The research in this book looks at the likelihood and level of use of implemented technological components with regard to the adoption of different precision agricultural technologies. To identify the variables affecting farmers' choices to embrace more precise technology, zero-inflated Poisson and negative binomial count data regression models are utilized. Outcomes from the count data analysis of a random sample of various farm operators show that various aspects, including farm dimension, farmer demographics, soil texture, urban impacts, farmer position of liabilities, and position of the farm in a state, were significantly associated with the approval severity and likelihood of precision farming technologies.
Technical topics discussed in the book include:
- Precision agriculture
- Machine learning
- Wireless sensor networks
- IoT
- Deep learning
Betal nemt med kort, Klarna, Apple Pay eller Google Pay. Ikke tilfreds? Du har altid 14 dages fortrydelsesret. Læs mere i vores vilkår. Har du spørgsmål, så send os en mail på hello@memmo.org.
Memmo gør det nemmere at studere – uanset hvor du er i verden. Hos os samler du dine kursusbøger og smarte studieværktøjer ét sted: resuméer, quizzer, podcasts og flashcards. Og så er der Ted, din studieven, der svarer på alt, du undrer dig over. Over 50 000 studerende studerer allerede her – bygget til at hjælpe dig med at lære hurtigere og stresse mindre.