Use of Geostatistics as a Tool to Study Spatial-Temporal Dynamics of <i>Leucoptera coffeella</i> in Coffee Crops
Coffee is considered one of the most important commercial commodities globally, and in 2020, it moved to a global market of USD 102.02 billion. However, the attack of pests in coffee production can cause significant economic losses. <i>Leucoptera coffeella</i> is a critical pest in coffe...
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-02-01
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| Series: | Agriculture |
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| Online Access: | https://www.mdpi.com/2077-0472/13/2/438 |
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| author | Adriana H. Walerius Angelo Pallini Madelaine Venzon Paulo A. Santana Júnior Thiago L. Costa Jhersyka da S. Paes Emílio de S. Pimentel Marcelo C. Picanço |
| author_facet | Adriana H. Walerius Angelo Pallini Madelaine Venzon Paulo A. Santana Júnior Thiago L. Costa Jhersyka da S. Paes Emílio de S. Pimentel Marcelo C. Picanço |
| author_sort | Adriana H. Walerius |
| collection | DOAJ |
| description | Coffee is considered one of the most important commercial commodities globally, and in 2020, it moved to a global market of USD 102.02 billion. However, the attack of pests in coffee production can cause significant economic losses. <i>Leucoptera coffeella</i> is a critical pest in coffee-producing countries, with productivity losses reaching 87%. The knowledge of the spatial distribution patterns of <i>L. coffeella</i> is essential to developing an efficient sampling and control plan. Moreover, it allows us to target for control specific locations/seasons where <i>L. coffeella</i> occurrence is at its highest density before reaching the economic injury level. Therefore, our objective in this study was to determine the spatial distribution of <i>L. coffeella</i> in coffee crops through geostatistical analysis. Data on the population density of <i>L. coffeella</i> were collected over four years on a farm with 18 center pivots located in the Brazilian Cerrado. The presence of <i>L. coffeella</i> was recorded in all 18 pivots during the entire time of the study (2016 to 2020). The highest densities were from July to November. These high densities of <i>L. coffeella</i> positively correlated with maximum air temperatures and wind speed. It was also verified to negatively correlate with minimum air temperatures and rainfall. The surrounding vegetation does not affect the pest densities. The pest hotspots appeared in different pivots and different locations inside pivots. Furthermore, <i>L. coffeella</i> showed an aggregated distribution pattern. For three years, the colonization started at the edge of the crop. The sampling should be performed equidistant as the pest is distributed equally in all directions. The information found in this study provides valuable information to initiate timely management and control methods in coffee crops with a high incidence of <i>L. coffeella</i>, thus reducing production costs and the harmful effects of pesticide use. |
| first_indexed | 2024-03-11T09:17:39Z |
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| id | doaj.art-27e52c94fada455eb8f39f13c7275a0b |
| institution | Directory Open Access Journal |
| issn | 2077-0472 |
| language | English |
| last_indexed | 2024-03-11T09:17:39Z |
| publishDate | 2023-02-01 |
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| series | Agriculture |
| spelling | doaj.art-27e52c94fada455eb8f39f13c7275a0b2023-11-16T18:31:10ZengMDPI AGAgriculture2077-04722023-02-0113243810.3390/agriculture13020438Use of Geostatistics as a Tool to Study Spatial-Temporal Dynamics of <i>Leucoptera coffeella</i> in Coffee CropsAdriana H. Walerius0Angelo Pallini1Madelaine Venzon2Paulo A. Santana Júnior3Thiago L. Costa4Jhersyka da S. Paes5Emílio de S. Pimentel6Marcelo C. Picanço7Department of Entomology, Federal University of Viçosa, Viçosa 36570-900, BrazilDepartment of Entomology, Federal University of Viçosa, Viçosa 36570-900, BrazilAgriculture and Livestock Research Enterprise of Minas Gerais (EPAMIG), Viçosa 36571-000, BrazilDepartment of Entomology, Federal University of Viçosa, Viçosa 36570-900, BrazilDepartment of Agronomy, Federal University of Viçosa, Viçosa 36570-900, BrazilDepartment of Agronomy, Federal University of Viçosa, Viçosa 36570-900, BrazilDepartment of Entomology, Federal University of Viçosa, Viçosa 36570-900, BrazilDepartment of Entomology, Federal University of Viçosa, Viçosa 36570-900, BrazilCoffee is considered one of the most important commercial commodities globally, and in 2020, it moved to a global market of USD 102.02 billion. However, the attack of pests in coffee production can cause significant economic losses. <i>Leucoptera coffeella</i> is a critical pest in coffee-producing countries, with productivity losses reaching 87%. The knowledge of the spatial distribution patterns of <i>L. coffeella</i> is essential to developing an efficient sampling and control plan. Moreover, it allows us to target for control specific locations/seasons where <i>L. coffeella</i> occurrence is at its highest density before reaching the economic injury level. Therefore, our objective in this study was to determine the spatial distribution of <i>L. coffeella</i> in coffee crops through geostatistical analysis. Data on the population density of <i>L. coffeella</i> were collected over four years on a farm with 18 center pivots located in the Brazilian Cerrado. The presence of <i>L. coffeella</i> was recorded in all 18 pivots during the entire time of the study (2016 to 2020). The highest densities were from July to November. These high densities of <i>L. coffeella</i> positively correlated with maximum air temperatures and wind speed. It was also verified to negatively correlate with minimum air temperatures and rainfall. The surrounding vegetation does not affect the pest densities. The pest hotspots appeared in different pivots and different locations inside pivots. Furthermore, <i>L. coffeella</i> showed an aggregated distribution pattern. For three years, the colonization started at the edge of the crop. The sampling should be performed equidistant as the pest is distributed equally in all directions. The information found in this study provides valuable information to initiate timely management and control methods in coffee crops with a high incidence of <i>L. coffeella</i>, thus reducing production costs and the harmful effects of pesticide use.https://www.mdpi.com/2077-0472/13/2/438coffee leaf minergeostatisticsintegrated pest managementspatial distribution |
| spellingShingle | Adriana H. Walerius Angelo Pallini Madelaine Venzon Paulo A. Santana Júnior Thiago L. Costa Jhersyka da S. Paes Emílio de S. Pimentel Marcelo C. Picanço Use of Geostatistics as a Tool to Study Spatial-Temporal Dynamics of <i>Leucoptera coffeella</i> in Coffee Crops Agriculture coffee leaf miner geostatistics integrated pest management spatial distribution |
| title | Use of Geostatistics as a Tool to Study Spatial-Temporal Dynamics of <i>Leucoptera coffeella</i> in Coffee Crops |
| title_full | Use of Geostatistics as a Tool to Study Spatial-Temporal Dynamics of <i>Leucoptera coffeella</i> in Coffee Crops |
| title_fullStr | Use of Geostatistics as a Tool to Study Spatial-Temporal Dynamics of <i>Leucoptera coffeella</i> in Coffee Crops |
| title_full_unstemmed | Use of Geostatistics as a Tool to Study Spatial-Temporal Dynamics of <i>Leucoptera coffeella</i> in Coffee Crops |
| title_short | Use of Geostatistics as a Tool to Study Spatial-Temporal Dynamics of <i>Leucoptera coffeella</i> in Coffee Crops |
| title_sort | use of geostatistics as a tool to study spatial temporal dynamics of i leucoptera coffeella i in coffee crops |
| topic | coffee leaf miner geostatistics integrated pest management spatial distribution |
| url | https://www.mdpi.com/2077-0472/13/2/438 |
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