深度学习与航空调查在巴西半干旱区广泛的牲畜热点识别

IF 1.2 4区 农林科学 Q2 AGRICULTURE, MULTIDISCIPLINARY Ciencia E Agrotecnologia Pub Date : 2023-03-10 DOI:10.1590/1413-7054202347010922
Mayara Lopes de Freitas Lima, Samara Maria Farias de Souza, Isabelle Ventura de Sá, O. A. Santana
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引用次数: 0

摘要

在巴西半干旱地区,采用生态生产管理的粗放型畜牧业是维持和增加山羊产品(如肉类)产量且不消耗环境资源的最有效方法。这一系列行动(诱导山羊迁移和牧场关闭)是畜牧业4.0的一部分,其中工业4.0饲料区使用人工智能和深度学习进行有效管理,由生产者和消费者进行适当监控。这项工作的目的是利用无人机拍摄的航测图像,利用深度学习技术进行分类,确定有ficus-indica (Mill,仙人掌科)饲料棕榈品种的牧区,用于繁殖和生产Capra aegagrus-hircus山羊(Lineu,牛科)。工业架构参考模型4.0的方法步骤适应现场情况(半干旱区),包括(A)研究区域划分,(B)图像采集(无人机),(C)深度学习训练,卷积神经网络(CNN)训练,(D)训练精度分析,(E)自动山羊生产评估和验证。基于牧草棕榈密度的区域分类使我们能够衡量牲畜造成的环境退化。受刺激的山羊迁移减少了这种退化,并增加了山羊生物量和产量。
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Deep learning with aerial surveys for extensive livestock hotspot recognition in the Brazilian Semi-arid Region
ABSTRACT In the Brazilian Semi-arid Region, extensive livestock farming with ecoproductive management is the most efficient way to maintain and increase the production of goat products (e.g., meat) with of not depleting environmental resources. This set of actions (induced goat migration and pasture closure) is part of Livestock 4.0, in which Industry 4.0 feed areas are efficiently managed using artificial intelligence and deep learning properly monitored by the producer and the consumer. The objective of this work was to identify pasture areas with Opuntia ficus-indica (Mill, Cactaceae) forage palm species for breeding and production of Capra aegagrus-hircus goats (Lineu, Bovidae) using aerial survey images captured by drones classified using deep learning techniques. The methodological steps of the Industry Architecture Reference Model 4.0 were adapted to the field situation (Semi-arid Region) including (A) study area delimitation, (B) image collection (by drones), (C) deep learning training, convolutional neural network (CNN) training, (D) training accuracy analysis, and (E) automatic goat production evaluation and validation. The area classification based on the forage palm density allowed us to measure the environmental degradation caused by livestock. Stimulated goat migration reduced this degradation as well as increased goat biomass and volume production.
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来源期刊
Ciencia E Agrotecnologia
Ciencia E Agrotecnologia 农林科学-农业综合
CiteScore
2.30
自引率
9.10%
发文量
19
审稿时长
6-12 weeks
期刊介绍: A Ciência e Agrotecnologia, editada a cada 2 meses pela Editora da Universidade Federal de Lavras (UFLA), publica artigos científicos de interesse agropecuário elaborados por membros da comunidade científica nacional e internacional. A revista é distribuída em âmbito nacional e internacional para bibliotecas de Faculdades, Universidades e Instituições de Pesquisa.
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