%和50%(NE-25%N 和NE-50%N)、氮肥增量25%和50%(NE+25%N和NE+50%N)共6个处理,测定水稻产量、植株氮素养分吸收量、氮肥利用率等指标。结果显示,两年早、晚稻产量及氮肥产量反应均为养分专家系统推荐施氮量的NE处理最高,较NE-100%N和NE-50%N处理显著增产11.6%～59.3%,随施氮量的增加,至NE处理时产量达到最高,继续增加则水稻产量有降低趋势。进一步进行拟合方程表明,产量和施氮量之间呈极显著一元二次抛物线关系,两年NE处理早、晚稻施氮量较最大施氮量分别降低13.7%～18.2%和6.7%～12.5%,而产量均较最大施氮量对应产量略高。氮素养分吸收量随施氮量的增加,在NE处理时达到最高,早、晚稻两年平均氮素吸收量较其他处理分别显著提高9.5%～105.7%和7.0%～88.0%。而NE处理的早、晚稻平均氮肥吸收利用率较其余处理两年增幅分别为14.7%～147.0%和8.9%～155.0%,平均农学效率较NE-50%N、NE-25%N处理均无显著差异,较其余处理两年增幅为27.9%～108.2%。综上,养分专家系统推荐氮肥用量可使双季常规稻增产,提高水稻植株的氮素养分吸收量以及氮肥利用率,同时达到减氮增效的目标,有利于科学指导双季常规稻的氮肥施用。     

Quantitative evaluation of the microbial nutrient sink in soil in relation to a model system for soil fungistasis

A quantitative approach was devised to evaluate the influence of soil microbial activity as a sink for nutrients exuded by fungal spores as a factor in soil fungistasis. The approach was based on measuring the CO₂ evolved from microbial respiration of ¹⁴C-labelled exudates from conidia of Cochliobolus victoriae incubated on soil. The amount of exudate lost by spores on soil was greater than the amount lost by spores incubated on a bed of sand undergoing leaching at a flow rate of 110 ml h^?1. where restriction of germination was similar to that on soil. Increasing flow rates in the leaching system increased spore exudation and reduced germination. Germination of C. victoriae conidia on membrane filters floated on distilled water decreased as the volume of water increased. The results indicate that the microbial nutrient sink of soil is sufficient to impose soil fungistasis.     

Pollution profile of a river

A host of chemical industries subject the river to pollutants such as acids, alkalies and their salts, trace metals and radionuclides belonging to the Th and U chains. Proximity of different outfalls and poor lateral mixing in the river are responsible for high local aquatic concentrations. Scavenging reactions, in situ, and sedimentation of suspended matter result in the accumulation of radionuclides near the outfall area. Monsoon ‘flushes out’ the river into the backwater area and translocation of sediments is the major factor in the transport of pollutants.     

森林养分循环模型应用

The nutrient cycling model NuCM is one of the most detailed models for simulating processes that influence nutrient cycling in forest ecosystems. A field study was conducted at Tieshanping, a Masson pine （Pinus massoniana Lamb.） forest site, in Chongqing, China, to monitor the impacts of acidic precipitation on nutrient cycling. NuCM simulations were compared with observed data from the study site. The model produced an approximate fit with the observed data. It simulated the mean annual soil solution concentrations in the two simulation years, whereas it sometimes failed to reproduce seasonal variation. Even though some of the parameters required by model running were measured in the field, some others were still highly uncertain and the uncertainties were analyzed. Some of the uncertain parameters necessary for model running should be measured and calibrated to produce a better fit between modeled results and field data.     

Soil test reporting a nutrient index system

Abstract

An index system of reporting soil test results is suggested which is not confounded with the requirements of a particular crop but is based on each laboratory's evaluation of the test results in relation to the predicted relative sufficiency of each element in a fertile soil. It is suggested that soil test—fertilizer rate correlation adjustments begin after the fact rather than in a precursory manner to influence the results reported. A 0–100 index is proposed as a self explanatory measure and correlated with general crop response as follows: 0–15, nutrient deficiencies visible; 16–50, nutrient deficiencies obscured but plant response probable; 51–100, adequate nutrients available for most crops; 100+, amounts available in excess of present needs.     

基于GIS的猕猴桃土壤养分评价与施肥建议模型研究

该论文以陕西省周至县为例,基于GIS技术,得到土壤养分的地域分布模型和适宜性等级划分;针对猕猴桃的生育特性,建立了养分需求模型;针对土壤养分的空间分布特点,给出具有决策指导意义的施肥建议,以提高猕猴桃果品的品质和产量;研制了基于施肥建议模型的果树施肥信息系统。该方法实现了GIS支持下的基础土壤养分数据的空间化、可视化、系统化管理,最大程度上实现了连续性的养分分布模型的构建,并对不同地域的施肥建议进行了可视化输出。该方法是实现“数字农业”和“精准施肥”目标的有益探索,具有一定的理论和实践意义。     

利用ECMWF再分析数据验证PRECIS对中国区域气候的模拟能力

本文利用1979～1983年的ECMWF再分析数据作为准观测侧边界条件驱动Hadley气候预测和研究中心的区域气候模式系统PRECIS，验证PRECIS对中国区域的气候模拟能力。选择典型的观测站点北京模拟的日最高，最低气温、太阳短波总辐射和月均降水量与观测结果进行直接比较，显示：PRECIS具有很强的模拟地面气候季节变化的能力。全国740个台站的观测与模拟值的统计分析表明：尽管模拟的最高，最低气温在0℃附近有一‘锯齿’状的偏差，PRECIS能够很好地模拟全国范围最高，最低气温的型态分布特征；从全国范围看，模拟的降水值偏高，但显示出很强的模拟极端降水事件的能力；模拟的地面太阳短波总辐射与全国122个台站的观测结果的比较显示：PRECIS模拟的辐射值偏高，全国范围内约高22％。因此，当应用PRECIS输出结果进行气候变化的影响评价时，需要对模式的输出结果进行订正。     

湖南省主要农作物土壤有效养分校正系数估算数学模型研究

分析了湖南省早稻、中稻、晚稻、玉米、油菜、棉花、烤烟、红薯等8个主要农作物的2 459个"3414"肥效试验结果,获得了大量的土壤速效氮、磷、钾有效养分校正系数,其中土壤有效磷校正系数平均值最高,为161.55%,其次是速效钾的68.30%,最低的是碱解氮的38.25%,说明作物对土壤有效磷的利用率最高,对土壤碱解氮的利用率最低;土壤有效养分校正系数与对应土壤速效养分含量均呈极显著的负相关,其中与速效钾含量的相关性最密切,其次是有效磷和碱解氮;以土壤速效养分含量为自变量x,以对应的校正系数为因变量y,回归分析建立的最佳数学模型均为双曲线,其回归关系和拟合度均到达极显著水平;数据来源于全省大样本的试验结果,具有较强的代表性,可以用于校正斯坦福施肥量估算公式中的有效养分校正系数值,为精确估算主要农作物施肥量和制定施肥配方提供科学依据。