Web Application for Spatial Modelling of Field Trials

In plant improvement experimental designs are used to decompose the total phenotypic variance observed in field experiments into at least two components: A genetic and a non-genetic component that is attributable to the spatial variation or environment. Recently, new methodologies for the modelling of spatial trends have been published using the arrangement of the experimental units in the field. These methodologies have shown an improvement in the prediction of the genetic potential of evaluated genotypes. However, the use of these tools may be limited because of the cost to access a licensed product and/or the requirement to be familiar with the language and environment that was used for their implementation. This, in turn limits the data analysis efficiency for decision making. These limitations led to the development of Mr.Bean, an easy-to-access, practical and user-friendly tool that integrates the spatial modelling capabilities of SpATS, the graphical versatility of plotly and the interactive and simple construction approach offered by Shiny for the development of Web applications. This tool incorporates descriptive analyses, measures of dispersion and centralization, graphical visualization for comparing multiple variables, the adjustment of mixed models with or without spatial components and the identification of outlier data. All these capabilities are aimed at plant breeders and in general people working with agricultural field data to make precise decisions more quickl

First draft report on use of simulation tools to optimize breeding strategies in the breeding program of interspecific hybrids of Urochloa sp. breeding program at CIAT

There is a plethora of new technologies available for breeding programs. Those technologies tend to become “bandwagons - a bandwagon is an idea, activity, or because that becomes increasingly fashionable as more and more people adopt it” as described by Bernardo (2016). Breeders are usually tempted to apply it all. However, as it has been proven by history not all bandwagons are successful for all breeding schemes, and at the end the goal of increasing the genetic gain is not always achieved. Simulation approaches have proven to be an efficient tool to support decision making processes in several fields. Various software packages for breeding simulations are currently available which differ in the input information which needs to be provided to the program, the operative background calculations (e.g. population history simulation or model calculations for multivariate normal distribution) and output provided (Sun et al., 2011, Mi et al., 2014, Faux et al., 2016). Two simulation-based R packages have been widely adopted in the CGIAR and other institutions to support the decision-making process and resource allocation that breeders do in daily life named, AlphaSim (Faux et al., 2016; Gaynor at el., 2021) and SelectionGain (Mi et al., 2014). Those packages test the effect of the size of the breeding program, the number of breeding and testing stages, and the effect of accuracy of the trials and selection intensity in the expected genetic gain (GG). In the description of the different schemes tested, new technologies can also be represented, being able to predict the effect of those technologies in the genetic gain, which in turn, can make the waves of bandwagons less acute and allocation of funding also more effective. The Brachiaria intespecific breeding program at CIAT, with nearly 30 years of experience, is unique by its biology (polyploid and apomictic) and by being an example of several new technologies successfully used (induced polyploidy, Marker assisted selection (MAS), clonal propagation, Near Infrared Spectophotometry (NIRS), drone-based image analysis within others). The program releases apomictic hybrids by applying a scheme of recurrent selection in the female parent pool while maintaining the apomictic tester fixed, also known as recurrent selection based on specific combining ability (RS-SCA; Hull 1945; Miles 2007). The apomictic male parent pool (Brachiaria decumbens) has been difficult to improve due to the unavailability of a B. decumbens sexual tetraploid individual that enables the crosses for that pool, respecting the heterotic pattern. In this study we used simulation-based R packages to test various possible modifications to the current breeding scheme being applied at the Urochloa intespecific breeding program at CIAT. We explored the impact in the genetic gain given by the possible migration from RS-SCA, to reciprocal recurrent selection (RRS), considering the challenges in logistics and population size. More specifically, the refreshing of the apomictic tester in each future heterotic pool and the hybrid formation under various sizes of the diallel crossing design. With a 20 years burn-in period used as baseline, followed by 30 year evaluation period, the simulations revealed that the first 15 years the current breeding scheme (RS-SCA) offers higher rates of GG, but after that, this scheme is surpass by all treatments with RRS. We hypothesize, in the RS-SCA the genetic variability is exhausted during the first 15 years, while the RRS provides double genetic variability to exploit. We discuss the challenges on the application of this new approach at the light of the logistics and the lack of a sexual tetraploid individual for the crosses in the B. decumbens heterotic pool. Currently the study has been finished and the document with all the details is being written, then we plan to submit for peer review before the end of 2021

RankspeQ: An R package platform for genotype characterization and performance-ranking based on MultispeQ measurements

With the new technologies in plant phenotyping, robust and reliable tools are still required to analyze large-scale and multivariate datasets. The RankspeQ is a novel R package developed to evaluate genotype performance and to support selection-driven decisions based on leaf traits and environment-related variables measured by the MultispeQ device. The presented software consists of 3 main functions: i) data cleaning, ii) computational trait- genotype ranking, and iii) comparison of accessions against grain yield or another crop trait. Optionally, the evaluation can be performed by alternative groups which can be defined by the user, such as genepools, families, among others. The software development as well as the data evaluation was made with datasets of Phaseolus spp. experiments. However, R code - with easy modifications - can be used on any other crop. This valuable tool helps to understand the hidden potential of MultispeQ equipment and - most - identify crop traits useful in genotype characterization in particular environments. The tool has direct potential for physiologists, breeders etc. as it identifies the best performing accessions. However, it also targets false positive results with low yield but high photosynthetic performance. We also propose to use a new efficiency index to calculate the ratio of incoming radiation for net photosynthesis in proportion to light dissipation processes. Further updates will include new algorithms (e.g. trait heritability), generalization to other species and a shiny interface to make the software user friendly

FarmConners market showcase results: wind farm flow control considering electricity prices

The EU and UK have made ambitious commitments under the net-zero plans to decarbonise their economies by 2050. For this, offshore wind will play a major role, significantly contributing to a paradigm shift in the power generation and greater volatility of electricity prices. The operating strategy of wind farms should therefore move from power maximisation to profit maximisation which includes income from providing power system services and the reduction of maintenance costs. Wind farm flow control (WFFC) is a key enabler for this shift through mitigation of wake effects in the design and operation phases. The results of the FarmConners market showcases presented here are the first attempt to economically assess WFFC strategies with respect to electricity market prices. Here, we present a conceptual simulation study starting from individual turbine control and extend it to layouts with 10 and 32 turbines operated with WFFC based on the results of five participants. Each participant belonged to a different research group with their respective simulation environments, flow models and WFFC strategies. Via a comparative analysis of relative WFFC benefits estimated per participant, the implications of wind farm size, the applied control strategy and the overall model fidelity are discussed in zero-subsidy scenarios. For all the participants, it is seen that the income gain can differ significantly from the power gain depending on the electricity price under the same inflow, and a favourable control strategy for dominant wind directions can pay off even for low electricity prices. However, a strong correlation between income and power gain is also observed for the analysed high-electricity-price scenarios, underlining the need for additional modelling capabilities to carry out a more comprehensive value optimisation including lower prices and system requirements driven cases.FarmConners market showcase results: wind farm flow control considering electricity pricespublishedVersio

Estimation of genetic gain for resistance to spittlebugs (Hemiptera: Cercopidae) in the Interspecific Urochloa CIAT Breeding Program using historical data

Grasses from the genus Urochloa are sown worldwide throughout the tropics and subtropics. Urochloa grasses have different attributes that make them an important forage resource, however susceptibility to abiotic and biotic stresses are also common. In order to develop a superior forage source, the interspecific Urochloa breeding programme was started at CIAT in the late 1980’s combining desirable attributes of the three most important species signalgrass (U. decumbens), palisadegrass (U. brizantha) and ruzigrass (U. ruziziensis). One of the main targets of the breeding programme is to continuously improve resistance to spittlebugs (Hemiptera: Cercopidae), which cause high economic damage in livestock systems throughout tropical and subtropical America. In the recurrent selection breeding scheme, seven successive cycles of selection of the apomictic hybrids and the parental sexual lines were screened for resistance to four species at the nymphal stage, measured as damage to plants based on visual scoring (0-5), using a high throughput methodology in the greenhouse. A means to measure the response to selection of a breeding programme is to estimate the rate of genetic gain for the target traits. The assembly of historical data from founders of the breeding programme and seven generations of the synthetic population of female parents in a linear mixed model, allowed the quantification of the rate of genetic gain for the improvement in resistance to spittlebugs. This rate was estimated as the slope of the line obtained by plotting the values of resistance across generations. The analysis shows a rapid and simultaneous increase in the resistance against three species of spittlebug nymphs: Aenolamia varia, A. reducta and Zulia carbonaria after seven cycles of selection. Resistance to Prosapia simulans was screened in only one cycle showing some level of resistance in the genotypes that can be exploited for improvement in the future. The success in the continuous improvement for spittlebug resistance can be explained by the fact that within a breeding cycle, parents are screened and selected based on their resistance level to spittlebug as part of the parental population improvement

Mr.Bean: a comprehensive statistical and visualization application for modeling agricultural field trials data

Crop improvement efforts have exploited new methods for modeling spatial trends using the arrangement of the experimental units in the field. These methods have shown improvement in predicting the genetic potential of evaluated genotypes. However, the use of these tools may be limited by the exposure and accessibility to these products. In addition, these new methodologies often require plant scientists to be familiar with the programming environment used to implement them; constraints that limit data analysis efficiency for decision-making. These challenges have led to the development of Mr.Bean, an accessible and user-friendly tool with a comprehensive graphical visualization interface. The application integrates descriptive analysis, measures of dispersion and centralization, linear mixed model fitting, multi-environment trial analysis, factor analytic models, and genomic analysis. All these capabilities are designed to help plant breeders and scientist working with agricultural field trials make informed decisions more quickly. Mr.Bean is available for download at https://github.com/AparicioJohan/MrBeanApp

FielDHub: A shiny app for design of experiments in life sciences

FielDHub is an R Shiny design of experiments (DOE) app that aids in the creation of traditional, unreplicated, augmented and partially-replicated (Cullis et al., 2006) designs applied to agriculture, plant breeding, forestry, animal and biological sciences. One of the problems that life scientists often face is the lack of freely available and user-friendly interactive tools to create designs that fit their needs. A few open-source DOE R packages options exist including agricolae (de Mendiburu & Yaseen, 2020) and blocksdesign (Edmondson, 2021), but they require users to be familiar with the R programming language and do not have a graphical user interface (GUI)