Another Look at Bayesian Analysis of AMMI Models for Genotype-Environment Data

Linear–bilinear models are frequently used to analyze two-way data such as genotype-by-environment data. A well-known example of this class of models is the additive main effects and multiplicative interaction effects model (AMMI). We propose a new Bayesian treatment of such models offering a proper way to deal with the major problem of overparameterization. The rationale is to ignore the issue at the prior level and apply an appropriate processing at the posterior level to be able to arrive at easily interpretable inferences. Compared to previous attempts, this new strategy has the great advantage of being directly implementable in standard software packages devoted to Bayesian statistics such as WinBUGS/OpenBUGS/JAGS. The method is assessed using simulated datasets and a real dataset from plant breeding. We discuss the benefits of a Bayesian perspective to the analysis of genotype-by-environment interactions, focusing on practical questions related to general and local adaptation and stability of genotypes. We also suggest a new solution to the estimation of the risk of a genotype not exceeding a given threshold.     

生态平衡施肥模型与目标产量施肥模型比较研究

对目标产量施肥模型特点、弊端和预测施肥量精度等进行了综合研究,并与生态平衡施肥模型进行了比较。结果表明:尽管目标产量施肥模型构建合理,参数获得容易,但参数多,参数易变,参数准确测定困难,参数间存在相互影响关系,模型中没有考虑土壤有效养分平衡或变化,因此,它难以作为精确施肥模型使用;与其相比,生态平衡施肥模型将施肥系统中诸多变量统一在质量守恒定律之下,具有测土施肥模型和肥料效应函数模型的双重功能,参数变异小,参数易于获得和预测施肥量准确等诸多优点。     

Zum Einfluss langjährig differenzierter Kaliumdüngung auf Parameter des Bodenwasserhaushaltes

Using soil samples from 15 field trials of long term-differences in potassium fertilization from sites in Germany, the Czech Republic and Hungary, we conducted a laboratory analysis to measure the effects of potassium fetilization on soil potassium content, water-retention functions and crop growth parameters such as field capacity, permanent wilting point and available water content. The different soil water parameters showed a specific response to potassium fertilization and strong interactions with a number of soil characteristics. Higher water content, caused by an increase in potassium, was measured in low water retention below pF 3.0 and only in a few cases with pF 4.2. The strongest response to long-term differences in potassium fertilization on field capacity and available water content were detected for sandy soils. This effect decreased with increased clay content. In sandy soils, the response to potassium fertilization was mediated by an increase in soil organic carbon (TOC). In soils with a high silt content from Bad Lauchstädt and Bonn only minute effects of TOC on the water-holding capacity were measured. The effect of potassium on the various water-retention parameters in soils was strongly affected by TOC of the particular soil. Thus, the potassium-mediated increase in the field capacity of soils with a low TOC from the experimental site in Bonn (1.05 M% TOC) with almost 1.2 Vol% was almost twice as high as for the site in Bad Lauchstädt, which is characterized by a TOC of 1.97 M%. We hypothesize that these interactions are responsible for the substantial increase in available water content following increased potassium in clay soil with a low TOC in Putnok (Hungary).     

Bodengefüge,Wurzelentwicklung und Wurzelfunktionen

Soil fabric, root development and root functions Plant roots fulfil numerous functions. These include the uptake of water and nutrients as well as a significant role in the energy, nutrient and hormone metabolism of the plant. To accomplish these functions the plant develops a huge root network during just a few weeks and extends it with a remarkable rate against considerable resistance through the soil pore system. This induces numerous mechanical as well as biochemical interactions between soil and roots, which are of great agronomic and ecological significance. Through a combination of knowledge from various research fields this paper intends to improve the understanding of plant root-soil interactions and to identify knowledge gaps.     

根系水质模型中土壤与作物参数优化及其不确定性评价

农业系统模型参数优化存在很高的不确定性,是模型应用研究的重点和难点。该研究利用自动优化程序PEST(parameter estimation software)对根系水质模型(root zone water quality model,RZWQM)中土壤参数(土壤水力学参数和根系生长参数)和作物遗传参数进行了优化,结果表明PEST优化模拟结果明显优于传统试错法的校正结果,且具有较高的参数优化效率。模型参数优化不确定性评价表明校正数据和参数初始值的选择、土壤水力学参数估算方法、不同类型参数间的相互作用以及优化目标方程(误差来源计算)都明显影响模型模拟结果。以上过程中土壤水力学参数优化值差异较小,但其土壤水分特征曲线却明显不同。通过以上评价分析提高了RZWQM相关参数优化结果的可靠性及其模拟功能,降低了模型参数优化的不确定性,为PEST优化其他模型参数提供了重要支持。     

The role of soil science in the land use negotiation process*

Abstract. The hierarchial concept of land use planning becomes less relevant in a society with continuous interactions between stakeholders, researchers, planners and politicians. In this context, land use negotiation rather than land use planning appears to be the most appropriate concept. In the negotiation process, good quality data about the land is important as land properties are, obviously, key elements to be considered. Case studies at farm and regional level have been analysed to explore answers to a number of questions. How can soil data be presented most effectively? What are the research needs? How can the large existing body of data be mobilized most effectively? Studies on regional land use in Costa Rica used methods in a logical sequence including projections, explorations and predictions of land use patterns. The work involved upscaling of data, obtained at farm level, to the regional level. Work at farm level focussed on prototyping procedures in which farming systems were ‘designed’ by close interaction between farmers and scientists, including applications of precision agriculture. Soil data demands were analysed, emphasizing the effects of using data with different degrees of detail together with the application of pedotransfer functions which effectively transform existing data into parameters that are difficult or expensive to measure directly. This not only facilitated interactions with stakeholders but also with colleague scientists in interdisciplinary teams. In addition, use of Geographical Information Systems allowed visual presentations of alternative geographical land use patterns that were associated with various scenarios, thereby facilitating the interaction processes. A plea is made to increase interaction of stakeholders and researchers by considering research programmes as vehicles for joint learning.     

Combining X-ray computed tomography with relevant techniques for analyzing soil–root dynamics – an overview

The study of below-ground features of roots and soil and their interactions is essential for understanding the configuration and diversities in such a dynamic environment. X-ray computed tomography is recognized as a tool for visualizing the physical interactions in the soil. In many studies, it has been used as a stand-alone tool to describe soil and root parameters. However, in recent times, attempts to couple it with other complementary tools are gaining rapid interest among researchers. The paper therefore provides an overview of the major application of combining X-ray computed tomography with other relevant methods in analyzing the structural characteristics of roots and soil media. The relevance of using this multidisciplinary approach for unraveling the mysteries surrounding root–soil dynamic interactions is stressed. The current and future trends of such studies are also pointed out.     

Microbial communities and their relevance for ecosystem models: Decomposition as a case study

Soil microbial communities are so vastly diverse that complex interactions, which alter ecosystem functions, may occur among microbial species and functional groups. In this review, we explore the empirical evidence for situations when shifts in the community structure of microbes would elicit a change in ecosystem process rates, specifically decomposition, even when microbial biomass remains constant. In particular, we are interested in a subset of these scenarios in which knowledge of microbial community structure would improve model predictions for ecosystem functions. Results from microcosm and field studies indicate that microbial species diversity, functional group diversity, and community composition can all influence ecosystem process rates. The underlying mechanisms that may elicit changes in ecosystem functions from shifts in microbial community structure include evolutionary constraints on microbial trait adaptation, trait correlations, dispersal limitation, and species interactions. The extent of microbial diversity in soils is not known, so it is presently not possible to model all scenarios of microbial community structure shifts. However, by incorporating documented patterns in functional groups that are relevant for a particular ecosystem process and potential relationships between microbial phylogeny and function, the predictive power of process models will be significantly improved. The inclusion of this information into process models is critical for predicting and understanding how ecosystem functions may shift in response to global change.     

BODIUM—A systemic approach to model the dynamics of soil functions

The increasing demand for biomass for food, animal feed, fibre and bioenergy requires optimization of soil productivity, while at the same time, protecting other soil functions such as nutrient cycling and buffering, carbon storage, habitat for biological activity and water filter and storage. Therefore, one of the main challenges for sustainable agriculture is to produce high yields while maintaining all the other soil functions. Mechanistic simulation models are an essential tool to fully understand and predict the complex interactions between physical, biological and chemical processes of soils that generate those functions. We developed a soil model to simulate the impact of various agricultural management options and climate change on soil functions by integrating the relevant processes mechanistically and in a systemic way. As a special feature, we include the dynamics of soil structure induced by tillage and biological activity, which is especially relevant in arable soils. The model operates on a 1D soil profile consisting of a number of discrete layers with dynamic thickness. We demonstrate the model performance by simulating crop growth, root growth, nutrient and water uptake, nitrogen cycling, soil organic matter turnover, microbial activity, water distribution and soil structure dynamics in a long-term field experiment including different crops and different types and levels of fertilization. The model is able to capture essential features that are measured regularly including crop yield, soil organic carbon, and soil nitrogen. In this way, the plausibility of the implemented processes and their interactions is confirmed. Furthermore, we present the results of explorative simulations comparing scenarios with and without tillage events to analyse the effect of soil structure on soil functions. Since the model is process-based, we are confident that the model can also be used to predict quantities that have not been measured or to estimate the effect of management measures and climate states not yet been observed. The model thus has the potential to predict the site-specific impact of management decisions on soil functions, which is of great importance for the development of a sustainable agriculture that is currently also on the agenda of the ‘Green Deal’ at the European level.     

Peak functions for modeling high resolution soil profile data

Parametric and non-parametric depth functions have been used to estimate continuous soil profile properties. However, some soil properties, such as those seen in weathered loess, have anisotropic peak-shaped depth distributions. These distributions are poorly handled by common parametric functions. And while nonparametric functions can handle this data they lack meaningful parameters to describe physical phenomena in the depth distribution of a property such as a peak, an inflection point, or a gradient. The objective of this work is to introduce the use of asymmetric peak functions to model complex and anisotropic soil property depth profiles. These functions have the advantages of providing parameters, which quantify or describe pedogenic processes. We demonstrate the application of the Pearson Type IV (PIV) and the logistic power peak (LPP) functions to high resolution soil property depth profiles measured by diffuse reflectance spectroscopy in a claypan soil landscape of Northeastern Missouri, USA. Both peak functions successfully fit clay, silt, and pH data for an example soil profile from a summit landscape position (R² = 0.90 for pH and 0.98 for silt and clay). The LPP function was further demonstrated to fit clay depth distribution for a shoulder, backslope, footslope, and a depositional landscape position (R² = 0.98, 0.96, 0.96, 0.91). Relationships between the fitted parameters of these profiles were useful to describe landscape trends in their morphological features and show promise to continuously describe pedogenic processes in three dimensions. Peak functions are a useful companion to high-resolution soil profile data collected by sensors and their combined use may allow more intensive mapping and better explanation of soil landscape variability.     

One-dimensional image analysis of soil structure. I. Principles

A one-dimensional (1-D) image analysis system, ANOSOL, has been developed which uses test lines to measure the distances in a random direction across and between pore space in images of impregnated soil blocks. Suitable strategies are discussed for both random and systematic sampling using test lines. A comprehensive set of interrelated 1-D parameters are derived for use as structural indices and their stereological relationship to 3-D parameters is discussed. The intercept length distributions for both pore space and solid can be adequately described using a three-parameter model consisting of the weighted sum of two negative exponential functions. The advantages of the parameters chosen are discussed with references to those used by other workers. The importance of choosing, as structural indices, parameters that are stereologically related to the desired 3-D parameters is also discussed.     

灰色关联及非线性规划法构建传递函数估算黑土水力参数

土壤水分特征曲线和饱和导水率是重要的水力参数,为了简便准确获取这些参数,以松嫩平原黑土区南部为研究区域,采集136个采样点土样用于测定不同土层土壤水分特征曲线、饱和导水率以及土壤理化性质,并运用灰色关联分析确定影响土壤水力参数的主要土壤理化性质,采用非线性规划构建土壤分形维数、有机质、干容重、土壤颗粒组成与土壤水分特征曲线、饱和导水率之间的土壤传递函数,并通过与现有土壤传递函数对比分析进行精度验证。结果表明:1)土壤分形维数是估算土壤水分特征曲线模型参数和饱和导水率的主要参数之一,同时,干容重和有机质含量也在不同土层土壤传递函数中起到重要的作用;2)通过验证分析,不同土层各参数平均绝对误差接近于0,均方根误差值也都较小,其中在不同土层土壤传递函数估算的土壤含水率均方根误差分别为0.022、0.017cm~3/cm~3;3)对比分析其他已存的土壤水分特征曲线和饱和导水率的土壤传递函数,该文构建的土壤传递函数均方根误差值均较小,决定系数值都在0.66以上,表明估算精度较高,均好于其他方法估算精度,具有良好的区域适应性。综上,所构建的土壤水分特征曲线和饱和导水率土壤传递函数可以用于松嫩平原黑土区土壤水力参数估算。     

Beyond microbial diversity for predicting soil functions: A mini review

Since the advent of sequencing technologies,the determination of microbial diversity to predict microbial functions,which are the major determinants of soil functions,has become a major topic of interest,as evidenced by the 900 publications dealing with soil metagenome published up to 2017.However,the detection of a gene in soil does not mean that the relative function is expressed,and the presence of a particular taxon does not mean that the relative functions determined in pure culture also occur in the studied soil.Another critical step is to link microbial community composition or function to the product analyzed to determine flux rates.Indeed,flux rates might not only be highly dynamic,but several metabolites can depend on different reactions,which makes the link to one process of interest difficult or even impossible.This review also discusses biases caused by sampling,storage of samples,DNA extraction and purification,sequencing(amplicon-vs.metagenome sequencing),and bioinformatic data analysis.Insights and the limits of predicting microbial interactions by network inference methods are critically discussed,and finally,future directions for a better understanding of soil functions by using measurements of microbial diversity are presented.     

Pan Bread and Chinese White Salted Noodle Qualities of Chinese Winter Wheat Cultivars and Their Relationship with Gluten Protein Fractions

Improvement of food processing quality has become a major breeding objective in China. Nineteen Chinese leading winter wheat cultivars with improved quality and two Australian cultivars with high bread and noodle-making qualities were sown in four locations for two years to investigate dough properties, pan bread, and Chinese white salted noodle (CWSN) qualities, and their association with the quantity of protein fractions. The results indicated that genotype, environment, and genotype-by-environment interaction significantly affected most of quality traits and amount of protein fractions. Genotype mainly determined the quantity of gluten protein fractions and pan bread quality parameters, while environment was the most important source of variation for the noodle quality parameters. Chinese cultivars were characterized by acceptable protein content (11.1–13.4%), medium to strong dough strength (maximum resistance 176.9–746.5 BU), medium to poor dough extensibility (166.5–216.4 mm), fair to very good pan bread qualities, and good to very good CWSN qualities. Gliadin contributed more in quantity to protein content (r = 0.80, P < 0.001), however, glutenin and its subgroups were more important to dough strength. The quantity of glutenin, HMW-GS, and LMW-GS were highly and significantly correlated with dough strength-related traits such as farinograph development time, stability, extensigraph maximum resistance, and extension area (r = 0.70–0.91, 0.65–0.89, and 0.70–0.91, respectively; P < 0.001). The quantity of LMW-GS could explain 82.8% of the total variation of dough maximum resistance. The quantity of gliadin and the ratio of HMW-GS to LMW-GS determined dough extensibility (r = 0.75 and r = –0.59, respectively; P < 0.001 and P < 0.01, respectively). Higher quantity of glutenin and lower ratio of gliadin to glutenin resulted in higher bread score with r = 0.70 (P < 0.001) and r = –0.74 (P < 0.001), respectively. However, protein content and its fractions have a moderate undesirable effect on CWSN parameters such as color, firmness, and taste. Therefore, both allelic variation and quantity of storage protein fractions should be considered in breeding cultivars with improved pan bread making quality.     

THE EFFECT OF SOIL TYPE, SLOPE, RAIN INTENSITY AND THEIR INTERACTIONS ON SPLASH DETACHMENT AND TRANSPORT

From a factorial experiment using a graded sand and three soils (sand, clay loam, and clay), five slopes (0.0, 3.5, 7.0, and 14.0 per cent) and four intensities (50, 80, 110, and 140 mm h^?1), splash detachment and splash transport are described in terms of the direct effects and the first and second order interactions of these variables. The graded sand and three soils tested are significantly different in the mean weight of soil detached and transported. They can be placed in rank order of graded sand, sand, clay, and clay loam with increasing resistance to splash detachment. The amount of material transported is in the order of graded sand > clay > sand > clay loam. For each soil there are significant increases in splash detachment and splash transport with increasing rainfall intensity. Both splash parameters are significantly correlated with slope steepness. The most important interactions that influence splash detachment and splash transport are soil × intensity and slope × intensity respectively. Significant interactions show that the factors are not independent of each other; the simple effects of a factor differ, and the magnitude of any simple effect varies according to the level of the other factors of the interaction term. These interactions have not been explicitly studied in previous research on splash erosion. Power equations are established between splash activity and the above variables and reasonable working ranges for the exponents are suggested.     

Mathematical representation of related periodic variables using fourier series and projections of vector functions: application to the biological sciences

Environmental and biological periodic variables have been expressed as Fourier series, combined in vector functions and then projected onto defined planes. The projections show the interactions between the variables with time. Integrated and differentiated forms of periodic variables measured as change per unit time can also be projected. Examples using annual environmental and biological data are presented but the approach has a wide applicability to relationships of any length of period.     

精细农业机械化作物生产计算机集成技术(英)

介绍了一项适用于精细农业机械化的新技术：计算机集成作物生产技术（CCP）。该技术融合信息采集、网络通讯、数据处理、过程决策、自动执行等功能，能有效地完成作物生产的精确机械化作业。计算机集成作物生产技术的3个主要功能是先根据需要实时采集传感数据，然后根据传感信息构建合理的行动决策，最后将传递上述决策并付诸实施。为了说明CCP的工作原理和结构设计，介绍了由伊利诺依大学机械电子系统实验室设计开发的CCP技术系统的关键功能。研究结果表明，在车辆自动导航，主从机械控制，在线式变量作业等利用农业机械实施田间作物生产作业的领域，有必要在农业机械上集成CCP技术，使机械自动地完成各项最优化项目作业。最后，根据以往工作中的经验，简要讨论了目前CPP技术发展所面临的问题和挑战。     

干燥物系解析理论研究进展

干燥是含湿物料与有限介质两个独立物系,在限定的工艺条件下,自发进行能量传递和转换的过程。它隶属热力学范畴,而又不同于一般的热力过程,在物系边界存在诸多错综复杂的随机因素交互作用,使得基于热力学熵参数无法对实际过程的能效进行实时的定量评价。基于传递定律建立扩散模型,得不到传递系数严格意义的数学解,存在微积分结果偏离实际较远的情况;基于反应工程原理建立干燥动力学模型,存在指前因子,活化能,机理函数等待定的物理量,实际应用存在很大的局限性。如何从理论上完整地解析出实际过程,得到其分析解是热力学应用技术基础科学研究领域自古以来的重大理论难题。近十几年,笔者从非均相系热力学基础和干燥?分析入手,以干燥?传递和转换时的自由能消耗为统一尺度,以水分活度为一切干燥物系的共同属性,揭示了干燥物系固有特征函数及其理论解,丰富了热力学应用技术基础理论。该文从干燥物系解析理论发展的历史现状,阐释揭示物料干燥理论过程、评价工艺装备能效的解析理论与方法并指明其应用与发展的技术途径,为揭示物系传递机理、评价工艺装备系统能效、实现干燥过程自适应控制和制订科学的工艺能效评价标准提供参考。     

Testing for additivity in chemical mixtures using a fixed-ratio ray design and statistical equivalence testing methods

Fixed-ratio ray designs have been used for detecting and characterizing interactions of large numbers of chemicals in combination. Single-chemical dose-response data are used to predict an “additivity curve” along an environmentally relevant ray. A “mixture curve” is estimated from the mixture dose-response data along the ray. A test of additivity is equivalent to a test of coincidence of these two curves, which is based on the traditional hypothesis testing framework that assumes additivity in the null hypothesis and rejects with evidence of interaction. However, failure to reject may be due to lack of statistical power, making the claim of additivity problematic. As a solution we have developed rigorous methodology to test for additivity using statistical equivalence testing logic in which additivity is claimed based on pre-specified biologically important additivity margins, if the data support such a claim. Using the principle of confidence interval inclusion, a confidence region about the difference of meaningful functions of model parameters from the mixture model and that predicted under additivity is computed. When the confidence region is completely contained within the additivity margins then additivity is claimed with a Type I error rate chosen a priori to be some acceptably small value. The method is illustrated using an environmentally relevant fixed-ratio mixture of nine haloacetic acids where cytotoxic response is measured.     

Genotype-by-environment interaction of elite heat and drought tolerant bread wheat (Triticum aestivum L.) genotypes under non-stressed and drought-stressed conditions

ABSTRACT

The selection of relatively high and stable yielding genotypes is key in wheat breeding programs to improve yield performance under heat and drought-stressed environments. This study determined grain yield response and stability among elite heat and drought tolerant bread wheat genotypes under simulated drought-stressed (DS) and non-stressed (NS) environments to select promising parents for breeding. Twenty-four elite bread wheat genotypes selected from the International Maize and Wheat Improvement Centre (CIMMYT) drought and heat tolerant nursery were assessed under NS and DS conditions using a 7?×?4 alpha-lattice design under rainout shelter (RS) and glasshouse (GH) environments. Grain yield data was subjected to analysis of variance (ANOVA), the additive main effect and multiplicative interaction (AMMI) and genotype and genotype-by-environment (GGE) biplot analyses. ANOVA and AMMI revealed highly significant (p?≤?0.001) differences among test genotypes (G), environments (E) and G?×?E interaction effects suggesting differential responses for selection. The GGE biplot explained 83.76% of total variation and aided in selection of high-yielding and stable heat and drought tolerant wheat genotypes such as LM13, LM22, LM95 and LM100. These selections are recommended for breeding for yield gains under heat and drought-stressed environments.