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The sustainability of coffee production is a concern for producers around the world. To be sustainable, it is necessary to achieve satisfactory levels of coffee productivity and quality. Pests and diseases cause reduced productivity and can affect the quality of coffee beans. To ensure sustainability, producers need to monitor pests that can lead to substantial crop losses, such as the coffee leaf miner, Leucoptera coffeella (Lepidoptera: Lyonetiidae), which belongs to the Lepidoptera order and the Lyonetiidae family. This research aimed to use machine learning techniques and vegetation indices to remotely identify infestations of the coffee leaf miner in coffee-growing regions. Field assessments of coffee leaf miner infestation were conducted in September 2023. Aerial images were taken using remotely piloted aircraft to determine 13 vegetative indices with RGB (red, green, blue) images. The vegetation indices were calculated using ArcGis 10.8 software. A comprehensive database encompassing details of coffee leaf miner infestation, vegetation indices, and crop data. The dataset was divided into training and testing subsets. A set of four machine learning algorithms was utilized: Random Forest (RF), Logistic Regression (LR), Support Vector Machine (SVM), and Stochastic Gradient Descent (SGD). Following hyperparameter tuning, the test subset was employed for model validation. Remarkably, both the SVM and SGD models demonstrated superior performance in estimating coffee leaf miner infestations, with kappa indices of 0.6 and 0.67, respectively. The combined use of vegetation indices and crop data increased the accuracy of coffee leaf miner detection. The RF model performed poorly, while the SVM and SGD models performed better. This situation highlights the challenges of tracking coffee leaf miner infestations in fields with varying ages of coffee plants, different cultivars, and other environmental variables. [ABSTRACT FROM AUTHOR]

The coffee leaf miner (Leucoptera coffeella) is a key pest in coffee-producing regions in Brazil. The objective of this work was to evaluate the potential of machine learning algorithms to identify coffee leaf miner infestation by considering the assessment period and Sentinel-2 satellite images generated on the Google Earth Engine platform. Coffee leaf miner infestation in the field was measured monthly from 2019 to 2023. Images were selected from the Sentinel-2 satellite to determine 13 vegetative indices. The selection of images and calculations of the vegetation indices were carried out using the Google Earth Engine platform. A database was generated with information on coffee leaf miner infestation, vegetation indices, and assessment times. The database was separated into training data and testing data. Nine machine learning algorithms were used, including Linear Discriminant Analysis, Random Forest, Support Vector Machine, k-nearest neighbors, and Logistic Regression, and a principal component analysis was conducted for each algorithm. After optimizing the hyperparameters, the testing data were used to validate the model. The best model to estimate miner infestation was RF, which had an accuracy of 0.86, a kappa index of 0.64, and a precision of 0.87. The developed models were capable of monitoring coffee leaf miner infestation. [ABSTRACT FROM AUTHOR]

Coffee is a worldwide commodity, and both coffee-producing and coffee-consuming countries have real concerns about environmental problems and economic growth strategies based on the efficient use of resources. Because this crop is a perennial, pests can significantly affect coffee production, causing considerable yield losses and threatening coffee supply and security. The presence of insects and control strategies for coffee pests is becoming a challenge. Environmental sustainability, conservation of biodiversity, and safety of the coffee seed must go hand in hand with the economic sustainability of coffee growers. This is especially important, as there has been an increase in demand for coffee and new consumer interest in differentiated quality coffee. Regular pest control methods based only on the use of synthetic pesticides are no longer effective or sustainable due to the development of insecticide resistance and negative effects on the environment, human health, and biodiversity. Thus, to ensure better control and ecological sustainability, it is crucial to reduce pesticide use by adopting original alternative strategies to maintain pest populations below the economic threshold level and towards reaching the European Green Deal. In this review, we collect information available for sustainable control of the principal coffee pests in Colombia: coffee berry borer (CBB), Hypothenemus hampei; Monalonion velezangeli; coffee root mealybugs; coffee leaf miner: Leucoptera coffeella; and the coffee red spider mite: Oligonychus yothersi. The control strategies include deep knowledge of the biology of insects and the coffee plant, their relationship with weather and habitats, as well as natural controllers. These control strategies do not involve the use of insecticides, are ecologically friendly and novel, and can be applied in other coffee-producing countries. [ABSTRACT FROM AUTHOR]

Coffee crop has been growing increasingly in Brazil and, in view of this, technologies are constantly being developed to obtain greater productivity. In this context, the effect of polyethylene mulching as a source of fertilizer on coffee production has been studied. The objective of this work was to evaluate the incidence of leaf miner and red mite in coffee as a function of the use of polyethylene mulching and controlled and conventional release fertilizer. The research was carried out in the experimental area of the Federal University of Uberlândia - Campus Monte Carmelo, Minas Gerais, with the cultivar IPR 100, in a randomized block design with four blocks. The following treatments were tested: T1 - double-faced white/black mulching with conventional fertilizer; T2 - white/black double-sided mulching with controlled release fertilizer; T3 - double-sided silver/black mulching with conventional fertilizer; T4 - silver/black double-sided mulching with controlled release fertilizer; T5 - No mulching with conventional fertilizer; T6 - No mulching with controlled release fertilizer. The evaluations took place fortnightly from July 2020 to December 2020, upon verification of the presence or absence of leaf miner and red mite caterpillars. Population density peaks for leaf miner occurred from July to October 2020, and for red mite in August, due to low relative humidity and precipitation. Thus, it is concluded that the use of double-sided silver/black mulching provided greater attractiveness to the coffee leaf miner. The fertilizer sources did not influence the probability of occurrence of this insect pest. In addition, conventional fertilizers, as well as those of controlled release, and the absence/presence of soil coverings, did not influence the incidence of red mite in coffee trees in the Cerrado Mineiro region. [ABSTRACT FROM AUTHOR]

• Pesticide use and the landscape lead to variations in the shape, size, and Fluctuating asymmetry of females of Closterocerus coffeellae wings. • Females of C. coffeella with larger wings show a strongly or moderately aggregated spatial pattern in coffee plantations. • C. coffeellae presents greater potential to biocontrol, and it must be conserved. Closterocerus coffeellae (Hymenoptera: Eulophidae) is a parasitoid of the coffee leaf miner occurring in coffee farms with high selection pressure caused by pesticides and different landscape patterns on the surrounding crops. This work aims to detect morphometric variations and levels of Fluctuating Asymmetry (FA) in the wings of C. coffeellae in coffee farms with a history of insecticide use and different landscape composition in the Planalto region, Bahia, Brazil. Parasitoids originated from six coffee farms in this region. We prepared microscopy slides of the right wings of 30 C. coffeellae females from each population. We determined variations in wing size and shape by geometric morphometry analysis, adding 1 landmark and 9 semi-anatomical landmarks to the wings. The landscape metrics (3 km radius) and levels of spatial dependence for size and AF were calculated using geostatistical analysis. Higher forest cover and edge density in coffee plantations lead to an increase in the wing size of C. coffeellae and reduced wing FA levels. Diversity of the surrounding agricultural land cover in coffee farms and pesticide use reduces wing size and increases levels of FA in coffee farms. The centroid size exhibited strong and moderate aggregation levels across coffee farms. The conservation of C. coffeellae is recommended since the species can be used as a bioproduct against the coffee leaf miner, and as a biocontrol solution for coffee farms. Furthermore, adopting conservative practices of natural vegetation surrounding coffee farms is essential for the parasitoids. It must be included in the coffee leaf miner management, mainly in farms with higher agricultural cropland diversity on surrounding coffee farms and with higher pesticide use. [ABSTRACT FROM AUTHOR]

Brazilian arabica coffee production is based on a set of highly productive cultivars sexually propagated. All of them are susceptible to coffee leaf miner, Leucoptera coffeella, and most of them are also susceptible to coffee leaf rust, Hemileia vastatrix. Aiming to reduce the selection process of cultivars with multiple resistances to both biotic constraints, the Coffea arabica clones 760, 1059, 1064 and 1215 were evaluated under field conditions. The mean yield of four C. arabica clones was not statistically different from the experimental controls; however, the yield of clone 1059 was 21% higher than the control cultivar Obatã IAC 1669-20. Leaf miner resistance level in all the evaluated clones remained the same as the mother plant's. However, the same did not occur for resistance to H. vastatrix, due to the emergence of new pathogen races. In summary, it is potentially feasible the adoption of clone 1059 as a new clonal cultivar resistant to coffee leaf miner. [ABSTRACT FROM AUTHOR]

Highlights: [•] Indirect plant defence provided by extrafloral nectaries affects neighbour plants. [•] Nectar availability of Inga trees increased parasitism rate of coffee leafminer. [•] Nectar availability of Inga trees decreased coffee damage. [•] Inga trees might be a good strategy to enhance natural pest control in coffee crops. [ABSTRACT FROM AUTHOR]

The coffee leaf miner, Leucoptera coffeella, is the most important pest of Coffea arabica plantations in Brazil, and all cultivars are susceptible to the insect. However, distinct reactions have been observed in other species, such as C. congensis and C. canephora. In this work, the occurrence of antixenotic response was surveyed in individuals of Coffea species, selected for resistance to the leaf miner at both field and laboratory conditions. Tests performed on young plants from C. arabica cultivars Icatu Precoce IAC 3282, Mundo Novo IAC 515-20, Tupi IAC 1669-33 and Catuaí Amarelo IAC 62 demonstrated that these were preferred for oviposition when pooled with seedlings from C. canephora cv. Apoatã IAC 2258. Apoatã was also preferred over C. racemosa for oviposition. Similar results were observed in tests using detached leaves, and higher amount of eggs was counted in the cv Obatã IAC 1669-20 and Catuaí Vermelho IAC 81, and lower oviposition frequency was observed in C. canephora cv. Guarini IAC 1598. C. congensis showed an oviposition frequency between C. arabica and C. canephora. Also, the results suggest that the frequency of oviposition is co-related with the plant resistance level, during larvae infection. [ABSTRACT FROM AUTHOR]

The coffee production is an economic mainstay for many countries in the world. Brazil is the world's largest producer and exporter of coffee, being responsible for about 25% of the world production. It is well known that coffee plantations are susceptible to more than 850 fungal and insect pests. Among these pests, the most important significant throughout Brazil is the coffee-leaf-miner, [Leucoptera coffeella (Guérin-Mèneville & Perrottet, 1842) (Lepidoptera: Lyonetiidae)]. It is estimated that the loss in yield due to infestation by L. coffeella moths can increase to as much as 80% in areas where the coffee-leaf-miner larvae are not controlled. Though it is effective, the chemical control of the pest substantially increases the cost of production and constitutes a risk to the environment. The knowledge about the spatial-temporal dynamics of coffee-leaf-miner and predatory wasps may provide valuable information about the biological management pest context. One way to investigate the spatial-temporal synchronism of predator and prey is to calculate and compare an index of spatial randomness within a sequence time. This paper advocates using the Morisita's index, coupled with the bootstrap method, in a temporal sequence to characterize the spatial- temporal dynamics of coffee-leaf-miner and predatory wasp (Hymenoptera: Vespidae) in one hectare of an organic coffee plantation. The results showed that coffee-leaf-miner and predatory wasps presented a seasonal behavior with a temporal synchronism. The results also showed that both new and preyed mines were aggregated during the peak population (dry season). There was little evidence for space-time interaction between coffee-leaf-miner and predatory wasps. [ABSTRACT FROM AUTHOR]

Only few factors influencing pest populations can be studied in the laboratory, but many population-driving factors interact in the field. Therefore, complementary laboratory and field approaches are required for reliable predictions of real-world patterns and processes. Laboratory and field experiments with the red spider mite, Oligonychus ilicis McGregor (Acari: Tetranychidae), and the coffee leaf miner, Leucoptera coffeella Guérin-Méneville (Lepidoptera: Lyonetiidae), on coffee plants, Coffea arabica L. (Rubiaceae), were combined to study the relative importance of biotic interactions, including resource preferences and natural-enemy impact, and habitat factors, such as agroforestry type and management intensity, on coffee pest densities. In the laboratory, leaf discs cut from undamaged coffee plants were significantly preferred by red spider mites over those from plants infested with conspecific mites, leaf rust pathogens [ Hemileia vastatrix Berkeley & Broome (Uredinales)], or coffee leaf miners, resulting in higher reproductive success. Similarly, undamaged plants were preferred by coffee leaf miners over red spider mite-infested plants. However, in the field, red spider mite densities were positively correlated with coffee leaf miner and leaf rust densities, thereby contrasting with laboratory predictions. Hence, our study suggests that the importance of resource preferences and fitness expected based on laboratory experiments was suppressed by environmental conditions in the field, though other unassessed biotic interactions could also have played a role. Furthermore, intensified agroforestry was characterized by higher red spider mite densities, whereas densities of its major natural enemy, the predatory mite Amblyseius herbicolus Chant (Acari: Phytoseiidae), were not related to agroforestry management. Densities of coffee leaf miner and its main natural enemy, a eulophid parasitoid (Hymenoptera), were not affected by management practices. In conclusion, patterns found in the laboratory did not hold for the field, emphasizing the difficulties of extrapolating small-scale experiments to larger spatial scales and the need to combine both approaches. [ABSTRACT FROM AUTHOR]

• Ceraeochrysa cubana larvae successfully prey on coffee leaf miner (CLM) eggs. • Second and third instar of C. cubana larvae prey on CLM larvae and pupae. • The predator C. cubana is a candidate for biocontrol programs of CLM. Coffee leaf miner (CLM), Leucoptera coffeella, is a key pest of unshaded coffee in hot, dry neotropical production areas. Control is hampered by CLM mining behavior that reduces biological control and pesticide efficacy. Therefore, finding natural enemies that can efficiently control CLM could improve conservation and augmentative biological control practices, and potentially reduce reliance on increasingly ineffective insecticide applications. The green lacewing Ceraeochrysa cubana is a generalist predator often found in coffee crops in Brazil, but there is little information regarding its potential contribution to CLM control. We investigated whether C. cubana preys on immature stages of CLM and whether predation levels vary according to life stage of C. cubana or CLM. First, second and third instar C. cubana readily consumed CLM eggs, but once inside mines, few CLM larvae were consumed. Second and third instar C. cubana successfully preyed on CLM pupae, but first instars did not. Thus, all three instars of C. cubana were able to prey on at least one immature stage of CLM, with potential to impede mine formation and adult emergence. [ABSTRACT FROM AUTHOR]

• Coffee leaf miner damage is positively correlated with ants in coffee farms. • Anoline lizards are potential predators of the miner but are deter by the ants. • Lizards are negatively correlated with ants at the level of a patch. • This is a trait-mediated interaction that can influence coffee leaf miner damage. Complexity and contingency frame much of current thinking in population and community ecology. The coffee pest, Leucoptera coffeella, is particularly problematical in Puerto Rico, but is usually held under control in Mexico. A variety of arboreal ants are effective predators in Mexico, but are limited in an indirect fashion by the common aggressive arboreal ant, Azteca sericeasur. In Puerto Rico this species does not occur, suggesting that the small arboreal ants might be more effective predators there than in Mexico. However, the contingency of large population densities of Anoline lizards is well-known as a major biological control force for the leaf miner. Ants, especially the non-native Wasmannia auropunctata, have a negative effect on the lizards. Surveying ants and coffee leaf miners in 25 coffee farms in Puerto Rico, we investigate the effect of ants, in particular W. auropunctata, on the coffee leaf miner, and find that this ant species has a positive relationship with the miner. In a more detailed spatial study of two farms, surveys of anoline lizards show no significant negative relationship between the lizards and W. auropunctata on a per plant basis. However, we found a significantly lower abundance of lizards on patches dominated by this ant, suggesting that W. auropunctata indirectly protects the coffee leaf miner against this potential lizard predator. Thus, the structural complexity of a trait-mediated indirect effect occurs both in Mexico and Puerto Rico and potentially limits the effectiveness of biological control elements, but the contingencies are distinct in the two sites. [ABSTRACT FROM AUTHOR]

An expeditious three-step synthesis of a mixture of stereoisomers of 5,9-dimethylpentadecane 1, the sexual pheromone of the coffee leaf miner Leucoptera coffeella, is described. The route employs an unsymmetrical double Wittig olefination to build the carbon skeleton of the molecule, as the key reaction. The bis-phosphonium salt 3, derived from 1,3-dibromopropane 2, reacted ‘one-pot’ with the ketones 2-octanone and 2-hexanone, affording the asymmetric diene 4. This was readily hydrogenated over Pd/C, furnishing pheromone 1 in 54% overall yield. Synthetic 1 showed high biological activity when tested in field experiments. [Copyright &y& Elsevier]