Sökning: "Crop yield"
Visar resultat 1 - 5 av 330 uppsatser innehållade orden Crop yield.
1. Assessing water balance and yields in Malawian cropping systems : maize soybean and maize Gliricidia systems resilience against climate changeMaster-uppsats, SLU/Dept. of Soil and Environment
Sammanfattning : In Malawi, maize monocultures are increasingly susceptible to extreme weather patterns, causing considerable yield reduction and heightened food insecurity for smallholder farmers dependent on rainfed subsistence agriculture. Diversifying cropping systems is crucial for ensuring yield resilience. LÄS MER
2. Sustainable use of calcium nitrate fertilizer under variable precipitation, soil properties and crop managementMaster-uppsats, SLU/Dept. of Soil and Environment
Sammanfattning : Application of nitrogen fertilizers in agriculture contributes substantially to global greenhouse gas emissions and nitrogen leaching. Accordingly, there is a need to increase knowledge about sustainable farming practices to reduce nitrogen losses to the environment without curtailing crop harvest. LÄS MER
3. Biogasproduktion vid samrötning av substrat tillgängliga vid lantbruk : Småskalig rötning vid LillerudsgymnasietMaster-uppsats, Karlstads universitet/Fakulteten för hälsa, natur- och teknikvetenskap (from 2013)
Sammanfattning : The world is currently heavily dependent on fossil sources and the use of fossil fuels leads to increased global warming. One of the solutions to this environmental problems is biogas. LÄS MER
4. SHADING ANALYSIS OF AGRIVOLTAIC SYSTEMS : The shading’s effect on lettuce and potato from elevated agrivoltaic system in SwedenMaster-uppsats, Mälardalens högskola/Framtidens energi
Sammanfattning : The world is progressing towards a more sustainable society, where renewable energy sources, including solar energy, play a crucial role. This study aims to address the conflict between agriculture and energy production by exploring the installation of solar panels on farmland. LÄS MER
5. Study of evaluation metrics while predicting the yield of lettuce plants in indoor farms using machine learning modelsMagister-uppsats, Högskolan i Skövde/Institutionen för informationsteknologi
Sammanfattning : A key challenge for maximizing the world’s food supply is crop yield prediction. In this study, three machine models are used to predict the fresh weight (yield) of lettuce plants that are grown inside indoor farms hydroponically using the vertical farming infrastructure, namely, support vector regressor (SVR), random forest regressor (RFR), and deep neural network (DNN). LÄS MER