Zobrazeno 1 - 10
of 21
pro vyhledávání: '"Marcelo Chan Fu Wei"'
Publikováno v:
AgriEngineering, Vol 6, Iss 2, Pp 925-946 (2024)
Over the years, agricultural management practices are being improved as they integrate Information and Communication Technologies (ICT) and Precision Agriculture tools. Regarding sugarcane crop production, this integration aims to reduce production c
Externí odkaz:
https://doaj.org/article/b0c4d2ed149e41aca70e72b6ea0850a5
Publikováno v:
AgriEngineering, Vol 5, Iss 3, Pp 1163-1177 (2023)
Building machine learning (ML) calibrations using near-infrared (NIR) soil spectroscopy direct in agricultural areas (online NIR), soil attributes can be fine-scale mapped in a faster and more cost-effective manner, guiding management decisions to en
Externí odkaz:
https://doaj.org/article/a875137880e745049b30a495a055035b
Autor:
Maurício Martello, José Paulo Molin, Marcelo Chan Fu Wei, Ricardo Canal Filho, João Vitor Moreira Nicoletti
Publikováno v:
AgriEngineering, Vol 4, Iss 4, Pp 888-902 (2022)
Coffee has high relevance in the Brazilian agricultural scenario, as Brazil is the largest producer and exporter of coffee in the world. Strategies to advance the production of coffee grains involve better understanding its spatial variability along
Externí odkaz:
https://doaj.org/article/e32a468419de42eebf74ced679381ae6
Dimensionality Reduction Statistical Models for Soil Attribute Prediction Based on Raw Spectral Data
Autor:
Marcelo Chan Fu Wei, Ricardo Canal Filho, Tiago Rodrigues Tavares, José Paulo Molin, Afrânio Márcio Corrêa Vieira
Publikováno v:
AI, Vol 3, Iss 4, Pp 809-819 (2022)
To obtain a better performance when modeling soil spectral data for attribute prediction, researchers frequently resort to data pretreatment, aiming to reduce noise and highlight the spectral features. Even with the awareness of the existence of dime
Externí odkaz:
https://doaj.org/article/46e0993920204489b17c578fc033d11f
Autor:
Valéria Adriele Lopes, Marcelo Chan Fu Wei, Tainá Martins Cardoso, Eder de Souza Martins, José Carlos Casagrande, Eduardo Dal’Ava Mariano
Publikováno v:
Scientia Agricola, Vol 79, Iss 4 (2021)
ABSTRACT Alternatives to enhance the consensual low phosphorus (P) use efficiency of agriculture may include use of phosphate rock (PR) and plant species with unequal ability to get soil and rock P interplanted in cropping systems to allow plants wit
Externí odkaz:
https://doaj.org/article/00d9112bca8c47d89db1cd188fe217e7
Autor:
Tiago Rodrigues Tavares, José Paulo Molin, Lidiane Cristina Nunes, Marcelo Chan Fu Wei, Francisco José Krug, Hudson Wallace Pereira de Carvalho, Abdul Mounem Mouazen
Publikováno v:
Agronomy, Vol 11, Iss 6, p 1028 (2021)
Rapid, cost-effective, and environmentally friendly analysis of key soil fertility attributes requires an ideal combination of sensors. The individual and combined performance of visible and near infrared (VNIR) diffuse reflectance spectroscopy, X-ra
Externí odkaz:
https://doaj.org/article/67089e3193e144778c59b2cc2d2e2586
Publikováno v:
Remote Sensing, Vol 13, Iss 2, p 232 (2021)
Yield maps provide essential information to guide precision agriculture (PA) practices. Yet, on-board yield monitoring for sugarcane can be challenging. At the same time, orbital images have been widely used for indirect crop yield estimation for man
Externí odkaz:
https://doaj.org/article/9698eb40afcf43aeb5d21da643bf9a10
Autor:
Marcelo Chan Fu Wei, José Paulo Molin
Publikováno v:
Agriculture, Vol 10, Iss 8, p 348 (2020)
Soybean yield estimation is either based on yield monitors or agro-meteorological and satellite imagery data, but they present several limiting factors regarding on-farm decision level. Aware that machine learning approaches have been largely applied
Externí odkaz:
https://doaj.org/article/437e9c5aedb44f3bbaa9501b21e79858
Publikováno v:
Biosystems Engineering. 206:150-161
It is known that Near-infrared spectroscopy (NIRS) is a reliable technique used in industrial laboratories to measure sugarcane quality. However, its use as a proximal sensing technology for monitoring the spatial variability of attributes in the fie
Publikováno v:
Repositório Institucional da USP (Biblioteca Digital da Produção Intelectual)
Universidade de São Paulo (USP)
instacron:USP
Universidade de São Paulo (USP)
instacron:USP