Resultados de búsqueda - "algorithm"

Concerted evolution at a multicopy locus in the protozoan parasite Theileria parva: Extreme divergence of potential protein-coding sequences por Bishop, Richard P., Musoke, A.J., Morzaria, S.P., Sohanpal, B.K., Gobright, E.I.

“…The probe sequences were, however, protein coding accoring to predictive algorithms and codon usage. The 3'/C-terminal ends of the Uganda and Boleni ORFs exhibited 75 percent similarity and identity, respectively, to the previously identified Tpr1 and Tpr2 repetitive elements of T. parva Muguga. …”
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The FIGS (Focused Identification of Germplasm Strategy) approach identifies traits related to drought adaptation in Vicia faba genetic resources por Khazaei H, Street K, Bari, A., Mackay M, Stoddard FL

“…The two sets were grown under well watered conditions and leaf morpho-physiological traits related to plant water use were measured. Machine-learning algorithms split the accessions into two groups based on the evaluation data and the groups created by this process were compared to the original climate-based FIGS sets. …”
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Status of the draft potato ontology. por Simon, R., Bonierbale, Merideth W.

“…The CO serves primarily to harmonize phenotypic and genotypic data for semantic compatibility across diverse, distributed data types; and ontology in general, facilitates the use of terms by both humans and algorithms. Other potential uses include knowledge transfer across species and predictions. …”
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Machine Vision-Based Measurement Systems for Fruit and Vegetable Quality Control in Postharvest por Blasco, José, Munera, Sandra, Aleixos, Nuria, Cubero, Sergio, Moltó, Enrique

“…Machine vision-based applications require the use of multiple technologies and knowledge, ranging from those related to image acquisition (illumination, cameras, etc.) to the development of algorithms for spectral image analysis. Machine vision-based systems for inspecting fruit and vegetables are targeted towards different purposes, from in-line sorting into commercial categories to the detection of contaminants or the distribution of specific chemical compounds on the product's surface. …”
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The fate of wetlands: can the view from space help us to stop and reverse their global decline? por Strauch, A., Bunting, P., Campbell, J., Cornish, N., Eberle, J., Fatoyinbo, T., Franke, J., Hentze, K., Lagomasino, D., Lucas, R., Paganini, M., Rebelo, Lisa-Maria, Riffler, M., Rosenqvist, A., Steinbach, S., Thonfeld, F., Tottrup, C.

“…Many challenges still remain, although different projects and case studies successfully demonstrate the opportunities provided by the growing data archives, analysis algorithms, and processing capabilities. Many of these demonstrations focus on local wetland sites. …”
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Monitoring spatial-temporal variations of surface areas of small reservoirs in Ghana’s Upper East Region using Sentinel-2 satellite imagery and machine learning por Ghansah, B., Foster, T., Higginbottom, T. P., Adhikari, R., Zwart, Sander J.

“…The study also showed the effectiveness of remote sensing and machine learning algorithms as tools for monitoring small reservoirs.…”
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Conservation Agriculture Benefits Indian Farmers, but Technology Targeting Needed for Greater Impacts por Krishna, Vijesh V., Keil, Alwin, Jain, Meha, Weiqi Zhou, Jose, Monish, Surendran-Padmaja, Subash, Barba-Escoto, Luis, Singh, Balwinder, Jat, Mangi Lal, Erenstein, Olaf

“…Econometric models and machine learning algorithms were used to analyze remote sensing data and farm household data collected from the Indian states of Punjab and Bihar, two contrasting agrarian economies of the IGP. …”
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Bias correction of daily chirps-V2 rainfall estimates in Ghana por Johnson, R.

“…In this study, CHIRPS-v2 rainfall estimates were bias corrected using four (4) different bias correction algorithms (Linear Scaling (LS), Local Intensity Scaling (LOCI), Quantile Mapping (QM) and Bias Correction and Spatial Disaggregation (BCSD) methods) using 28 selected stations across Ghana and spatio-temporally over the entire country. …”
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Remote sensing grassland productivity attributes: a systematic review por Bangira, T., Mutanga, O., Sibanda, M., Dube, T., Mabhaudhi, Tafadzwanashe

“…Mastering and listing major uncertainties associated with different algorithms for the GP prediction and pledging to reduce these errors are critical.…”
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Effects of land use land cover change on streamflow of Akaki Catchment, Addis Ababa, Ethiopia por Negash, E. D., Asfaw, Wegayehu, Walsh, C. L., Mengistie, G. K., Haile, Alemseged Tamiru

“…Since the comparative performance of classification algorithms is poorly understood, we compared the performance of one parametric and five non-parametric machine learning methods for LULC mapping using Landsat imageries. …”
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Unleashing the potential of underutilized datasets to improve agricultural decision-making through comprehensive data analysis: An example of rice crop manager (RCM) dataset por Gakhar, Shalini, Sharma, Sheetal

“…We use the datasets collected in a decision support tool called Rice Crop Manager (RCM) and employ machine learning algorithms to estimate yield targets, which can then be used to generate field-specific nutrient management recommendations. …”
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Linkage disequilibrium between alleles at highly polymorphic mini- and micro-satellite loci of Theileria parva isolated from cattle in three regions of Kenya por Odongo, David O., Oura, C.A., Spooner, P.R., Kiara, Henry K., Mburu, D., Hanotte, Olivier H., Bishop, Richard P.

“…Genetic distances and dendrograms derived from these using neighbour-joining algorithms did not indicate significant clustering on a geographical basis. …”
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Tolerance to spittlebugs (Hemiptera: Cercopidae) in Urochloa spp. and Megathyrsus maximus grasses por Espitia Buitrago, Paula Andrea, Ruiz-Hurtado, Andres Felipe, Hernández, Luis Miguel, Jauregui, Rosa Noemi, Cardoso Arango, Juan Andres

“…The dataset is a resource for validating the current plant damage quantification technique for repeatability, and for training machine learning algorithms to identify, classify or quantify plant damage caused by biotic and abiotic stress with similar symptoms. …”
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Free online trainings on soil health monitoring with satellite based remote sensors por Huq, Rafiq, Lesueur, Didier

“…Each session featured three one-hour lectures as outlined below: 1. « Earth Observation and Soil Health: Where Innovation Meets Practice » - Focus: The origins and development of Earth Observation (EO) technology, its applications innatural sciences and soil health monitoring, as well as its opportunities and limitations. 2. « Satellite-Based Remote Sensing: How Earth Observation Enhances Soil Health Monitoring » - Focus: Various remote sensing (RS) technologies, their application in soil data collection, and the role of RS data in monitoring soil health. 3. « From Data to Decisions: Translating Remote Sensing Insights into Practical Soil Health Solutions » - Focus: AI-based agricultural informatics, the use of machine learning in data analysis and automation, and the importance of baseline data for machine learning algorithms.…”
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Advances in sorghum improvement for climate resilience in the global arid and semi-arid tropics: A Review por Mwamahonje, Andekelile, Mdindikasi, Zamu, Mchau, Devotha, Mwenda. Emmanuel, Sanga, Daines, Garcia Oliveira, Ana Luísa, Ojiewo, Chris O.

“…In addition, recent advancements including new machine learning algorithms, gene editing, genomic selection, rapid generation advancement, and recycling of elite material, along with high-throughput phenotyping tools such as drone- and satellite-based images and other speed-breeding techniques, have increased the precision, speed, and accuracy of new crop variety development. …”
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Optimizing Rice Crop Manager Odisha: AI-Driven Yield Prediction to compliment Extension using legacy data por Gakhar, Shalini, Bharti, Preeti

“…To leverage legacy data effectively, machine learning algorithms have been integrated into RCM to identify key factors influencing crop outcomes and assist in estimating target yields. …”
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Modelling the current and future agro-ecological distribution potential of Mexican prickly poppy (Argemone mexicana L.) invasive alien plant species in South Wollo, Ethiopia por Teklegiorgis, Shewakena, Belayneh, Anteneh, Gebermeskel, Kidane, Akomolafe, Gbenga Festus, Dejene, Sintayehu W.

“…An ensemble SDM model was run consisting of five algorithms into one single model. The area under the curve (AUC) and true skill statics (TSS) of the ensemble SDM score values of 0.89 and 0.7, respectively. …”
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Comparative performance of the objective vs. consensual seasonal climate forecasting approaches in West Africa and the Sahel por Tanimoune, Laouali I, Nimon, Pouwereou, Ali, Abdou, Houngnibo, Mandela C M, Alhassane, Agali, Mohamed, Hamatan, Soumana, Djibo, Assoumana, Boubacar Toukal, Segnon, Alcade Christel, Zougmore, Robert Bellarmin

“…AGRHYMET RCC-AOS, through the AICCRA project, has developed objective seasonal forecasting systems, combining advanced statistics, dynamical models, and artificial intelligence algorithms improving accuracy and reliability of climate forecasts across the region. …”
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An operational model for implementing conservation action por Knight, A., Cowling, R.M., Campbell, Bruce M.

“…This preoccupation has provided systematic assessments with well-tested tools (e.g., area selection algorithms) and principles (e.g., representation, complementarity), but our understanding of these techniques currently far exceeds our ability to apply them effectively to pragmatic conservation problems. …”
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Selection and validation of reference genes for quantitative RT-PCR expression studies of the non-model crop Musa por Podevin, N., Krauss, A., Henry, I., Swennen, Rony L., Remy, S.

“…The expression stability of six candidate reference genes was tested on six different sample sets, and the results were analyzed using the publicly available algorithms geNorm and NormFinder. Our results show that variety, plant material, primer set, and gene identity can all influence the robustness and outcome of RT-qPCR analysis. …”
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