Agricultural Research Knowledge
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- Anthropogenic events and responses to environmental stress are shaping the genomes of Ethiopian indigenous goatsAuthor(s): Belay, Shumuye; Belay, Gurja; Nigussie, Helen; Ahbara, Abulgasim; Tijjani, Abdulfatai; Dessie, Tadelle; Tarekegn, Getinet; Jianlin, Han; Mor, Siobhan; Woldekiros, Helina S.; Dobney, Keith; Lebrasseur, Ophelie; Hanotte, Olivier; Mwacharo, Joram (Nature Research (part of Springer Nature) (Fully open access journals))Date: 2024-06-28Type: Journal ArticleStatus: Open accessAnthropological and biophysical processes have shaped livestock genomes over Millenia and can explain their current geographic distribution and genetic divergence. We analyzed 57 Ethiopian indigenous domestic goat genomes alongside 67 equivalents of east, west, and north-west African, European, South Asian, Middle East, and wild Bezoar goats. Cluster, ADMIXTURE (K = 4) and phylogenetic analysis revealed four genetic groups comprising African, European, South Asian, and wild Bezoar goats. The Middle Eastern goats had an admixed genome of these four genetic groups. At K = 5, the West African Dwarf and Moroccan goats were separated from East African goats demonstrating a likely historical legacy of goat arrival and dispersal into Africa via the coastal Mediterranean Sea and the Horn of Africa. FST, XP-EHH, and Hp analysis revealed signatures of selection in Ethiopian goats overlaying genes for thermo-sensitivity, oxidative stress response, high-altitude hypoxic adaptation, reproductive fitness, pathogen defence, immunity, pigmentation, DNA repair, modulation of renal function and integrated fluid and electrolyte homeostasis. Notable examples include TRPV1 (a nociception gene); PTPMT1 (a critical hypoxia survival gene); RETREG (a regulator of reticulophagy during starvation), and WNK4 (a molecular switch for osmoregulation). These results suggest that human-mediated translocations and adaptation to contrasting environments are shaping indigenous African goat genomes.
- Whole-genome resource sequences of 57 indigenous Ethiopian goatsAuthor(s): Belay, Shumuye; Belay, Gurja; Nigussie, Helen; Jianlin, Han; Tijjani, Abdulfatai; Ahbara, Abulgasim; Tarekegn, Getinet; Woldekiros, Helina S.; Mor, Siobhan; Dobney, Keith; Lebrasseur, Ophelie; Hanotte, Olivier; Mwacharo, Joram (NATURE RESEARCH)Date: 2024-01-29Type: Journal ArticleStatus: Open accessDomestic goats are distributed worldwide, with approximately 35% of the one billion world goat population occurring in Africa. Ethiopia has 52.5 million goats, ~99.9% of which are considered indigenous landraces deriving from animals introduced to the Horn of Africa in the distant past by nomadic herders. They have continued to be managed by smallholder farmers and semi-mobile pastoralists throughout the region. We report here 57 goat genomes from 12 Ethiopian goat populations sampled from different agro-climates. The data were generated through sequencing DNA samples on the Illumina NovaSeq 6000 platform at a mean depth of 9.71x and 150 bp pair-end reads. In total, ~2 terabytes of raw data were generated, and 99.8% of the clean reads mapped successfully against the goat reference genome assembly at a coverage of 99.6%. About 24.76 million SNPs were generated. These SNPs can be used to study the population structure and genome dynamics of goats at the country, regional, and global levels to shed light on the species’ evolutionary trajectory.
- Organic dry pea (Pisum sativum L.): A sustainable alternative pulse-based protein for human healthAuthor(s): Thavarajah, Dil; Lawrence, Tristan J.; Boatwright, Jon Lucas; Windsor, Nathan; Johnson, Nathan; Kay, Joshua; Shipe, Emerson; Agrawal, Shiv Kumar; Thavarajah, Pushparajah (Public Library of Science)Date: 2024-04-12Type: Journal ArticleStatus: Open accessDry pea (Pisum sativum L.) is a cool-season food legume rich in protein (20–25%). With increasing health and ecosystem awareness, organic plant-based protein demand has increased; however, the protein quality of organic dry pea has not been well studied. This study determined the genetic variation of individual amino acids (AAs), total AAs (liberated), total protein, and in vitro protein digestibility of commercial dry pea cultivars grown in organic on-farm fields to inform the development of protein-biofortified cultivars. Twenty-five dry pea cultivars were grown in two USDA-certified organic on-farm locations in South Carolina (SC), USA, for two years (two locations in 2019 and one in 2020). The concentrations of most individual AAs (15 of 17) and the total AA concentration significantly varied with dry pea cultivar. In vitro protein digestibility was not affected by the cultivar. Seed total AA and protein for dry pea ranged from 11.8 to 22.2 and 12.6 to 27.6 g/100 g, respectively, with heritability estimates of 0.19 to 0.25. In vitro protein digestibility and protein digestibility corrected AA score (PDCAAS) ranged from 83 to 95% and 0.18 to 0.64, respectively. Heritability estimates for individual AAs ranged from 0.08 to 0.42; principal component (PCA) analysis showed five significant AA clusters. Cultivar Fiddle had significantly higher total AA (19.6 g/100 g) and digestibility (88.5%) than all other cultivars. CDC Amarillo and Jetset were significantly higher in cystine (Cys), and CDC Inca and CDC Striker were significantly higher in methionine (Met) than other cultivars; CDC Spectrum was the best option in terms of high levels of both Cys and Met. Lysine (Lys) concentration did not vary with cultivar. A 100 g serving of organic dry pea provides a significant portion of the recommended daily allowance of six essential AAs (14–189%) and daily protein (22–48%) for an average adult weighing 72 kg. Overall, this study shows organic dry pea has excellent protein quality, significant amounts of sulfur-containing AAs and Lys, and good protein digestibility, and thus has good potential for future plant-based food production. Further genetic studies are warranted with genetically diverse panels to identify candidate genes and target parents to develop nutritionally superior cultivars for organic protein production.
- Targeted improvement of plant-based protein: Genome-wide association mapping of a lentil (Lens culinaris Medik.) diversity panelAuthor(s): Johnson, Nathan; Boatwright, Jon Lucas; Bridges, William; Thavarajah, Pushparajah; Agrawal, Shiv Kumar; Thavarajah, Dil (Wiley Open Access)Date: 2023-12-14Type: Journal ArticleStatus: Open accessThe world is increasingly looking to plant-based sources to meet its protein needs.Multiple factors are driving this progression, ranging from nutritional and ethical con-siderations to climate change and population growth. As a pulse crop, lentil is ideal tohelp meet this change in demand. However, plant-based proteins have limiting aminoacids and lower protein digestibility compared to animal-based proteins. Thisresearch identifies genetic markers that can be used to accelerate breeding of proteinquality traits in lentil to ultimately help meet the rising demand in high-quality plant-based protein and bolster global food and nutritional security.Summary• Lentil (Lens culinaris Medik.) contains 25% high-quality protein in addition to highconcentrations of prebiotic carbohydrates and micronutrients, such as folate, iron,zinc, and selenium. As animal-based protein's economic and environmental costsrise, plant-based protein sources, such as lentil, will become increasingly importantto global food systems. Consequently, evaluating and targeting protein quality traitsfor genomic-assisted breeding is a valuable objective for lentil breeding programs.• A diversity panel of 183 breeding lines was analyzed for protein quality traits, includ-ing amino acids and protein digestibility. Genotyping-by-sequencing (GBS) data wereused to assess population structure and conduct genome-wide association studies(GWAS). Genes in local linkage disequilibrium (LD) with significant single nucleotidepolymorphism (SNP) markers were identified and categorized by homology.• Protein quality traits showed a wide range of variation. Repeatability estimateswere low to moderate across traits. Twelve traits were strongly correlated witheach other (r > .7). Admixture analysis identified six ancestral subpopulations,which also demonstrated clustering in principal component analysis. Ten differenttraits had significant SNP associations; two loci were shared across multiple traits.Twenty-seven candidate genes, including glutathione S-transferase, protease fam-ily, and gibberellin 2-beta-dioxygenase genes, were identified.
- Genome wide association study of seedling and adult plant leaf rust resistance in two subsets of barley genetic resourcesAuthor(s): Amouzoune, Mariam; Rehman, Sajid; Benkirane, Rachid; Udupa, Sripada M.; Mamidi, Sujan; Kehel, Zakaria; Al-Jaboobi, Muamer; Amri, Ahmed (Nature Research (part of Springer Nature) (Fully open access journals))Date: 2024-07-04Type: Journal ArticleStatus: Open accessLeaf rust (LR) caused by Puccinia hordei is a serious disease of barley worldwide, causing significant yield losses and reduced grain quality. Discovery and incorporation of new sources of resistance from gene bank accessions into barley breeding programs is essential for the development of leaf rust resistant varieties. To identify Quantitative Trait Loci (QTL) conferring LR resistance in the two barley subsets, the Generation Challenge Program (GCP) reference set of 142 accessions and the leaf rust subset constructed using the Focused Identification of Germplasm Strategy (FIGS) of 76 barley accessions, were genotyped to conduct a genome-wide association study (GWAS). The results revealed a total of 59 QTL in the 218 accessions phenotyped against barley leaf rust at the seedling stage using two P. hordei isolates (ISO-SAT and ISO-MRC), and at the adult plant stage in four environments in Morocco. Out of these 59 QTL, 10 QTL were associated with the seedling resistance (SR) and 49 QTL were associated with the adult plant resistance (APR). Four QTL showed stable effects in at least two environments for APR, whereas two common QTL associated with SR and APR were detected on chromosomes 2H and 7H. Furthermore, 39 QTL identified in this study were potentially novel. Interestingly, the sequences of 27 SNP markers encoded the candidate genes (CGs) with predicted protein functions in plant disease resistance. These results will provide new perspectives on the diversity of leaf rust resistance loci for fine mapping, isolation of resistance genes, and for marker-assisted selection for the LR resistance in barley breeding programs worldwide.
- Identification of suitable genotypes of lentil (Lens culinaris) for improved adaptation to rice fallow areas of Gangetic Alluvial ZoneAuthor(s): Chatterjee, Shayree; Das, Arpita; Bhattacharya, Sudip; Banerjee, Joydeep; Gupta, Sanjeev; Agrawal, Shiv Kumar (Indian Council of Agricultural Research (ICAR))Date: 2023-08-30Type: Journal ArticleStatus: Open accessRice fallows (RF) are the low lying kharif sown rice (Oryza sativa L.) areas that remain uncropped due to dearth of suitable cultivars of winter (rabi) pulses. A panel of 30 promising high yielding lentil (Lens culinaris Medik.) genotypes of diverse origin were assessed at both no till RF and with till condition at the Regional Research Substation (RRSS), Chakdah under the aegis of Bidhan Chandra Krishi Viswavidyalaya, Nadia, West Bengal for two years (2019–20 and 2020–21). Multi-trait performance (earliness, biomass and grain yield) of each genotype was considered during recommendation of suitable genotype for specific ecology deploying GGE biplot. The present study recommended IC 560183 for no till RF ecology and Moitree, IC 559996, ILL 7978 and L 1112-19 for with till ecology having specific adaptation. Additionally, 2011S-56212-2 and ILL 8006 were identified as ideal and desirable genotypes for both the ecologies and therefore, recommended for commercial cultivation across the areas of Gangetic alluvial zone for augmenting lentil production and productivity.
- Assessing pastoral reforms through the performance of Agro-Pastoral Community-Based Organizations in south TunisiaAuthor(s): Sghaier, Mariem; Frija, Aymen; Postigo, Julio; Speelman, Stijn; Alary, Veronique; Sghaier, Mongi (Elsevier)Date: 2024-09-02Type: Journal ArticleStatus: Timeless limited accessPastoralism is one of the most important agricultural production systems in drylands worldwide. It plays an important role in both the economy and the cycle of ecosystem goods and services. However, it is vulnerable to climatic challenges such as prolonged drought and socioeconomic pressures such as administrative shortcomings and ineffective governance. Under neoliberal influence, political and economic reforms have been implemented over the last 30 years to address these threats. These reforms have promoted local institutions for rangeland management and agro-pastoral development. In this paper, we assess the impact of these reforms on pastoral devolvement and Community-based natural resource management (CBNRM) by analyzing the performance of agro-pastoral community-based organizations CBOs in the province of Médenine (south-eastern Tunisia). We use a two-step methodology, with the first step focusing on a quantitative typology analysis of the performance of 31 CBOs. In a subsequent qualitative step, data from semi-structured interviews with 21 CBO chairpersons were used to identify the drivers of CBO performance. Results show that only 10% of the CBOs studied are able to move towards autonomy and proper integration into local and regional institutional networks and development dynamics. About 42% of the CBOs need further support and are in a precarious situation as they are dependent on public support. The remaining 48% have a low growth potential and in the early stages of consolidation. The qualitative analysis suggests that these shortcomings are mainly related to the CBOs' lack of networking skills. In addition, CBOs should improve their reputation and gain more trust from pastoral communities. Our findings suggest that well-functioning institutions do contribute to rural development; however, the design of pastoralist policy and institutional reforms should include long-term complementary support for the institutions created and consideration of the pastoralist community and regional contexts in order to achieve long-lasting transformative outcomes.
- ICARDA/UNDP Workshop: Increasing the Effectiveness of Water and Nitrogen in Rainfed Farming Systems in Mediterranean-Type EnvironmentsAuthor(s): (ICARDA), International Center for Agricultural Research in the Dry Areas (International Center for Agricultural Research in the Dry Areas (ICARDA), 1980-12-31)Date: 1980-12-31Type: Conference ProceedingsStatus: Timeless limited accessThis document contains the recommendations and summaries of discussions from the ICARDA/UNDP Workshop on Increasing the Effectiveness of Water and Nitrogen in Rainfed Farming Systems in Mediterranean-Type Environments. The workshop took place in Aleppo, Syria from January 13-18, 1980.
- Spatio-temporal microbial regulation of aggregate-associated priming effects under contrasting tillage practicesAuthor(s): Zhang, Yeye; Ren, Yunfei; Zhou, Shenglin; Ning, Xiaoyu; Wang, Xiu‐Kang; Yang, Yanming; Sun, Shikun; Nangia, Vinay; Bahn, Michael; Han, Juan; Liu, Yang; Xiong, You‐Cai; Liao, Yuncheng; Mo, Fei (Elsevier (12 months), 2024-05-15)Date: 2024-03-21Type: Journal ArticleStatus: Timeless limited accessTillage intensity significantly influences the heterogeneous distribution and dynamic changes of soil microorganisms, consequently shaping spatio-temporal patterns of SOC decomposition. However, little is known about the microbial mechanisms by which tillage intensity regulates the priming effect (PE) dynamics in heterogeneous spatial environments such as aggregates. Herein, a microcosm experiment was established by adding 13C-labeled straw residue to three distinct aggregate-size classes (i.e., mega-, macro-, and micro-aggregates) from two long-term contrasting tillage histories (no-till [NT] and conventional plow tillage [CT]) for 160 days to observe the spatio-temporal variations in PE. Metagenomic sequencing and Fourier transform mid-infrared techniques were used to assess the relative importance of C-degrading functional genes, microbial community succession, and SOC chemical composition in the aggregate-associated PE dynamics during straw decomposition. Spatially, straw addition induced a positive PE for all aggregates, with stronger PE occurring in larger aggregates, especially in CT soil compared to NT soil. Larger aggregates have more unique microbial communities enriched in genes for simple C degradation (e.g., E5.1.3.6, E2.4.1.7, pmm-pgm, and KduD in Nitrosospeera and Burkholderia), contributing to the higher short-term PE; however, CT soils harbored more genes for complex C degradation (e.g., TSTA3, fcl, pmm-pgm, and K06871 in Gammaproteobacteria and Phycicoccus), supporting a stronger long-term PE. Temporally, soil aggregates played a significant role in the early-stage PEs (i.e., < 59 days after residue addition) through co-metabolism and nitrogen (N) mining, as evidenced by the increased microbial biomass C and dissolved organic C (DOC) and reduced inorganic N with increasing aggregate-size class. At a later stage, however, the legacy effect of tillage histories controlled the PEs via microbial stoichiometry decomposition, as suggested by the higher DOC-to-inorganic N and DOC-to-available P stoichiometries in CT than NT. Our study underscores the importance of incorporating both spatial and temporal microbial dynamics for a comprehensive understanding of the mechanisms underlying SOC priming, especially in the context of long-term contrasting tillage practices.
- Advantageous spike-to-stem competition for assimilates contributes to the reduction in grain number loss in wheat spikes under water deficit stressAuthor(s): Li, Juan; Liang, Zimeng; Li, Yakun; Wang, Kexin; Nangia, Vinay; Mo, Fei; Liu, Yang (Elsevier Masson, 2024-03-01)Date: 2024-01-13Type: Journal ArticleStatus: Open accessThis study was conducted to investigate the mechanisms of assimilate distribution and sugar metabolism in spike-stem that inhibit the formation of fertile florets and grains per spike in winter wheat under pre-reproductive drought stress. Two winter wheat cultivars, CH58 (relatively strongly drought tolerant) and LH6 (relatively weakly drought tolerant), were subjected to successive soil drought treatments from jointing to heading during the 2020–2022 growing seasons. The results showed that pre-reproductive drought stress intensified the degradation and abortion of wheat florets. Compared to CH58, the decrease in the number of fertile florets and grains per spike of LH6 under drought stress increased by an average of 5.3%−8.0% and 8.3%−9.0%, respectively. Drought significantly inhibited the distribution of 13C-photosynthates in wheat spikes (15.7%−24.7%) and stems (8.5%−11.7%) during the booting stage. The number of differentially expressed genes enriched in starch and sucrose metabolic pathways was much higher in the spike and stem of LH6 than in those of CH58. Drought significantly reduced sucrose and hexose in young spikes but increased hexose and fructan concentrations in stems. Compared to LH6, the higher invertase activity and accompanying high expression of sugar transporter protein (STP) in CH58 spikes under drought stress contributed to the utilization of sucrose in young spikes. Additionally, under severe drought, the higher fructan concentration and expression of sugar transport proteins (SWEET and SUT) in the stem of CH58 improved the ability of the stem to transport assimilates to young spikes and thus alleviated the loss of grain number per spike. Exogenous spermidine optimized hexose and sucrose allocation in young wheat spikes and stems after drought stress, thereby increasing the number of fertile florets under drought stress. Overall, the ability of the dominant spike to utilize sugar and the ability to compete for assimilates between the spike and stem contribute to the resistance to drought stress-induced grain reduction in the spike. Exogenous chemicals can regulate the number of fertile florets through this pathway, thereby promoting the formation of wheat grain number.
- Understanding Agency Within Context: The Case of Breeding Cooperatives Program for Transforming Small Ruminant Value Chain in EthiopiaAuthor(s): Kinati, Wole; Temple, Elizabeth C.; Baker, A. Derek; Najjar, Dina; Hailu, Reta (SAGE Publications (UK and US))Date: 2024-04-22Type: Journal ArticleStatus: Open accessThe role of agency in women’s empowerment, whether individual or collective, has long been at the center of feminist discourse. Although, highly context dependent, studies on agency are less contextualized. Based on mixed methods, we generated in-depth understandings of what constitutes agency in livestock-based institutions, and associated contextual factors across three regions. Agency, the ability to make effective participation, conceptualization is based on four main dimensions, in turn associated with key agency enabling resources. The agency-enabling resources such as years of schooling, land holding, sheep flock size, number of women in the leadership committee, along with location and distance to extension services variables were associated with the ability to effectively participate. Study participants are aware of the influence of normative environment but lack the power to challenge it. If supported and used as a means, the collective action, breeding cooperative, itself could potentially generate its members such power.
- Prediction of pulse suitability in rice fallow areas using fuzzy AHP-based machine learning methods in Eastern IndiaAuthor(s): Sahoo, Satiprasad; Singha, Chiranjit; Govind, Ajit (Springer (part of Springer Nature), 2024-07-01)Date: 2024-03-08Type: Journal ArticleStatus: Timeless limited accessIn Eastern India, a widespread practice known as “rice fallow pulse” (RFP) involves using the soil’s remaining moisture to grow a short-duration pulse crop. For rainfed systems, it is an excellent practice of climate adaptation. To help farmers make informed decisions about where to plant what and to help policymakers create favorable conditions for timely seed distribution, it is imperative to forecast the appropriateness of pulse crops both geographically and temporally. Using fuzzy AHP (FAHP)-based machine learning methods, we tried to detect pulse appropriateness both geographically and temporally while considering fifteen natural, climatic, environment, and soil health-related characteristics in the Western Lateritic Zone of the Indian State of West Bengal. According to the findings, all machine learning (ML) techniques identified high-suitability zones in the districts of Murshidabad, Birbhum, Paschim Bardhaman, Paschim Medinipur, and Jhargram. By using machine learning techniques such as shrinkage discriminant analysis (SDA), neural network (nnet), random forest (RF), Naive Bayes (NB), rule-based C5.0, genetic algorithm (GA), and particle swarm optimization (PSO), it was found that moderate suitability zones were visible in some areas of Murshidabad, Birbhum, Paschim Bardhaman, Paschim Medinipur, and Purulia. Additionally, it was noted that all ML approaches revealed maximum low suitability zones in certain areas of Birbhum, Bankura, Purba Bardhaman, Purulia, and Murshidabad. Finally, district-level yearly pulse yields of minor, chickpea, and pigeonpea verified the precision of the ML-based models. We have devised a structure to assess pulse suitability analysis to improve crop and land productivity. One of the world’s most populous regions can use the data to inform policy decisions that will improve food and nutritional security in the face of shifting economic and environmental conditions.
- Impacts of hydroclimate change on climate-resilient agriculture at the river basin managementAuthor(s): Singha, Chiranjit; Sahoo, Satiprasad; Govind, Ajit; Pradhan, Biswajeet; Alrawashdeh, Shatha; Aljohani, Taghreed Hamdi; Almohamad, Hussein; Md Towfiqul Islam, Abu Reza; Abdo, Hazem Ghassan (IWA Publishing)Date: 2023-12-15Type: Journal ArticleStatus: Open accessThis paper focuses on exploring the potential of Climate resilient agriculture (CRA) for river basin-scale management. Our analysis is based on long-term historical and future climate and hydrological datasets within a GIS environment, focusing on the Ajoy River basin in West Bengal, Eastern India. The standardized anomaly index (SAI) and slope of the linear regression (SLR) methods were employed to analyse the spatial pattern of the climate variables (precipitation, Tmax and Tmin) and hydrological variables (actual evapotranspiration (AET), runoff (Q), vapor pressure deficit (VPD), potential evapotranspiration (PET), and climate water deficit (DEF)) using the TerraClimate dataset spanning from 1958 to 2020. Future climate trend analysis spanning 2021 to 2050 was conducted using the CMIP6 based GCMs (MIROC6 and EC-Earth3) dataset under shared socio-economic pathway (SSP2-4.5, SSP5-8.5 and historical). For spatiotemporal water storage analysis, we relied on Gravity Recovery and Climate Experiment (GRACE) from the Center for Space Research (CSR) and the Jet Propulsion Laboratory (JPL) data, covering the period from 2002 to 2021. Validation was performed using regional groundwater level data, employing various machine learning classification models. Our findings revealed a negative precipitation trend (approximately −0.04 mm/year) in the southern part, whereas the northern part exhibited a positive trend (approximately 0.10 mm/year).
- Development of Raisedbed Machine for Small-Scale Farmers to Improve Water Uses Efficiency in Irrigated EcosystemsAuthor(s): Swelam, Atef; Emara, Ahmed; Fouda, Tarek F (Universitatea de Ştiinţe Agronomice si Medicina Veterinara - Bucureşti, 2023-12-01)Date: 2023-12-01Type: Journal ArticleStatus: Open accessThe locally manufactured small-scale agricultural machinery in Egypt has recently acquired high importance in order to localize technology and innovation at the farm level. This study aims to design a cost-effective multi-seed planting raisedbed machine to rationalize water use and enhance land productivity in the Nile Delta of Egypt. The small farmers will adopt this technique to enable water, energy, seeds, and effort saving. The design of the machine went through a systematic process of tests to ensure that the design fit for purpose considering a set of design criteria such as soil type, crop type, and varieties as well as seeds size, planting rates, roads networks, farm sizes, cost-effectiveness, and available existing traction forces. The analyses using SolidWorks, a solid modelling computer-aided design and engineering application program, and Ansys simulation software were carried out to the loads and stresses subjected to different parts of the machine in order to identify the proper thickness and materials to manufacture the machine. Based on the stress and strain analysis, the machine structure and its components were designed. The main components of the machine include the main skeleton, seed drill box, planter seed box, feeding chambers, and cells as well as a feeding tube, gearbox, ditchers, ground-driving wheel and transmission mechanism, and mounting triangle. After building the machine components, various investigations were performed by subjecting the used materials to ascending loads to analyze shearing force, normal stress, shear stress, strain, and strength analysis in a micro meshes scale in all machine components. These tests enabled the identification of deformations, equivalent elastic strain, and Safety factor on different machine parts. The simulated values of the machine’s parts in thicknesses and dimensions were in good correspondence and consistency with the actual design values. The model showed that the boundary conditions were accurate and rational, and it would provide a scientific basis for the optimum design of the raisedbed machine under multiple and interlinked loads.
- Fostering an enabling environment for equality and empowerment in agri-food systems: An assessment at multiple scalesAuthor(s): Lecoutere, Els; Leah Achandi, Esther; Lubega Ampaire, Edidah; Fischer, Gundula; Gumucio, Tatiana; Najjar, Dina; Singaraju, Niyati (Elsevier (12 months), 2024-03-01)Date: 2023-12-22Type: Journal ArticleStatus: Open accessInequalities by gender and intersecting sources of social differentiation in access to resources, exercise of agency, and desirable outcomes persist in agri-food systems in low- and middle income countries. Despite decades of development and theoretical assessment efforts calling for multiscale approaches to addressing inequalities in agri-food systems, common approaches remain specific to a scale rather than holistic. In this paper, we make the case that achieving lasting equality and empowerment in agri-food systems requires transformative change. This depends on fostering an enabling environment by relaxing ‘deeper’ – often interrelated – institutionalized constraints to equality and empowerment across multiple nested scales of the state, markets, communities, household and individuals. Based on a review of recent literature focused on agri-food systems in low- and middle income countries, we present newly emerging thinking and a status update of key structural constraints to equality at different scales – rooted in policy and discriminatory, formal and informal, social and economic institutions, including norms. We give examples that show how structural constraints to equality at different nested scales are interdependent and mutually reinforcing; demonstrating the need for holistic approaches tackling constraints at multiple scales to foster transformative change in agri-food systems. We recommend designing holistic policy and development programs that combine strategies for relaxing constraints to equality and empowerment at multiple scales using inclusive processes of tailoring and prioritizing. To inform the design of such programs, we present recent evidence of effective or promising strategies for addressing structural constraints to equality that relate to policy, market systems, collectives and norms.
- Identifying manning roughness coefficient using automatic calibration method and simulation of pollution incidents in the Nile River, EgyptAuthor(s): Abouelsaad, Omnia; Hassan, Aziz; Omar, Mohie; Hinkelmann, Reinhard (Elsevier (12 months))Date: 2024-07-30Type: Journal ArticleStatus: Open accessStudy region A reach of the Nile River located between Naga Hammadi barrage and Asyut barrage, Egypt Study focus An accurate representation of hydrodynamics of an important water source helps cope with expected future climate changes, pollution incidents and water quality problems. Here, a comparison between HEC-RAS 1D and TELEMAC-2D model was conducted by identifying different Manning coefficients. Moreover, an automatic calibration using Dual-Annealing optimization method was applied for first time to calibrate the model with non-uniform Manning coefficients. The transport of tracer (pollution) was simulated by computing tracer residence times. Pollution transport scenarios were discussed to draw a picture of pollution incidents which will continue to happen in the future. An equation indicating the relation between flow discharge and residence time was derived to hurriedly help decision makers in water management during sudden pollution incidents. New hydrological insights for the region A model with spatially variable Manning coefficients using TELEMAC-2D was set up and calibrated achieving good accuracyies with average errors of approximately 4 cm and 7 cm between field and simulated water levels for two different discharge scenarios. Moreover, an equation for relation between flow discharge and residence time was derived producing a strong correlation coefficient of 0.95. This study, integrating advanced hydrodynamic models and automatic calibration techniques, provides a robust framework for assessing and managing water resource challenges under varying flow conditions.
- Detection and Molecular Characterization of Phytoplasma Associated with Phyllody Disease on Dimorphotheca Pluvialis in EgyptAuthor(s): El-Banna, Om-Hashem M.; Kheder, Ahmed A.; Haj Ali, Mayadah A. (ESCIENCE PRESS)Date: 2024-04-30Type: Journal ArticleStatus: Open accessDuring the spring of 2021-2022, imported grown African daisy (Dimorphotheca pluvialis L. Moench) plants (Family: Asteracae) exhibiting symptoms of phyllody phytoplasma, such as phyllody and virescence of flowers, and witches' broom, were observed in different gardens of Cairo governorate, Egypt. The disease was successfully transmitted experimentally through dodder (Cuscuta reflexa) to healthy periwinkle (Cantharanthus roseus) plants. The light and transmission electron microscopic examination revealed phytoplasma units in sieve tubes with a lot of deterioration of the cell components due to the phytoplasma infection. Nested polymerase chain reaction (nested-PCR) assay used as a key technique to identify the phytoplasma by amplifying products of 1250 bp using two pairs of primers; a universal primer pair (P1/P7) and (R16F2n/R16R2) as a specific primer pair. The Egyptian phytoplasma isolate (Dimo-Cairo) was registered with accession number “OQ676407.1” in the NCBI GenBank. MEGA sequence analysis software version 11 was used to generate the phylogenetic tree of Dimo-Cairo and to compare it with the other phytoplasma strains. The clustering of phytoplasma strains confirmed that Dimo-Cairo was associated with the 16Sr-II group (Candidatus Phytoplasma aurantifolia), and placed it close to stem curling and phyllody phytoplasma (16Sr-II-A subgroup), witches-broom phytoplasma and cactus witches-broom phytoplasma (16Sr-II-C subgroup) and Corchorus olitorius phytoplasma and Vicia faba stunting phytoplasma (16Sr-II-D subgroup). To our knowledge, this is the first report of a phytoplasma infecting Dimorphotheca pluvialis plants in Egypt.
- Prediction of soil nutrients through PLSR and SVMR models by VIs-NIR reflectance spectroscopyAuthor(s): Singha, Chiranjit; Swain, Kishore Chandra; Sahoo, Satiprasad; Govind, Ajit (Elsevier (12 months), 2023-12-01)Date: 2023-11-10Type: Journal ArticleStatus: Open accessThough soil nutrients play important roles in maintaining soil fertility and crop growth, their estimation requires direct soil sampling followed by laboratory analysis incurring huge cost and time. In this research work, soil nutrients were predicted using VIs-NIR reflectance spectroscopy (range 350–2500 nm) with Partial Least Squares Regression (PLSR) and Support Vector Machine Regression Model (SVMR) model through principal component analysis. Two hundred soil samples were collected from Tarekswar, Hooghly, West Bengal, India to predict eight selected soil nutrients, such as soil organic carbon (OC), pH, available nitrogen (N), available phosphorus (P), available potassium(K), electric conductivity (EC), zinc (Zn) and soil texture (sand, silt, and clay) levels. The OC content was predicted with sound accuracy (R2: 0.82, RPD: 2.28, RMSE: 0.13, RPIQ: 4.15 FD-SG), followed by P (R2: 0.71, RPD: 1.83, RMSE: 4575, RPIQ: 3.44 1st derivative). The soil parameters sensitive to the particular band of visible spectrum were also identified viz. wavelengths of 409, 444, 591 and 592 nm for OC, 430 and 505 nm for P, 464 nm for K; 580 nm for Zn, 492,511,596 and 698 nm for N; 493, 569 and 665 nm for EC; 492,567 and 652 nm for pH; 457 nm for sand and 515 nm for clay. The soil nutrient levels were predicted by PLSR and SVMR models through PCA and Sentinel 2 imagery and soil suitability map were also generated for seven soil parameters such as OC, pH, EC, N, P, K and clay content. Through map query tool in ArcGIS software environment the PLSR and SVMR model successfully identify the suitability class with level of accuracy of 87.2% and 88.9%, respectively, against the direct soil analysis based suitability mapping. The machine learning technique based soil nutrient and soil suitability prediction can be easily adopted in different regions. This will reduce the cost of laboratory soil analysis and optimize the total time requirement.
- The Fusion Impact of Compost, Biochar, and Polymer on Sandy Soil Properties and Bean ProductivityAuthor(s): Kheir, Ahmed M.S.; Govind, Ajit; Zoghdan, Medhat G.; Khalifa, Tamer; Aboelsoud, Hesham; Shabana, Mahmoud Mohamed Abd ElHay (MDPI)Date: 2023-10-03Type: Journal ArticleStatus: Open accessTwo of the most significant issues confronting arid and semi-arid countries are soil degradation and the need to reclaim sandy soils and improve their properties to enhance the agricultural area and ensure food security. Many attempts to improve sandy soil properties have been attempted using soil amendments, but further research is needed to explore the combined impact of cost-effective amendments. To that purpose, we investigated the impact of various soil amendments, including single and combination applications of synthetic Super Absorbent Polymer (SAP), compost, and biochar, on sandy soil physiochemical characteristics and bean (Vicia faba L.) production and quality throughout three growing seasons. In a randomized complete block design with three replicates per treatment, different treatments such as control (without application), lower dose of SAP (SAP1), higher dose of SAP (SAP2), biochar, compost, SAP1 plus biochar, SAP1 plus compost, SAP2 plus biochar, SAP2 plus compost, and biochar plus compost were used. The combined treatments, such as SAP2 plus biochar (T8), SAP2 plus compost (T9), and biochar plus compost (T10), improved soil physiochemical characteristics and crop production significantly. Application of T10 decreased soil bulk density by 15%, 17%, and 13% while increasing soil available water by 10%, 6%, and 3% over the first, second, and third growing seasons, respectively, compared to untreated soil (T1). The application of treatment (T9) surpassed other treatments in terms of yield, quality, and economic return, significantly increasing the seed yield by 24%, 26%, and 27% for the first, second, and third season compared with untreated soil. The higher rate of polymer combined with compost could be considered a cost-effective soil amendment to improve sandy soil productivity in arid and semi-arid regions.
- Machine Learning-Driven Remote Sensing Applications for Agriculture in India—A Systematic ReviewAuthor(s): Pokhariyal, Shweta; Patel, N. R.; Govind, Ajit (MDPI)Date: 2023-08-31Type: Journal ArticleStatus: Open accessIn India, agriculture serves as the backbone of the economy, and is a primary source of employment. Despite the setbacks caused by the COVID-19 pandemic, the agriculture and allied sectors in India exhibited resilience, registered a growth of 3.4% during 2020–2121, even as the overall economic growth declined by 7.2% during the same period. The improvement of the agriculture sector holds paramount importance in sustaining the increasing population and safeguarding food security. Consequently, researchers worldwide have been concentrating on digitally transforming agriculture by leveraging advanced technologies to establish smart, sustainable, and lucrative farming systems. The advancement in remote sensing (RS) and machine learning (ML) has proven beneficial for farmers and policymakers in minimizing crop losses and optimizing resource utilization through valuable crop insights. In this paper, we present a comprehensive review of studies dedicated to the application of RS and ML in addressing agriculture-related challenges in India. We conducted a systematic literature review following the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines and evaluated research articles published from 2015 to 2022. The objective of this study is to shed light on the application of both RS and ML technique across key agricultural domains, encompassing “crop management”, “soil management”, and “water management, ultimately leading to their improvement. This study primarily focuses on assessing the current status of using intelligent geospatial data analytics in Indian agriculture. Majority of the studies were carried out in the crop management category, where the deployment of various RS sensors led yielded substantial improvements in agricultural monitoring. The integration of remote sensing technology and machine learning techniques can enable an intelligent approach to agricultural monitoring, thereby providing valuable recommendations and insights for effective agricultural management.