Robustly forecasting maize yields in Tanzania based on climatic predictors

Seasonal yield forecasts are important to support agricultural development programs and can contribute to improved food security in developing countries. Despite their importance, no operational forecasting system on sub-national level is yet in place in Tanzania. We develop a statistical maize yield forecast based on regional yield statistics in Tanzania and climatic predictors, covering the period 2009–2019. We forecast both yield anomalies and absolute yields at the sub-national scale about 6 weeks before the harvest. The forecasted yield anomalies (absolute yields) have a median Nash–Sutcliffe efficiency coefficient of 0.72 (0.79) in the out-of-sample cross validation, which corresponds to a median root mean squared error of 0.13 t/ha for absolute yields. In addition, we perform an out-of-sample variable selection and produce completely independent yield forecasts for the harvest year 2019. Our study is potentially applicable to other countries with short time series of yield data and inaccessible or low quality weather data due to the usage of only global climate data and a strict and transparent assessment of the forecasting skill

Global agronomy, a new field of research. A review

The global impact of agriculture has recently become a major research topic, stressed by the rapid growth of the world population. Agriculture management is indeed influencing the quality of water, air, soil, and biodiversity at the global scale. The main agricultural challenges have already been reviewed, but these reviews did not discuss in detail the adaptations of agricultural techniques to global issues and the research challenges for agronomy. Here, we propose a research planning for global agronomy including the following advices. Agronomists should update their research objects, methods, and tools to address global issues. Yield trends and variations among various regions should be analyzed to understand the sources of these variations. Crop model simulations should be upscaled to estimate potential yields and to assess the effect of climate change and resource scarcity at the global scale. Advanced methods should analyze output uncertainty of complex models used at a global scale. Indeed various global models are actually used, but these models are too complex and the output uncertainty is difficult to analyze. The meta-analysis of published data is a promising approach for addressing global issues, though meta-analysis must be applied carefully with appropriate techniques. Finally, global datasets on the performance and environmental impact of cropping systems should be developed to allow agronomists to identify promising cropping systems

Modelling land use strategies to optimise crop production and protection of ecologically important weed species

There is a need to develop farming systems that enable both a satisfactory level of crop production and suitable environmental conditions for natural species. Wildlife-friendly cropping techniques, such as a reduced amount of applied herbicide or a lower crop density, might be adopted in order to maintain populations of weed species of biological interest. An alternative might be to adopt an intensive cropping system in a part of the field and spare the other part as set-aside or field margins, available for the natural development of plant species. The objective of this study was to present a method to compare two strategies for maintaining a desirable level of abundance of a given species of interest in agricultural areas, specifically (i) a strategy based on a wildlife-friendly cropping system in a large cultivated area and (ii) a strategy based on a more intensive cropping system in a reduced area of cultivation, i.e. with land-sparing. The principle is to calculate the ratio of crop production obtained with strategy (i) to the production obtained with strategy (ii) for a given target density of natural species. We show that the value of this ratio, and thus the relative performance of the two strategies, depends on the density of the weed species that can be maintained in an uncultivated ecological area. The method is applied in case studies of two plant species with contrasting ecology and conservation goals. The numerical results show that the strategy based on a wildlife-friendly cropping system is more profitable in most situations

Modeling the effect of soil meso- and macropores topology on the biodegradation of a soluble carbon substrate

Soil structure and interactions between biotic and abiotic processes are increasingly recognized as important for explaining the large uncertainties in the outputs of macroscopic SOM decomposition models. We present a numerical analysis to assess the role of meso- and macropore topology on the biodegradation of a soluble carbon substrate in variably water saturated and pure diffusion conditions . Our analysis was built as a complete factorial design and used a new 3D pore-scale model, LBioS, that couples a diffusion Lattice-Boltzmann model and a compartmental biodegradation model. The scenarios combined contrasted modalities of four factors: meso- and macropore space geometry, water saturation, bacterial distribution and physiology. A global sensitivity analysis of these factors highlighted the role of physical factors in the biodegradation kinetics of our scenarios. Bacteria location explained 28% of the total variance in substrate concentration in all scenarios, while the interactions among location, saturation and geometry explained up to 51% of it

User Profile and Workload Analysis for Local Area Networks

Performance analysis tools for computer networks need accurate and comprehensive estimates of user workload. An approach is presented that estimates network impact for a wide variety of end user types and applications that are typical on local area networks. Fourteen user types and nine generic application types are defined, and data is collected to determine the average network bandwidth needed to accommodate the output of individual and aggregate user/application combinations. Workload is estimated using a combination of data obtained from live test experiments, and data collected from the literature. Finally, the implementation of this data in a highly interactive network modeling tool (NetMod) is illustrated with screen images generated during tool execution.http://deepblue.lib.umich.edu/bitstream/2027.42/107870/1/citi-tr-90-3.pd

Fairness in Oculomotoric Biometric Identification

Gaze patterns are known to be highly individual, and therefore eye movements can serve as a biometric characteristic. We explore aspects of the fairness of biometric identification based on gaze patterns. We find that while oculomotoric identification does not favor any particular gender and does not significantly favor by age range, it is unfair with respect to ethnicity. Moreover, fairness concerning ethnicity cannot be achieved by balancing the training data for the best-performing model