Balancing quality with quantity: a case study of UK bread wheat

Nick Fradgley Keith Gardner Stéphanie M. Swarbreck Alison Bentley (2023, [Artículo])

Grain Protein Content Environmental Sustainability End-Use Quality Modern Bread Baking Methods CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA GRAIN PROTEIN CONTENT HISTORY QUALITY WHEAT YIELDS

Preliminary dissection of grain yield and related traits at differential nitrogen levels in diverse pre-breeding wheat germplasm through association mapping

Achla Sharma Juan Burgueño Prashant Vikram Nitika Sandhu Satinder Kaur Parveen Chhuneja (2023, [Artículo])

Plant Nitrogen Use Efficiency Pre-Breeding Lines Genome-Wide Association Study Marker Trait Association CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA WHEAT PRE-BREEDING BREEDING LINES NITROGEN LANDRACES GENETIC MARKERS

Nitrogen use efficiency and genotype-by-environment interaction in durum wheat genotypes under varying nitrogen supply

Tesfaye Geleta Aga Bekele Abeyo (2024, [Artículo])

Straw Nitrogen Uptake Nitrogen Harvest Index CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA NITROGEN-USE EFFICIENCY STRAW GENOTYPE ENVIRONMENT INTERACTION HARD WHEAT

Low nitrogen narrows down phenotypic diversity in durum wheat

Tesfaye Geleta Aga Bekele Abeyo (2023, [Artículo])

Clusters Durum Wheat Nitrogen Efficiency CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA HARD WHEAT GENETIC DIVERGENCE NORMALIZED DIFFERENCE VEGETATION INDEX NITROGEN PRINCIPAL COMPONENT ANALYSIS

Fighting food, fertilizer, and the climate crisis in Africa through targeted nitrogen management

Tek Sapkota Sieglinde Snapp (2022, [Objeto de congreso])

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA FOOD INSECURITY NITROGEN FERTILIZERS RICE WHEAT MAIZE NUTRIENT MANAGEMENT

Optimization of N dose in rice under conservation agriculture with sub-surface drip fertigation

C.M. Parihar Hari Sankar Nayak Renu Pandey Avinash Kumar ML JAT (2021, [Artículo])

Biological Yield Economic N Dose Yield Attributes CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA YIELDS NITROGEN ZERO TILLAGE DIRECT SOWING RICE

Multi-modal deep learning improves grain yield prediction in wheat breeding by fusing genomics and phenomics

Xu Wang Sandesh Kumar Shrestha Philomin Juliana Suchismita Mondal Francisco Pinto Govindan Velu Leonardo Abdiel Crespo Herrera JULIO HUERTA_ESPINO Ravi Singh Jesse Poland (2023, [Artículo])

New Crop Varieties Plant Breeding Programs Yield Prediction CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA LEARNING GRAIN YIELDS WHEAT BREEDING FOOD SECURITY

Hub meeting Honduras: Gestión de la red de innovación en el occidente y oriente de Honduras. ¿Porque genero e inclusion social en Agrilac?

Angela Meentzen (2023, [Objeto de congreso])

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA GENDER EQUALITY FOOD SYSTEMS CLIMATE CHANGE WOMEN'S PARTICIPATION

Targeted nitrogen management to increase cereal production while reducing nitrogen consumption in India

Tek Sapkota Sieglinde Snapp (2022, [Objeto de congreso])

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA CEREAL PRODUCTS PRODUCTION SYSTEMS CEREALS NITROGEN RICE WHEAT MAIZE

Classification of Cucumber Leaves Based on Nitrogen Content Using the Hyperspectral Imaging Technique and Majority Voting.

Sajad Sabzi Razieh Pourdarbani Mohammad Hossein Rohban Alejandro Fuentes_Penna José Luis Hernández-Hernández Mario Hernández Hernández (2021, [Artículo])

Improper usage of nitrogen in cucumber cultivation causes nitrate accumulation in the fruit and results in food poisoning in humans; therefore, mandatory evaluation of food products becomes inevitable. Hyperspectral imaging has a very good ability to evaluate the quality of fruits and vegetables in a non-destructive manner. The goal of the present paper was to identify excess nitrogen in cucumber plants. To obtain a reliable result, the majority voting method was used, which takes into account the unanimity of five classifiers, namely, the hybrid artificial neural network¿imperialism competitive algorithm (ANN-ICA), the hybrid artificial neural network¿harmonic search (ANN-HS) algorithm, linear discrimination analysis (LDA), the radial basis function network (RBF), and the Knearest- neighborhood (KNN). The wavelengths of 723, 781, and 901 nm were determined as optimal wavelengths using the hybrid artificial neural network¿biogeography-based optimization (ANNBBO) algorithm, and the performance of classifiers was investigated using the optimal spectrum. The results of a t-test showed that there was no significant difference in the precision of the algorithm when using the optimal wavelengths and wavelengths of the whole range. The correct classification rate of the classifiers ANN-ICA, ANN-HS, LDA, RBF, and KNN were 96.14%, 96.11%, 95.73%, 64.03%, and 95.24%, respectively. The correct classification rate of majority voting (MV) was 95.55% for test data in 200 iterations, which indicates the system was successful in distinguishing nitrogen-rich leaves from leaves with a standard content of nitrogen.

artificial neural network cucumber hyperspectral imaging majority voting nitrogen INGENIERÍA Y TECNOLOGÍA CIENCIAS TECNOLÓGICAS TECNOLOGÍA DE LOS ALIMENTOS