Knowledge Management Portal

In plants, the study of belowground traits is gaining momentum due to their importance on yield formation and the uptake of water and nutrients. In several cereal crops, seminal root number and seminal root angle are proxy traits of the root system architecture at the mature stages, which in turn contributes to modulating the uptake of water and nutrients. Along with seminal root number and seminal root angle, experimental evidence indicates that the transpiration rate response to evaporative demand or vapor pressure deficit is a key physiological trait that might be targeted to cope with drought tolerance as the reduction of the water flux to leaves for limiting transpiration rate at high levels of vapor pressure deficit allows to better manage soil moisture. In the present study, we examined the phenotypic diversity of seminal root number, seminal root angle, and transpiration rate at the seedling stage in a panel of 8-way Multiparent Advanced Generation Inter-Crosses lines of winter barley and correlated these traits with grain yield measured in different site-by-season combinations. Second, phenotypic and genotypic data of the Multiparent Advanced Generation Inter-Crosses population were combined to fit and cross-validate different genomic prediction models for these belowground and physiological traits. Genomic prediction models for seminal root number were fitted using threshold and log-normal models, considering these data as ordinal discrete variable and as count data, respectively, while for seminal root angle and transpiration rate, genomic prediction was implemented using models based on extended genomic best linear unbiased predictors. The results presented in this study show that genome-enabled prediction models of seminal root number, seminal root angle, and transpiration rate data have high predictive ability and that the best models investigated in the present study include first-order additive × additive epistatic interaction effects. Our analyses indicate that beyond grain yield, genomic prediction models might be used to predict belowground and physiological traits and pave the way to practical applications for barley improvement.

A large proportion of rural households, particularly in the dry land areas, representative for more than 10% of the world's land surface and up to 80% in Morocco, depend for their livelihoods on livestock. They exploit livestock's capacity to live in very harsh environments using herd-mobility at multiple scale level. Understanding the multiple contributions of livestock to the household and national economy raises complex research issues and challenges linked with the multitude of goods and services derived from livestock, their interactions with other family activities, and the local and national context. The objective of our research was therefore to analyse the diversity and assess the resilience of livelihood strategies of farming households oriented to livestock using a set of data collected in the dry land areas (oases and mountainous zones) of Morocco and discuss the livelihood outcome indicators. To achieve this, we have realized a cross-sectional analysis of livelihoods and adaptive capacity, to select a set of pertinent indicators. These indicators have been developed using an adapted version of the Rural Household Multi-Indicator Survey (RHoMIS) toolkit for pastoral and agropastoral household systems. Our results highlight the critical importance of livelihood diversification (off-farm diversification, livestock diversification, and crop diversification) in building household resilience and the livelihood outcomes. While livelihood strategies undoubtedly contribute to livelihood outcomes, there is also a critical iterative process, i.e., livelihood outcomes also influence the livelihood strategies at the farming households. The present work proposes an aggregated indicator of livelihood outcomes allowing us to capture the heterogeneity of living conditions of agropastoral systems by considering the main drivers of this system, i.e., mobility, livestock species, and physiological stage composition of the herd. This approach could constitute a valuable contribution to help fill the knowledge gaps that do not allow policy makers in developing contextualized rural development policies and instruments in these very harsh environments.

Evapotranspiration (ET) measurement on a real-time basis at a large scale with high temporal frequency is important for agricultural water use and water resource planning. Identifying the differences between potential ET and crop ET at fine spatial resolutions is essential for management of agriculture and water resources. It could contribute to the water deficit assessment at the individual farm level. This study evaluates the potential of remote sensing-based models at five different locations in the Near East and North African (NENA) region. Ground-based ET was determined for these locations during different crop growing seasons. Remote sensing-based ET estimates generated through three remote sensingbased models (WaPOR, METRIC, and SEBAL) were compared with ground-based estimates. This comparative analysis evaluated the remote sensing-based modelling approaches and identified the model that generated the closest estimates to the ground estimates. Results showed that SEBAL and METRIC performed well except few locations. SEBAL showed highest index of agreement (d) (0.49 to 0.91) between observed and estimated ET data followed by METRIC (0.40 to 0.66) and WaPOR (0.31 to 0.61) for all seasons. Overall, the model's performance parameters showed that SEBAL had the smallest nRMSE and uncertainty and the largest Ratio of Performance to Deviation (RPD) and (d) compared to the other two models. RPD has been used as the standard way to report the quality of a model. Therefore, the results of this study reveal that SEBAL performed well for study locations followed by METRIC and WaPOR. Another finding for the study locations is that the ground ET determination technique based on soil moisture depletion (SMD) was less correlated with RS-based ET than other techniques.

SKiM 2021 Steering Committee minutes

Steering Committee presentation by the National Focal Point of Sudan on the national developments and future perspectives in knowledge management.

SKiM 2021 Steering Committee presentation on enhancing KM performance through science and community of practices on knowledge management.

Steering Committee presentation by the National Focal Point of Morocco on the national developments and future perspectives in knowledge management.

SKiM 2021 Steering Committee presentation by Virginia Tech on the value of knowledge.