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Artificial Neural Networks in Agriculture
| Artificial Neural Networks in Agriculture |
| Autore | Kujawa Sebastian |
| Pubbl/distr/stampa | Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 |
| Descrizione fisica | 1 electronic resource (283 p.) |
| Soggetto topico |
Research & information: general
Biology, life sciences Technology, engineering, agriculture |
| Soggetto non controllato |
artificial neural network (ANN)
Grain weevil identification neural modelling classification winter wheat grain artificial neural network ferulic acid deoxynivalenol nivalenol MLP network sensitivity analysis precision agriculture machine learning similarity metric memory deep learning plant growth dynamic response root zone temperature dynamic model NARX neural networks hydroponics vegetation indices UAV neural network corn plant density corn canopy cover yield prediction CLQ GA-BPNN GPP-driven spectral model rice phenology EBK correlation filter crop yield prediction hybrid feature extraction recursive feature elimination wrapper artificial neural networks big data classification high-throughput phenotyping modeling predicting time series forecasting soybean food production paddy rice mapping dynamic time warping LSTM weakly supervised learning cropland mapping apparent soil electrical conductivity (ECa) magnetic susceptibility (MS) EM38 neural networks Phoenix dactylifera L. Medjool dates image classification convolutional neural networks transfer learning average degree of coverage coverage unevenness coefficient optimization high-resolution imagery oil palm tree CNN Faster-RCNN image identification agroecology weeds yield gap environment health crop models soil and plant nutrition automated harvesting model application for sustainable agriculture remote sensing for agriculture decision supporting systems neural image analysis |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910557509803321 |
Kujawa Sebastian
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| Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Remote Sensing of Land Surface Phenology
| Remote Sensing of Land Surface Phenology |
| Autore | Ma Xuanlong |
| Pubbl/distr/stampa | MDPI - Multidisciplinary Digital Publishing Institute, 2022 |
| Descrizione fisica | 1 electronic resource (276 p.) |
| Soggetto topico |
Technology: general issues
History of engineering & technology Environmental science, engineering & technology |
| Soggetto non controllato |
climate change
digital camera MODIS Mongolian oak phenology sap flow urbanization plant phenology spatiotemporal patterns structural equation model Google Earth Engine Three-River Headwaters region GPP carbon cycle arctic photosynthesis remote sensing crop sowing date development stage yield gap yield potential process-based model land surface temperature urban heat island effect contribution Hangzhou land surface phenology NDVI spatiotemporal dynamics different drivers random forest model data suitability satellite data spatial scaling effects the Loess Plateau autumn phenology turning point climate changes human activities Qinghai-Tibetan Plateau snow phenology driving factors spatiotemporal variations Northeast China vegetation indexes seasonally dry tropical forest vegetation phenology climatic limitation solar-induced chlorophyll fluorescence enhanced vegetation index gross primary production evapotranspiration water use efficiency NDPI Qilian Mountains snow cover high elevation soil moisture vegetation dynamics carbon exchange |
| ISBN | 3-0365-5326-6 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910619465703321 |
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Ma Xuanlong
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| MDPI - Multidisciplinary Digital Publishing Institute, 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Site-Specific Nutrient Management
| Site-Specific Nutrient Management |
| Autore | Grzebisz Witold |
| Pubbl/distr/stampa | Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022 |
| Descrizione fisica | 1 electronic resource (224 p.) |
| Soggetto topico |
Research & information: general
Biology, life sciences Technology, engineering, agriculture |
| Soggetto non controllato |
Triticum aestivum L.
farmyard manure mineral fertilizers crude protein content soil properties, site-specific requirements yield site-specific nitrogen management regional optimal nitrogen management net return nitrogen use efficiency spatial variability temporal variability seed density N uptake indices of N productivity mineral N indigenous Nmin at spring post-harvest Nmin N balance N efficiency maximum photochemical efficiency of photosystem II chlorophyll content index soil enzymatic activity biological index fertility nitrogenase activity microelements fertilization (Ti Si B Mo Zn) soil nitrate nitrogen content contents of available phosphorus potassium magnesium calcium cardinal stages of WOSR growth PCA site-specific nutrient management soil brightness satellite remote sensing crop yield soil fertility winter wheat winter triticale vegetation indices NDVI grain yield number of spikes economics normalized difference vegetation index (NDVI) on-the-go sensors winter oilseed rape → winter triticale cropping sequence N input N total uptake N gap Beta vulgaris L. organic manure weather conditions soil chemistry sugar concentration climatic potential yield yield gap soil constraints subsoil remote sensing-techniques field a field crop production sustainability homogenous productivity units nitrogen indicators: in-season spatial vertical variability of N demand and supply spectral imagery |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910566459003321 |
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Grzebisz Witold
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| Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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