Autore |
Cavallo Eugenio
|
Edizione | [1st ed. 2024.] |
Pubbl/distr/stampa |
Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024
|
Descrizione fisica |
1 online resource (471 pages)
|
Disciplina |
628
|
Altri autori (Persone) |
Auat CheeinFernando
MarinelloFrancesco
SaçılıkKamil
MuthukumarappanKasiviswanathan
AbhilashPurushothaman C
|
Collana |
Lecture Notes in Civil Engineering
|
Soggetto topico |
Environmental engineering
Civil engineering
Agriculture
Industrial engineering
Production engineering
Renewable energy sources
Environmental Civil Engineering
Industrial and Production Engineering
Renewable Energy
|
ISBN |
9783031515798
303151579X
|
Formato |
Materiale a stampa  |
Livello bibliografico |
Monografia |
Lingua di pubblicazione |
eng
|
Nota di contenuto |
Intro -- Preface -- Organization -- Contents -- Machinery Systems in Agriculture -- Definition of Reference Models for Functional Parameters and Price for Mowers and Mowerconditioners -- Determination of the Effect of the Technical Parameters Which Affect the Tractor Energy Efficiency -- Chopper System for In-line Small Square Balers -- Determination of Suitable Shearing Conditions for Effective Pruning of Tree Branches -- Shear Tests of Grapevine (Vitis vinifera L.) Canes -- The Effect of Different Tillage Methods on Plant Emergence Parameters for Wheat -- Design Approaches of One-Pass Strip-Till Machines -- Energy Systems in Agriculture -- Coefficient of Dynamic Wall Friction for Hardwood Fuel Pellets -- Mapping Biomass Energy Potential from Agricultural Residues in Tanzania -- Effect of Different Drying Temperatures on CO2 Emissions in Acorn Drying -- Energy-Based Slow-City/Agriculture Mechanization with Circular Hydrogen and Renewable Energy Systems -- Effect of Different OLR and Mixture Ratios on Biogas Production Using Goat Dung and Maize Silage -- Post-Harvest Technologies and Process Engineering -- Optical Techniques for Automated Evaluation of Seed Damage -- Exploring Transfer Learning for Enhanced Seed Classification: Pre-trained Xception Model -- Classification of Pistachio Varieties Using Pre-trained Architectures and a Proposed Convolutional Neural Network Model -- Evaluation of Hydration State around Glycerol as a Humectant Using Microwave Dielectric Spectroscopy -- atural Resources and Environmental Systems in Agriculture -- Development of Fertigation System for Hose Reel Irrigation Machines -- Developing a Data-Driven Model for Predicting Water Stress in Pistachio Trees -- Plant, Animal and Facility Systems in Agriculture -- Evaluation of Air Conditioning Parameters in Semi-closed Greenhouses under Turkey's Climatic Conditions -- 1 Introduction -- 2 Materials and Methods -- 3 Results -- 4 Conclusion -- References -- Criteria of Ecological Pressure on Agricultural Systems -- Discharge Coefficients for Adjustable Slot Inlets Used to Ventilate Animal Production Buildings -- Using Composted Cow Manure to Improve Nutrient Content, Aeration Porosity, and Water Retention of Pine Bark-Based Potting Media -- Impact of Building Geometry, Window Types, and Materials on Daylighting Performance of Livestock Buildings -- Estimation of Vitamin A Concentration in Cattle Blood Based on Fluorescence With/Without Blood Cell Separation by Plasma Filter -- Determination of Operating Parameters in Milking Robots with Milk First Cow Traffic -- Fine-Tuning Growth Conditions: Leaf-Level Vapor Pressure Deficit Control for Optimized Photosynthesis -- Investigation of the Compliance of the Milking Routine and the Pulsator's Working Characteristics to Them Milking Technique in the Bozanönü District of Isparta Province -- Information Technologies, Sensors and Control Systems in Agriculture -- Comparison and Evaluation of Vegetation Indices for Image Sensing Systems in Precision Agriculture -- Implementation and Assessment of an Autonomous Ground Vehicle (AGV) for On-Field Agricultural Operations -- Autonomous Ground Vehicle for Field Activities: Preliminary Sustainability Assessments -- Estimating Tall Fescue and Alfalfa Forage Biomass Using an Unmanned Ground Vehicle -- Combining Digital Image Processing and Machine Learning is Useful for the Early Detection of Salinity and Drought Stresses in Cucumber
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Record Nr. | UNINA-9910806193703321 |