Agricultural Research Knowledge

Permanent URI for this collectionhttps://hdl.handle.net/20.500.11766/187

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A review on the utilization of the by-products generated during the production of Argan oil
Author(s): Hallouch, Otmane; Ibourki, Mohamed; Bijla, Laila; Oubannin, Samira; Asbbane, Aberrahim Asbbane; Mazar, Adil; Devkota, Krishna; Guillaume, Dominique; Wen Goh, Khang; Bouyahya, Abdelhakim; Lee, Learn-Han; Majourhat, Khalid; Gharby, Said (Elsevier (12 months), 2025-04-01)
Date: 2025-03-04
Type: Journal Article
Status: Open access
The annual production of argan oil reaches approximately 4450 tons, which inevitably generates a large quantity of by-products. From the point of view of argan oil production, the pulp, the nutshell and the press cake represent approximately 97 % of the weight of the fruit, while only the kernels, weighing approximately 6 kg per 100 kg of dried fruit, are used to produce argan oil. Such quantity of kernels makes 3 L of argan oil. Most often, by-products resulting from argan oil production are not used industrially and are considered waste. Valorizing those inherently produced by-products is necessary to increase sustainability competitiveness and lessen the impact of the argan oil industry on the environment. This review aims to present an overview of the by-products generated during the production of argan oil, examine current valorization approaches and discuss the prospects for improving their future valorization. The valorization of argan nutshell is one of the most advanced and promising areas, positioning this residue as a sustainable resource that enhances the profitability of the argan oil sector. Their utilization in the production of CO2-based activated charcoal and biofuels further promotes their value and sustainability. Overall, this review highlights the growing interest in argan by-products in recent years, and the emergence of numerous value-adding applications in the fields of bioenergy, nanomaterials, pharmaceutical and cosmetics industries.
Optimizing water-use efficiency under elevated CO₂: A meta-analysis of crop type, soil modulation, and enrichment methods
Author(s): Mokhtar, Ali; He, Hongming; Attaher, Samar; Salem, Ali; Alam, Muneer (Elsevier Masson, 2025-03-31)
Date: 2025-02-04
Type: Journal Article
Status: Open access
Elevated CO2 (eCO2) significantly affect the carbon-water cycle in terrestrial ecosystems especially for gas exchange and water use efficiency (WUE). Therefore, in this study, we have conducted a meta-analysis to quantitative statistical means among studies and discuss how WUE responds to eCO2 under pathway (C3 and C4), four enrichment methods and soil types based on 124 peer-reviewed studies and 1474 observations to provide an in-depth overview of how these factors interact under future CO₂ scenarios. Key findings reveal that: (1) C₃ crops, such as potato and tomato, show significantly greater increases in WUE compared to C₄ crops like maize, with effect sizes of 13.96 and 7.02 for plant-level WUE (WUEₚ), suggesting that C₃ crops may be more advantageous in water-limited environments due to reduced photorespiration under eCO₂; (2) soil type substantially modulates WUE responses, with clay soils, due to their high water-holding capacity, demonstrating the highest WUE enhancements (effect sizes of 7.87 for WUEₚ and 12.54 for yield WUE, WUEᵧ), while sandy soils, characterized by rapid drainage, showed limited improvements; and (3) greenhouse and growth chamber studies displayed the highest WUE improvements, while FACE experiments, which better replicate real-world conditions, indicated smaller WUE increases due to environmental variability, underscoring the need for a hybrid approach that merges controlled data with field insights to develop practical, water-efficient agricultural strategies. Collectively, these findings highlight the potential for crop- and soil-specific strategies to optimize WUE under elevated CO₂, offering valuable insights for sustainable agriculture and climate adaptation.
Performance, Agro-Morphological, and Quality Traits of Durum Wheat (Triticum turgidum L. ssp. durum Desf.) Germplasm: A Case Study in Jemâa Shaïm, Morocco
Author(s): Manhou, Khadija; Taghouti, Mona; Moussadek, Rachid; Elyacoubi, Houda; Bennani, Sahar; Zouahri, Abdelmjid; Ghanimi, Ahmed; Sanad, Hatim; Lhaj, Majda Oueld; Hmouni, Driss; Dakak, Houria (Multidisciplinary Digital Publishing Institute (MDPI))
Date: 2025-05-17
Type: Journal Article
Status: Open access
The productivity and resilience of durum wheat have been enhanced through the selection of accessions, optimizing agronomic and quality traits to address environmental challenges. This study evaluates the performance of 219 durum wheat accessions, including 120 elite lines from a national breeding program (G1 to G120), 63 international lines (G121 to G183), 27 Moroccan varieties (including Faraj, Karim, Tomouh, Marzak, Amria, Chaoui, IRDEN, and others), and nine landraces (G211 to G219, from Imilchil, Rich, and Taounate regions). Trials were conducted at the Jemâa Shaïm experimental station (INRA-Morocco) with an “Alpha lattice” design and two replications. Significant correlations were observed between spike length (SL) and number of spikelets per spike (SPS) (r = 0.950; p < 0.001), and between grain yield (GY) and thousand-kernel weight (TKW) (r = 0.530; p < 0.01), while no correlation was found between quality parameters and GY (r = 0.010; p > 0.05). Principal component analysis (PCA) revealed that agronomic traits explained 77.12% of variability, while quality traits accounted for 95.54%. Elite lines exhibited a high yellow pigment index (14.90), important for technological quality. Traditional landraces performed well in spike length (8.78 cm), thousand-kernel weight (50.23 g), protein content (17.07%), and gluten content (36.90%). Moroccan varieties such as Faraj achieved a grain yield of 6.12 t/ha, while international lines showed the highest SDS value (9.39 mL). These findings highlight the potential of diverse accessions for developing high-yielding, high-quality durum wheat.
Pre-Treatment Effects on Chemico-Physical Characteristics of Argan Press Cake Used for Bread Production
Author(s): El Kaourat, Asma; Choukri, Hasnae; Kartah, Badr; Snoussi, Ahmed; Zeppa, Giuseppe; Benali, Aouatif; Taghouti, Mona; El Monfalouti, Hanae (Multidisciplinary Digital Publishing Institute (MDPI))
Date: 2025-04-10
Type: Journal Article
Status: Open access
Argan oil is known worldwide for its nutritional, therapeutic, and cosmetic benefits. However, the extraction process produces 40–50% of argan press cake (APC), which is rich in protein, fiber, and minerals. Despite its nutritional potential, the high saponin content of APC imparts a bitter taste and anti-nutritional properties, making it unsuitable for human consumption and often wasted. This study addresses this issue by using boiling treatments with citric acid (CA) and distilled water (DW) to reduce the saponin content while evaluating the impact on APC quality. In addition, this study explores, for the first time, the incorporation of treated argan press cake, APC-CA and APC-DW, at different levels (5%, 10%, 15%, and 20%) into whole wheat flour (WWF) for bread production to improve the nutritional profile. The results indicate that both treatments significantly reduce saponin content while maintaining nutritional quality comparable to untreated APC. This includes a 50% reduction in phytic acid levels. The absence of tryptophan fluorescence emission was observed in APC-CA, which may be related to chemical degradation or interactions with other molecules. The substitution of APC-CA and APC-DW increased the protein of composite flours in a level-dependent manner. At substitution levels up to 10%, APC-CA and APC-DW positively influenced the technological properties of the bread. This study demonstrates the potential of APC to improve the nutritional value of bread and supports zero-waste initiatives by reusing by-products.
Selection Increases Mitonuclear DNA Discordance but Reconciles Incompatibility in African Cattle
Author(s): Shi, Xian; Ma, Cheng Ma; Chen, Ningbo; Xu, Ming-Min; Kambal, Sumaya; Cai, Zheng-Fei; Yang, Qiwen; Adeola, Adeniyi C; Liu, Li-Sheng; Wang, Jun; Lu, Wen-Fa; Li, Yan; Msalya, George M; Lei, Chuzhao; Mwacharo, Joram; Jianlin, Han; Hanotte, Olivier; Zhang, Ya-Ping; Peng, Min-Sheng (Oxford University Press (OUP))
Date: 2025-02-08
Type: Journal Article
Status: Open access
Mitochondrial function relies on the coordinated interactions between genes in the mitochondrial DNA and nuclear genomes. Imperfect interactions following mitonuclear incompatibility may lead to reduced fitness. Mitochondrial DNA introgressions across species and populations are common and well documented. Various strategies may be expected to reconcile mitonuclear incompatibility in hybrids or admixed individuals. African admixed cattle (Bos taurus × B. indicus) show sex-biased admixture, with taurine (B. taurus) mitochondrial DNA and a nuclear genome predominantly of humped zebu (B. indicus). Here, we leveraged local ancestry inference approaches to identify the ancestry and distribution patterns of nuclear functional genes associated with the mitochondrial oxidative phosphorylation process in the genomes of African admixed cattle. We show that most of the nuclear genes involved in mitonuclear interactions are under selection and of humped zebu ancestry. Variations in mitochondrial DNA copy number may have contributed to the recovery of optimal mitochondrial function following admixture with the regulation of gene expression, alleviating or nullifying mitochondrial dysfunction. Interestingly, some nuclear mitochondrial genes with enrichment in taurine ancestry may have originated from ancient African aurochs (B. primigenius africanus) introgression. They may have contributed to the local adaptation of African cattle to pathogen burdens. Our study provides further support and new evidence showing that the successful settlement of cattle across the continent was a complex mechanism involving adaptive introgression, mitochondrial DNA copy number variation, regulation of gene expression, and selection of ancestral mitochondria-related genes.
Spatiotemporal analysis of drought characteristics across multiple timescales in the upper Blue Nile basin, Ethiopia
Author(s): Alemu, Melkamu; Zaitchik, Benjamin; Enku, Temesgen; Abeyou, Abeyou; Yimer, Esifanos; Griensven, Ann (Springer (part of Springer Nature) (Springer Open Choice Hybrid Journals))
Date: 2025-07-29
Type: Journal Article
Status: Timeless limited access
In the context of climate change, in-depth analysis of the spatiotemporal characteristics, propagation dynamics, and influencing factors of droughts is critical for early warning and decision-making. However, such analyses are often constrained by a lack of sufficient in-situ hydro-meteorological data. This study addresses this gap by utilizing the Standardized Precipitation Index (SPI), Standardized Precipitation Evapotranspiration Index (SPEI), Standardized Soil Moisture Index (SSMI), and Gravity Recovery and Climate Experiment Drought Severity Index (GRACE-DSI) from remote sensing and reanalysis sources. We assessed meteorological, agricultural, and hydrological droughts in the Upper Blue Nile Basin (UBNB) using run theory to analyze key drought characteristics: events, duration, and severity from 1982 to 2023. The Granger causality test evaluated causal relationships between meteorological and agricultural/hydrological droughts, while the maximum Pearson correlation coefficient method identified the propagation times of droughts across various agroecological zones and land cover types. Additionally, hierarchical cluster analysis was conducted to pinpoint homogeneous drought regions. Results indicated that the UBNB experienced frequent droughts, with spatial variations in drought characteristics: drought duration and severity increased with longer timescales, while the number of drought events decreased. Causal relationships were confirmed between meteorological and agricultural/hydrological droughts, with a short propagation time of about 2 months from meteorological to agricultural drought, and approximately 12 months to hydrological drought. These propagation times varied by agroecological zones, being longer in croplands and highlands, and shorter in lowlands and tree-covered areas. Cluster analysis identified three distinct drought clusters in the UBNB, providing insights for targeted adaptation measures in drought-prone regions.
Advanced diagnostic strategies for the detection and identification of seed-borne viruses at ICARDA to enhance seed health security
Author(s): Kumari, Safaa; Moukahel, Abdulrahman (the Mediterranean Phytopathological Union, 2025-08-01)
Date: 2025-08-01
Type: Conference Paper
Status: Open access
ICARDA’s Seed Health Laboratory (ICARDA-SHL) is responsible for the monitoring, clearance, and documentation of the safe germplasm movement at the Center. The laboratory processes over 50,000 samples annually for seed-borne pathogens/pests, for the purpose of short- and long-term conservation and global distribution. This rigorous screening process is essential for preventing the spread of seed-borne pests across borders, especially viruses that can be transmitted further by insect vectors upon introduction. This has made the management of seed-borne viruses more challenging, as infected seeds can introduce the virus into new areas and lead to infections in subsequent growing seasons. Early detection and accurate diagnosis of viral diseases are critical for implementing effective control measures and strategies. In this context, ICARDA-SHL is actively engaged in the development, validation and dissemination of advanced diagnostic tools and protocols for germplasm health testing, facilitating technology transfer to NPPOs. Accordingly, ICARDA-SHL has developed and applied various molecular tests for the detection and identification of seed-borne legume viruses, including IC-RT-PCR, uniplex RT-PCR and multiplex RT-PCR in a single direct test. These advanced diagnostic techniques allow rapid analysis of large numbers of samples at a relatively low cost, high throughput, short execution times and enhanced accuracy, thus ensuring the availability of certified seeds, which are key strategies to mitigate the spread of seed-borne legume viruses that cannot be controlled by conventional plant treatments. In this presentation, validated molecular tools for the detection and identification of selected legume viruses (e.g. AMV, CMV, BYMV, PSbMV) applied by ICARDA-SHL will be described.
Management of major viral and fungal diseases affecting temperate food legume crops in the Arab and Mediterranean countries
Author(s): Kumari, Safaa; Kemal, Seid Ahmed (the Mediterranean Phytopathological Union, 2025-08-01)
Date: 2025-08-01
Type: Conference Paper
Status: Open access
The production, productivity and quality of temperate food legumes (faba bean, Kabuli chickpea, lentil, and field pea) are affected by several viral and fungal diseases in the Arab and Mediterranean countries. Surveys conducted over the past three decades have shown that the most important diseases affecting food legumes are wilt/root rot disease complex caused by Fusarium spp., Rhizoctonia and Pythium spp., and foliar diseases. In a few countries, parasitic nematodes (Heterodera and Pratylenchus spp.), and Ascochyta blights (Didymella spp.) are the major diseases of chickpea, faba bean and lentil, whereas faba bean suffers from chocolate spot (Botrytis fabae) and rust (Uromyces viciae-fabae). Viruses are emerging production constraints of food legumes where Faba bean necrotic yellows virus (FBNYV), Chickpea chlorotic stunt virus (CpCSV), Beet western yellows virus (BWYV), Bean yellow mosaic virus (BYMV), and Pea seed-borne mosaic virus (PSbMV) are the major ones. These viruses are affecting food legumes individually or as mixed infections. The importance of food legume viruses is mainly associated with increased in aphid activities due to changes in climate and cropping system in the regions. A positive linear correlation has been observed between virus prevalence and aphids that can transmit these viruses. The main aphid species in legume fields were Acyrthosiphon pisum (Harris), Aphis craccivora Koch. and Aphis fabae Scopoli. In addition, several wild species (annual or perennial) were found infected with these viruses and may play an important role in the spread of these viruses. In recent years, virus epidemics have been reported in some Arab countries (such as Egypt, Tunisia, Syria, and Jordan), sometimes causing considerable yield reduction. Significant progress has been made in managing fungal diseases by integrating two or more management options, such as development resistant varieties, production of healthy seeds, adjusting planting dates, seed treatments, selective use of fungicide sprays, and cultural practices that reduce the impact on food legume productivity and quality. Over the past two decades, faba bean genotypes resistant to FBNYV and BLRV, chickpea genotypes resistant to CpCSV and BWYV, and lentil genotypes resistant to FBNYV, BLRV and PSbMV have been successful identified. In addition, a relatively quick and simple plastic house technique was developed to identify resistant genotypes on the basis of relative virus movement and multiplication using Tissue blot immunoassay (TBIA). However, management options remain limited for emerging viruses, the emergence of virulent pathogens mainly for Ascochyta blight on chickpea, and complex soil-borne diseases caused by several parasitic pathogens and nematodes. Further efforts are still needed to develop varieties with multiple disease resistance, integrate new management options supported by digital innovations, establishing regional networks for food legume disease research for development, capacity development, and utilize modern tools, such as diagnostic tools, AI-based early warning and detection systems. Furthermore, more farmer-led participatory research for development is needed to effectively address the key plant health challenges arising from climate and farming systems changes facing food legume production systems in the Arab and Mediterranean countries which is leading to cereal monocropping.
Seeds of change: cultivating feminist leadership in the co-operatives of the MENA region
Author(s): Najjar, Dina; Ouesalti, Dorsaf; Ben Ghanem, Hajer; El Amil, Rola; Ait Hssain, Jihad; Nidkazza, Zakaria; Benrais, Brahim; Kallida, Rajae; Oussoulous, Nada (Taylor and Francis Group)
Date: 2025-09-18
Type: Journal Article
Status: Open access
This paper examines women’s leadership in local group governance in Morocco, Tunisia, and Lebanon, highlighting rural co-operatives as key spaces for socioeconomic participation and agency. Based on interviews and focus groups with a total of 917 participants (688 women and 170 men co-operative members, and 59 officials), the study identifies major barriers to women’s leadership, including financial limitations, lack of training, gender stereotypes, and exclusion from policy processes. Despite these obstacles, women-led co-operatives foster economic independence, collective agency, and more-inclusive governance. However, their impact is constrained by normative and policy environments where gender-sensitive governance remains weak. Using Morocco as a case study, the research evaluates targeted interventions – capacity strengthening, theatre forum, and governance workshops – that have enhanced women’s leadership and shifted local perceptions. The study calls for multi-level reforms to expand access to resources and training, challenge restrictive norms, and strengthen co-operation between co-operatives, authorities, and international actors. Empowering women’s grassroots leadership can catalyse broader sociopolitical transformation and advance gender equality across the Middle East and North Africa (MENA) region. Cet article examine le leadership des femmes dans la gouvernance des groupes locaux au Maroc, en Tunisie et au Liban. Il met en relief les coopératives rurales en tant qu'espaces clés pour la participation et l'action socio-économiques. Cette étude s'appuie sur des entretiens et des groupes de réflexion organisés avec un total de 917 participants (688 femmes et 170 hommes membres de coopératives, et 59 responsables) pour identifier les principaux obstacles au leadership des femmes, notamment les restrictions financières, le manque de formation, les stéréotypes de genre et l'exclusion des processus politiques. Malgré ces obstacles, les coopératives dirigées par des femmes favorisent l'indépendance économique, le libre arbitre collectif et une gouvernance plus inclusive. Cependant, leur impact est limité par des environnements normatifs et de politiques générales au sein desquels la gouvernance sensible au genre reste faible. En utilisant le Maroc comme étude de cas, cette étude évalue des interventions ciblées – renforcement des capacités, forum théâtral et ateliers de gouvernance – qui ont renforcé le leadership des femmes et modifié les perceptions locales. L'étude appelle à des réformes à plusieurs niveaux pour élargir l'accès aux ressources et à la formation, remettre en question les normes restrictives et renforcer la coopération entre les coopératives, les autorités et les acteurs internationaux. Le renforcement du leadership des femmes au niveau local peut catalyser une transformation sociopolitique plus large et faire progresser l'égalité des genres dans toute la région MENA. Este artículo examina el liderazgo de las mujeres en la gobernanza de grupos locales de Marruecos, Túnez y Líbano, destacando las cooperativas rurales como espacios fundamentales para su participación socioeconómica y su agencia. A partir de la realización de entrevistas y grupos focales con un total de 917 participantes (688 mujeres y 170 hombres miembros de cooperativas, además de 59 funcionarios), el estudio buscó identificar las principales barreras que obstaculizan que las mujeres ejerzan el liderazgo, entre ellas las limitaciones financieras, la falta de formación, los estereotipos de género y la exclusión de los procesos orientados a determinar políticas públicas. A pesar de estos obstáculos, se constató que las cooperativas dirigidas por mujeres fomentan la independencia económica, la agencia colectiva y una gobernanza más inclusiva. Sin embargo, su impacto se ve limitado por entornos normativos y políticos en los que la gobernanza sensible al género sigue siendo débil. Utilizando Marruecos como estudio de caso, la investigación evaluó ciertas intervenciones específicas —fortalecimiento de capacidades, foro de teatro y talleres de gobernanza— que potenciaron el liderazgo de las mujeres y modificaron las percepciones locales. El estudio hace un llamado a implementar reformas en varios niveles, para ampliar el acceso a recursos y formación, cuestionar las normas restrictivas y reforzar la colaboración entre cooperativas, autoridades y agentes internacionales. Potenciar el liderazgo de las mujeres de base puede catalizar una transformación sociopolítica más amplia y hacer avanzar la igualdad de género en toda la región de Oriente Medio y Norte de África (MENA).
Statistical and hydrological evaluation of remotely sensed rainfall products in the Upper Blue Nile basin, Ethiopia
Author(s): Alemu, Melkamu; Zaitchik, Benjamin; Enku, Temesgen; Abeyou, Abeyou; Yimer, Esifanos; Griensven, Ann (Springer (part of Springer Nature))
Date: 2025-01-22
Type: Journal Article
Status: Timeless limited access
Satellite-based rainfall products (SRPs) have a wide range of applications, but their accuracy and reliability need to be assessed. This study evaluated the performance of three SRPs: Climate Hazards Group InfraRed Precipitation with Stations (CHIRPS), the Integrated Multi-satellitE Retrieval for Global Precipitation Measurement (IMERG), and Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Climate Data Record (PERSIANN-CDR) over the Upper Blue Nile Basin (UBNB) on daily and monthly time scales by employing three distinct approaches. First, the evaluation was carried out by comparing the SRPs with rainfall measurements obtained from 25 rainfall gauging stations using statistical indicators. Following this, the Triple Collocation (TC) was applied. The study continued to investigate the hydrological utility of the SRPs at three selected watersheds in the basin using the GR4J (Génie Rural à 4 paramètres Journalier) hydrological model. Results indicated a statistically significant strong monthly correlation between SRPs and gauge observations, but a weak daily correlation. IMERG showed higher performance on a daily scale, while CHIRPS outperformed on a monthly scale based on statistical metrics. TC-based results also revealed the superior performance of IMERG on the daily scale, with SRPs’ performance declining from west to east and exhibiting higher performance at lower elevations. GR4J modeling results indicated SRPs’ potential for hydrological modeling applications, but challenges in simulating the high flow conditions were noted. Overall, the study underscores the critical role of SRPs in enhancing hydrological modeling, streamflow simulations, and water resource management for policy decision-making, especially in data-scarce regions. However, further research is needed to enhance the reliability and applicability of SRPs for more accurate generalization.
Molecular and Serological Detection of Toxoplasma gondii inTwo Species of Rodents: Ctenodactylus gundi (Rodentia,Ctenodactylidae) and Psammomys obesus (Rodentia,Muridae) From South Tunisia
Author(s): Bouaicha, Faten; Amairia, Safa; Amdouni, Yosra; Elati, Khawla; Ben Smida, Boubaker; Rekik, Mourad; Gharbi, Mohamed (Wiley Open Access, 2025-05-01)
Date: 2025-04-28
Type: Journal Article
Status: Open access
The molecular and serological prevalence of Toxoplasma gondii infection was investigated among rodents living in desertic areasin the Tataouine district, in the south of Tunisia. A total number of 43 rodents were captured from four sites classified as aridand Saharan climatic zones. Sera, hearts, spleens and brains were collected from each rodent. Sera were tested for the presence ofanti-T. gondii IgG by the ELISA technique. PCR was used to detect T. gondii DNA from different tissues. Two rodent species wereidentified as Ctenodactylus gundi (Rodentia, Ctenodactylidae) (N = 28; 65%) and Psammomys obesus (Rodentia, Muridae) (N = 15;35%). The overall molecular prevalence of T. gondii was 39% (17/43). Infection prevalences were higher in C. gundi (53.6%; 15/28)compared to P. obesus (13.3%; 2/15). In both species, the brain was the most infected organ (p = 0.02). No significant difference wasrecorded for the two rodent species according to gender and sampling sites (p > 0.05). The overall seroprevalence was up to 34.9%(15/43). It was higher in C. gundi (43%; 12/28) compared to P. obesus (20; 3/15) (p = 0.02). These results highlight a high infectionlevel of T. gondii in desertic rodents. More investigations are required to understand the role of other desertic mammals and toidentify the genotype circulating in the Tunisian Sahara.
Assessing the vulnerability of groundwater to pollution under different land management scenarios using the modified DRASTIC model in Bahir Dar City, Ethiopia
Author(s): Ashagrie, Wasie; Gashaw, Temesgen; Ray, Ram; Tefera, Gebrekidan Worku; Demessie, Sintayehu Fetene; Tsegaye, Lewoye; Adem, Anwar; Abeyou, Abeyou; R. van Oel, Pieter; Adgo, Enyew; Haileslassie, Amare; Dile, Yihun T; Mekonnen, Mulatie; Chukalla, Abebe Demissie (Elsevier (12 months), 2025-02-28)
Date: 2025-02-15
Type: Journal Article
Status: Open access
Groundwater is one of the most vital natural resources worldwide. However, shallow aquifers are prone to contamination, posing significant risks to human health, livestock, agricultural productivity, and economic growth. Identifying appropriate land management strategies is critical for mitigating groundwater vulnerability to pollution. This study evaluates groundwater vulnerability to pollution under various land management scenarios using the modified DRASTIC model in Bahir Dar City, Ethiopia. The analysis incorporates multiple parameters within the ArcGIS environment, including depth to water table, net recharge, aquifer characteristics, soil properties, topography, vadose zone, hydraulic conductivity, and land use/land cover (LULC). In this study, LULC was added as an additional parameter to enhance the DRASTIC model. Groundwater vulnerability to pollution was evaluated under four distinct land management scenarios: baseline, agricultural expansion, urbanization, and reforestation. A single-parameter sensitivity analysis and a map removal sensitivity analysis were performed to identify the most influential parameters affecting groundwater vulnerability under the baseline LULC conditions. The result revealed that groundwater vulnerability in Bahir Dar City under baseline conditions is primarily influenced by LULC and net recharge. The areal average groundwater vulnerability to pollution index at the baseline scenario was 184. Agricultural expansion and urbanization increased the areal average groundwater vulnerability to pollution by 4.9 % and 1.6 %, respectively, while the reforestation scenario reduced it by 1.6 %. These findings highlight the critical role of effective land management practices, such as reforestation, in mitigating groundwater susceptibility to pollution. The results also indicate that groundwater vulnerability to pollution varies across different geological formations. Therefore, given the influence of geological variability on groundwater vulnerability, incorporating geological considerations into urban expansion planning is essential for minimizing the risk of groundwater contamination.
Performances of reanalysis products in representing the temperature climatology of Ethiopia
Author(s): Tadesse, Tazebew; Gashaw, Temesgen; Ray, Ram; Tefera, Gebrekidan Worku; Demessie, Sintayehu Fetene; Shawul, Alemayehu; Abeyou, Abeyou; R. van Oel, Pieter; Dile, Yihun T; Chukalla, Abebe Demissie; Haileslassie, Amare; Aniley, Endeg; Tagele, Alehegn; Bantider, Amare (Springer (part of Springer Nature) (Springer Open Choice Hybrid Journals))
Date: 2025-01-06
Type: Journal Article
Status: Timeless limited access
Identifying the most reliable reanalysis temperature products is crucial for advancing hydro-climate research in data-scarce regions. This study evaluated two widely used reanalysis datasets in estimating minimum temperature (Tmin) and maximum temperature (Tmax) across various Agro-Ecological Zones (AEZs) of Ethiopia at different temporal scales over the period 1990 to 2020. These datasets include the Modern-Era Retrospective Analysis for Research and Applications, version 2.0 (MERRA v2.0) and the fifth generation of the European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis (ERA5). Evaluations was undertaken at each AEZs using five statistical metrics, scatter plots and line graphs by the data collected from 37 meteorological stations. The results indicate that MERRA v2.0 demonstrates superior performance in simulating Tmin across daily, monthly, and annual temporal scales in most AEZs, based on the majority or entirety of the evaluation metrics. For Tmax, MERRA v2.0 performs best on an annual scale, while ERA5 shows better performance on a daily scale. However, both reanalysis products exhibit comparable performance in estimating monthly Tmax. Notably, the performance of the reanalysis datasets varies across different AEZs. In general, the findings underscore the importance of selecting the most suitable reanalysis datasets for Tmin and Tmax separately, tailored to specific temporal scales and AEZs, to improve hydrology and/or climate studies in data scarce portions of the country.
Unlocking watershed mysteries: Innovative regionalization of hydrological model parameters in data-scarce regions
Author(s): Mihret, Temesgen; Zimale, Fasikaw A; Abeyou, Abeyou; D. Ayalew, Ayenew; Fohrer, Nicola (Elsevier (12 months), 2025-02-01)
Date: 2025-01-03
Type: Journal Article
Status: Open access
Study region The Upper Blue Nile Basin in Ethiopia, characterized by its complex hydrological system, is the focus of this study. The basin includes 76 gauged watersheds, which were analyzed to estimate parameters for ungauged locations using regionalization techniques. Study focus Regression-Based Approach (RBA), Physical Similarity Approach (PSA), and Spatial Proximity Approach (SPA), for estimating GR4J model parameters. A 25 km by 25 km fishnet-based grid was implemented to enable parameter prediction for ungauged watersheds. Principal Component Analysis (PCA) and k-means clustering were used to group gauged watersheds into three homogeneous clusters, with Beressa, Dedessa, and Gilgel Abay selected as pseudo-watersheds for validation. Model performance was evaluated using PBIAS, R², and NSE metrics. New hydrological insights for the region The RBA outperformed PSA and SPA in parameter transfer, achieving R² values of 0.57, 0.79, and 0.67; PBIAS values of 7.3, −1.5, and 2.6; and NSE values of 0.58, 0.78, and 0.67 for Beressa, Dedessa, and Gilgel Abay, respectively. Incorporating grid-based parameter values further improved model performance, with NSE values of 0.81 for Dedessa, 0.63 for Beressa, and 0.61 for Gilgel Abay. These findings highlight the effectiveness of the grid-based regionalization approach for accurate streamflow prediction in ungauged watersheds within the Upper Blue Nile Basin.
Random regression in comparison with finite-dimensional models for estimation of genetic parameters for growth traits in goats
Author(s): Tesema, Zeleke; Derbie, Belay; Getachew, Tesfaye; Meseret, Selam; Gizaw, Solomon (Springer)
Date: 2025-03-15
Type: Journal Article
Status: Timeless limited access
The application of the random regression model in comparison with finite-dimensional models (univariate and multivariate animal models) for genetic parameter estimation of growth traits in goats was evaluated in this study. A total of 2888 body weight records from 875 animals, recorded from birth to yearling age were used. All models included direct additive genetic and maternal genetic effects as a random effect in addition to fixed effects. Random regression model (RRM) was fitted with different orders (1st – 3rd) of Legendre polynomials and accounted for both homogeneous and heterogeneous residual variance. The best-fitting RRM had a polynomial of three orders for both random effects. The direct heritability estimate obtained via RRM was moderate to high, while it varied from 0.00 ± 0.08 to 0.36 ± 0.10 in finite dimensional models. A lower standard error of heritability and genetic correlation estimates was observed with RRM compared to multivariate (MUV) and univariate (UNI) analysis. Likewise, high accuracy and reliability of breeding value estimates are obtained via RRM, whereas the accuracy for MUV and UNI animal models were moderate and low to moderate, respectively. Based on standard errors, accuracy, and reliability of estimates, RRM seems versatile for genetic evaluation of growth traits of goats. However, the MUV animal model is the best-fitting model, according to the information criteria values. Thus, for small and less frequently measured data set, multivariate animal model seems good. Further studies with large and frequently measured body weight data sets may help ensure random regression’s applicability and differentiate it from finite-dimensional models.
Leveraging ML to predict climate change impact on rice crop disease in Eastern India
Author(s): Sahoo, Satiprasad; Singha, Chiranjit; Govind, Ajit; Mamta, Sharma (Springer (part of Springer Nature) (Springer Open Choice Hybrid Journals))
Date: 2025-03-08
Type: Journal Article
Status: Timeless limited access
Rice crop disease is critical in precision agriculture due to various influencing components and unstable environments. The current study uses machine learning (ML) models to predict rice crop disease in Eastern India based on biophysical factors for current and future scenarios. The nine biophysical parameters are precipitation (Pr), maximum temperature (Tmax), minimum temperature (Tmin), soil texture (ST), available water capacity (AWC), normalized difference vegetation index (NDVI), soil-adjusted vegetation index (SAVI), normalized difference chlorophyll index (NDCI), and normalized difference moisture index (NDMI) by Random forest (RF), Gradient Boosting Machine (GBM), Extreme Gradient Boosting (XGB), Artificial Neural Net (ANN), and Support vector Machine (SVM). The multicollinearity test Boruta feature selection techniques that assessed interdependency and prioritized the factors impacting crop disease. However, climatic change scenarios were created using the most recent Climate Coupled Model Intercomparison Project Phase 6 (CMIP6) Shared Socioeconomic Pathways (SSP) 2–4.5 and SSP5-8.5 datasets. The rice crop disease validation was accomplished using 1105 field-based farmer observation recordings. According to the current findings, Purba Bardhaman district experienced a 96.72% spread of rice brown spot disease due to weather conditions. In contrast, rice blast diseases are prevalent in the north-western region of Birbhum district, affecting 72.38% of rice plants due to high temperatures, water deficits, and low soil moisture. Rice tungro disease affects 63.45% of the rice plants in Bankura district due to nitrogen and zinc deficiencies. It was discovered that the link between NDMI and NDVI is robust and positive, with values ranging from 0.8 to 1. According to SHAP analysis, Pr, Tmin, and Tmax are the top three climatic variables impacting all types of disease cases. The study’s findings could have a substantial impact on precision crop protection and meeting the United Nations Sustainable Development Goals.
Review of aquifer storage and recovery opportunities and challenges in India
Author(s): Sahoo, Satiprasad; Singha, Chiranjit; Govind, Ajit; Sharma, Prabhakar (Springer (part of Springer Nature), 2025-02-18)
Date: 2025-02-18
Type: Journal Article
Status: Timeless limited access
Managing groundwater is a global challenge as offer rises across agriculture, industry, and energy sectors, while climate change, population explosion, industrialization, and urbanization leads to a decline in surface water resources. Managed aquifer recharge (MAR) is one solution that can enhance long-term water sustainability by increasing the natural replenishment of groundwater supplies through the use of non-traditional water sources. India, as the largest groundwater user, is mitigating over-extraction through MAR initiatives. However, Aquifer Storage and Recovery (ASR) provides a site-specific solution for maintaining a sustainable water supply. This approach targets densely populated regions in the Indian subcontinent, particularly those undergoing agricultural transitions, heavily dependent on groundwater for irrigation and domestic use, and facing water shortages in both ground and surface water supplies. The global land data assimilation systems (GLDAS) of 2003–2023 revealed significant groundwater and total water storage depletion in north-western India, with negative trends between − 27.816 and − 21.186 mm/year. These findings emphasize the urgent need to implement MAR systems in the Western Dry Region, Western Himalayas, and Gangetic Plains to ensure sustainable agricultural planning and management. Thus, the review paper emphasizes the potential of MAR and ASR techniques to meet both current and future demands for high-quality water while addressing the rising need for groundwater. In particular, ASR can tackle issues related to water stress, manage wastewater, alleviate flooding, prevent saltwater intrusion, lessen land subsidence, safeguard crops from damage, avert aquifer depletion, and enhance water quality. The review also discusses the significance of ASR-related groundwater resource projects in India, especially in the context of changing climatic conditions. At last, we explored ASR’s types, challenges, benefits, limitations, and recommendations for sustainable groundwater management. ASR is seen as a viable solution in India to improve water resource policies amid climate change, addressing water rights, public health, and environmental issues. These insights can help identify optimal sites in water-scarce regions of India for the deployment of specific ASR approaches aimed at enhancing water sustainability.
Exploring Nitrogen Use Efficiency in Cereals: Insight into Traits, Metabolism, and Management Strategies Under Climate Change Conditions – A Comprehensive Review
Author(s): Ben Debbane, Fatima Zahra; Baidani, Aziz; Aarbaoui, Maria; Moussadek, Rachid; Mrabet, Rachid; Amamou, Ali (Springer (part of Springer Nature), 2025-03-21)
Date: 2025-03-21
Type: Journal Article
Status: Timeless limited access
Nitrogen (N) is an essential element for cereals growth and development, playing a crucial role in productivity and yield. Consequently, nitrogen fertilizers are extensively used in cereal cultivation. However, the excessive fertilizer application has led to significant environmental challenges, including nitrate leaching, greenhouse gas emissions coupled, and rising production costs due to increasing fertilizer prices. Additionally, has contributed to declining grain quality through reduced Nitrogen Use Efficiency (NUE). Enhancing NUE is crucial to address these issues, requiring comprehension understanding of its components and the physiological mechanisms governing nitrogen uptake, assimilation, and remobilization. This review synthesizes existing literature on NUE components and their influence on NUE variation. It explores nitrogen pathways in plants, interactions with soil properties, and the impact of root architecture and carbon–nitrogen metabolism. The review also highlights practical strategies for enhancing NUE, including agronomic innovations such as precision fertilization and irrigation, remote sensing, and site-specific management, and physiological approaches. Furthermore, emerging high-throughput tools, including remote sensing technologies and precision agriculture, are discussed. Given the challenges posed by climate change, such as heat stress, elevated CO₂ levels, and unpredictable rainfall, developing nitrogen-efficient cereals is essential for insuring sustainability, productivity, and global food security. This review underscores the need for integrated strategies that advanced research, agronomic techniques, and technological innovation. Additionally, limited progress has been made in integrating cutting-edge genetic tools, such as Omics and CRISPR technologies, with a deeper understanding of the complex interaction between genetic and environmental factors to enhance NUE of cereal crops.
Application of Compost as an Organic Amendment for Enhancing Soil Quality and Sweet Basil (Ocimum basilicum L.) Growth: Agronomic and Ecotoxicological Evaluation
Author(s): Lhaj, Majda Oueld; Moussadek, Rachid; Mouhir, Latifa; Sanad, Hatim; Manhou, Khadija; Iben Halima, Oumaima; Yachou, Hasna; Zouahri, Abdelmjid; Mdarhri Alaoui, Meriem (MDPI, 2025-04-26)
Date: 2025-04-26
Type: Journal Article
Status: Open access
This study investigates the effectiveness of organic compost as a sustainable alternative to chemical fertilizers for improving soil health and enhancing crop productivity under greenhouse conditions. The experiment focused on sweet basil (Ocimum basilicum L.), an aromatic herb highly sensitive to soil fertility and structure, cultivated in sandy loam soil—a prevalent substrate in arid and semi-arid regions, often limited by poor water and nutrient retention. Using a randomized complete block design with six compost application rates, this study evaluated the physicochemical, biochemical, and agronomic responses of both soil and plants. The results demonstrated significant improvements across all parameters (p < 0.05), with the 30 t/ha compost treatment yielding the most notable enhancements in soil structure, nutrient content, and plant performance while maintaining acceptable levels of heavy metals. Soil organic matter (SOM) increased to 13.71%, while shoot length (SL), essential oil content (EOC), and the 100-seed weight improved to 42 cm, 0.83%, and 0.32 g, respectively, compared to the control. These finding underscore the benefits of high compost application rates in boosting greenhouse horticultural productivity while promoting sustainable agriculture. Moreover, this study supports the reduction in chemical fertilizer dependency and encourages the adoption of circular economy principles (CEPs) through organic waste recycling.
Advancing flood risk assessment: Multitemporal SAR-based flood inventory generation using transfer learning and hybrid fuzzy-AHP-machine learning for flood susceptibility mapping in the Mahananda River Basin
Author(s): Singha, Chiranjit; Sahoo, Satiprasad; Mahtaj, Alireza Bahrami; Moghimi, Armin; Welzel, Mario; Govind, Ajit (Elsevier (12 months), 2025-04-01)
Date: 2025-03-22
Type: Journal Article
Status: Open access
The Mahananda River basin, located in Eastern India, faces escalating flood risks due to its complex hydrology and geomorphology, threatening socioeconomic and environmental stability. This study presents a novel approach to flood susceptibility (FS) mapping and updates the region's flood inventory. Multitemporal Sentinel-1 (S1) SAR images (2020–2022) were processed using a U-Net transfer learning model to generate a water body frequency map, which was integrated with the Global Flood Dataset (2000–2018) and refined through grid-based classification to create an updated flood inventory. Eleven geospatial layers, including elevation, slope, soil moisture, precipitation, soil type, NDVI, Land Use Land Cover (LULC), geomorphology, wind speed, drainage density, and runoff, were used as flood conditioning factors (FCFs) to develop a hybrid FS mapping approach. This approach integrates the Fuzzy Analytic Hierarchy Process (FuzzyAHP) with six machine learning (ML) algorithms to create hybrid models FuzzyAHP-RF, FuzzyAHP-XGB, FuzzyAHP-GBM, FuzzyAHP-avNNet, FuzzyAHP-AdaBoost, and FuzzyAHP-PLS. Future flood trends (1990–2030) were projected using CMIP6 data under SSP2-4.5 and SSP5-8.5 scenarios with MIROC6 and EC-Earth3 ensembles. The SHAP algorithm identified LULC, NDVI, and soil type as the most influential FCFs, contributing over 60 % to flood susceptibility. Results show that 31.10 % of the basin is highly susceptible to flooding, with the western regions at greatest risk due to low elevation and high drainage density. Future projections indicate that 30.69 % of the area will remain highly vulnerable, with a slight increase under SSP5-8.5. Among the models, FuzzyAHP-XGB achieved the highest accuracy (AUC = 0.970), outperforming FuzzyAHP-GBM (AUC = 0.968) and FuzzyAHP-RF (AUC = 0.965). The experimental results showed that the proposed approach can provide a spatially well-distributed flood inventory derived from freely available remote sensing (RS) datasets and a robust framework for long-term flood risk assessment using hybrid ML techniques. These findings offer critical insights for improving flood risk management and mitigation strategies in the Mahananda River basin.

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