Search

Copyright of Irrigation & Drainage is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Ensuring global food security in the face of climate change is critical to human survival. With a predicted human population of 9.6 billion in 2050 and the demand for food supplies expected to increase by 60% globally, but with a parallel potential reduction in crop production for wheat by 6.0%, rice by 3.2%, maize by 7.4%, and soybean by 3.1% by the end of the century, maintaining future food security will be a challenge. One potential solution is new climate-smart varieties created using the breadth of diversity inherent in crop wild relatives (CWRs). Yet CWRs are threatened, with 16–35% regarded as threatened and a significantly higher percentage suffering genetic erosion. Additionally, they are under-conserved, 95% requiring additional ex situ collections and less than 1% being actively conserved in situ; they also often grow naturally in disturbed habitats limiting standard conservation measures. The urgent requirement for active CWR conservation is widely recognized in the global policy context (Convention on Biological Diversity post-2020 Global Biodiversity Framework, UN Sustainable Development Goals, the FAO Second Global Plan of Action for PGRFA, and the FAO Framework for Action on Biodiversity for Food and Agriculture) and breeders highlight that the lack of CWR diversity is unnecessarily limiting crop improvement. CWRs are not spread evenly across the globe; they are focused in hotspots and the hottest region for CWR diversity is in West Asia and North Africa (WANA). The region has about 40% of global priority taxa and the top 17 countries with maximum numbers of CWR taxa per unit area are all in WANA. Therefore, improved CWR active conservation in WANA is not only a regional but a critical global priority. To assist in the achievement of this goal, we will review the following topics for CWRs in the WANA region: (1) conservation status, (2) community-based conservation, (3) threat status, (4) diversity use, (5) CURE—CWR hub: (ICARDA Centre of Excellence), and (6) recommendations for research priorities. The implementation of the recommendations is likely to significantly improve CWRs in situ and ex situ conservation and will potentially at least double the availability of the full breadth of CWR diversity found in WANA to breeders, and so enhance regional and global food and nutritional security. [ABSTRACT FROM AUTHOR]

The Anomaly hotSpots of Agricultural Production (ASAP) Decision Support System was launched operationally in 2017 for providing timely early warning information on agricultural production based on Earth Observation and agro-climatic data in an open and easy to use online platform. Over the last three years, the system has seen several methodological improvements related to the input indicators and to system functionalities. These include: an improved dataset of rainfall estimates for Africa; a new satellite indicator of biomass optimised for near-real-time monitoring; an indicator of crop and rangeland water stress derived from a water balance accounting scheme; the inclusion of seasonal precipitation forecasts; national and sub-national crop calendars adapted to ASAP phenology; and a new interface for the visualisation and analysis of high spatial resolution Sentinel and Landsat data. In parallel to these technical improvements, stakeholders and users uptake was consolidated through the set up of regionally adapted versions of the ASAP system for Eastern Africa in partnership with the Intergovernmental Authority on Development (IGAD) Climate Prediction and Applications Centre (ICPAC), for North Africa with the Observatoire du Sahara et du Sahel (OSS), and through the collaboration with the Angolan National Institute of Meteorology and Geophysics (INAMET), that used the ASAP system to inform about agricultural drought. Finally, ASAP indicators have been used as inputs for quantitative crop yield forecasting with machine learning at the province level for Algeria's 2021 and 2022 winter crop seasons that were affected by drought. [ABSTRACT FROM AUTHOR]

This paper uses panel cointegration techniques and Granger causality tests to investigate the dynamic causal links between per capita renewable energy consumption, agricultural value added (AVA), carbon dioxide (CO 2 ) emissions, and real gross domestic product (GDP) for a panel of five North Africa countries spanning the period 1980–2011. In the short-run, Granger causality tests show the existence of bidirectional causality between CO 2 emissions and agriculture; a unidirectional causality running from agriculture to GDP, from GDP to renewable energy consumption, and from renewable energy consumption to agriculture. In the long-run, there is bidirectional causality between agriculture and CO 2 emissions; a unidirectional causality running from renewable energy to agriculture and to emissions, and from output to agriculture and to emissions. Long-run parameter estimates show that an increase in GDP or in renewable energy consumption (including combustible and waste) increases CO 2 emissions, whereas an increase in agricultural value added reduces CO 2 emissions. As policy recommendation, North African authorities should encourage renewable energy consumption, and especially clean renewable energy such as solar or wind, as this improves agricultural production and help to combat global warming. [ABSTRACT FROM AUTHOR]

This paper measures agricultural productivity growth by means of the sequential Malmquist Total Factor Productivity (TFP) index among a set of 32 West European, Central and East European (CEE), and Middle Eastern and North African (MENA) countries for the period 1961–2002. In a second stage, the authors also investigate whether this measure is converging among these countries by employing cross-sectional tests for absolute and conditional β-convergence as well as for club convergence. The results suggest that, despite the fact that the CEE and MENA countries have exhibited a high rate of productivity growth since the 1990s, absolute convergence cannot be confirmed. Evidence for conditional convergence is still found and the formation of two separate clubs of countries that converge to different equilibrium points is identified. [ABSTRACT FROM AUTHOR]

Displaying Nitrogen (N) indicators on a global grid poses unique opportunities to quantify environmental impacts from N application in different world regions under a variety of conditions. Such calculations require the use of maps showing the geo‐spatial distribution of crop production. Although there are several crop maps in the scientific literature to choose from, the consequences of this choice for the calculation of N indicators still need to be evaluated. In this study we analyze the differences in results for N Use Efficiency (NUE) and N surplus calculated on the global scale using two different crop maps (SPAM and M3). For our calculations we used publicly available statistical and literature data combined with each crop map and carefully traced the origins of the differences in the results. Our results showed that the regions most affected by discrepancies caused by differences in crop maps (yields and physical area) are Central Asia and the Russian Federation, Australia and Oceania, and North Africa. However, we also found that the inclusion or exclusion of grass crops influences the results, as does the aggregation of crops to categories. Considering all these differences, we note that M3 seems to provide the more plausible results for the calculation of N indicators. Our analysis not only highlights the importance of determining the critical parameters for N indicator calculation, but also allows key parameters connected with N use and overuse to be identified on the global scale. Key Points: Parameters like N surplus and NUE values are highly sensitive to the choice of crop mapAssumptions on grass crops also strongly influence N surplus and NUELeast bias in N indicators has been noted when using the M3 crop map [ABSTRACT FROM AUTHOR]

Originating from multivariate statistics, random matrix theory (RMT) is used in order to test whether the elements of an empirical correlation coefficient matrix are noise dominated or contain true information. In this article, an attempt is made to apply the properties of RMT in macroeconomic time series data, by investigating the degree of convergence in agricultural labour productivity growth among a set of 32 European and Middle East and North Africa countries. Once the distribution of the eigenvalues of the empirical correlation matrix is found to differ from that of a pure random matrix, data are further analysed by means of hierarchical clustering techniques which allow for the creation of data clusters with common properties. This two-step procedure is an alternate means for club convergence tests, while some sensitivity analysis tests indicate an acceptable level of robustness of the proposed methodology even in small sample sizes. [ABSTRACT FROM AUTHOR]

The interest of governments, international organizations, NGOs and the general public has recently been aroused by studies considering the use of existing agricultural technology, the use of innovations in such technology and the production of agricultural goods. The attention received by such studies has grown as a result of an unprecedented wave of trade liberalization in the world (involving bilateral, regional and multilateral trade-integration processes), coupled with concerns over food security, high rates of population growth and the use of limited and frequently degraded natural resources. In this context, the Malmquist Index, used to measure agricultural productivity, is a powerful tool, providing insights into whether or not a country is approaching what may be termed 'best practice' by using and disseminating existing technology (efficiency change), and/or by innovating technology (technical change). Using the Malmquist Index on a sample of 12 countries within West Asia and North Africa (WANA) indicated that, between 1961 and 1997, Turkey, Tunisia, Syria and Algeria (in that order) were the 'most productive' countries. Following them, in terms of agricultural productivity, were Iran, Egypt, Jordan and Morocco, while Pakistan, Sudan, Yemen and Ethiopia were the 'least productive' countries of the 12 considered. Recurring negative results, with respect to both technical change and efficiency change, in Ethiopia, Sudan, Pakistan and Yemen, suggest that governments and national and international organizations and research institutions should make greater efforts to strengthen agricultural research and extension services if food security and competitiveness are to be improved. [ABSTRACT FROM AUTHOR]

Date palm is one of the most economically important woody crops cultivated in the Middle East and North Africa and is a good candidate for improving agricultural yields in arid environments. Nonetheless, long generation times (5-8 years) and dioecy (separate male and female trees) have complicated its cultivation and genetic analysis. To address these issues, we assembled a draft genome for a Khalas variety female date palm, the first publicly available resource of its type for a member of the order Arecales. The ∼380 Mb sequence, spanning mainly gene-rich regions, includes >25,000 gene models and is predicted to cover ∼90% of genes and ∼60% of the genome. Sequencing of eight other cultivars, including females of the Deglet Noor and Medjool varieties and their backcrossed males, identified >3.5 million polymorphic sites, including >10,000 genic copy number variations. A small subset of these polymorphisms can distinguish multiple varieties. We identified a region of the genome linked to gender and found evidence that date palm employs an XY system of gender inheritance. [ABSTRACT FROM AUTHOR]

In Morocco, cereal production shows high interannual variability due to uncertain rainfall and recurrent drought periods. Considering the socioeconomic importance of cereal for the country, there is a serious need to characterize the impact of drought on cereal yields. In this study, drought is assessed through (1) indices derived from remote sensing data (the vegetation condition index (VCI), temperature condition index (TCI), vegetation health ind ex (VHI), soil moisture condition index (SMCI) and soil water index for different soil layers (SWI)) and (2) key land surface variables (Land Area Index (LAI), soil moisture (SM) at different depths, soil evaporation and plant transpiration) from a Land Data Assimilation System (LDAS) over 2000–2017. A lagged correlation analysis was conducted to assess the relationships between the drought indices and cereal yield at monthly time scales. The VCI and LAI around the heading stage (March-April) are highly linked to yield for all provinces (R = 0.94 for the Khemisset province), while a high link for TCI occurs during the development stage in January-February (R = 0.83 for the Beni Mellal province). Interestingly, indices related to soil moisture in the superficial soil layer are correlated with yield earlier in the season around the emergence stage (December). The results demonstrate the clear added value of using an LDAS compared with using a remote sensing product alone, particularly concerning the soil moisture in the root-zone, considered a key variable for yield production, that is not directly observable from space. The time scale of integration is also discussed. By integrating the indices on the main phenological stages of wheat using a dynamic threshold approach instead of the monthly time scale, the correlation between indices and yield increased by up to 14%. In addition, the contributions of VCI and TCI to VHI were optimized by using yield anomalies as proxies for drought. This study opens perspectives for the development of drought early warning systems in Morocco and over North Africa, as well as for seasonal crop yield forecasting. [ABSTRACT FROM AUTHOR]