Video Digitizer for the Rapid Measurement of Leaf Area Lost to Herbivorous Insects1 (original) (raw)
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BioLeaf: a professional mobile application to measure foliar damage caused by insect herbivory
Soybean is one of the ten greatest crops in the world, representing a billiondollar businesses every year. This crop suffers from insect herbivory that costs millions from producers. Hence, constant monitoring of the crop foliar damage is necessary to guide the application of insecticides. However, current methods to measure foliar damage are expensive and laboratorial, in some cases, depending on complex devices. To cope with these shortcomings, we introduce an image processing methodology to measure the foliar damage in soybean leaves. We developed a non-destructive imaging method based on two techniques, Otsu segmentation and Bezier curves, to estimate foliar loss in leaves with or without border damage. We instantiate our methodology in a mobile application named BioLeaf, which is freely distributed for smartphone users. We experimented with real-world leaves collected from a soybean crop in Brazil. Our results demonstrated that BioLeaf achieves foliar damage quantification with precision comparable to that of human specialists. With these results, our proposal might assist soybean producers, reducing the time to measure foliar damage, reducing analytical costs, and defining a commodity application that is applicable not only to soy, but also to different crops such as corn, cotton, rice, wheat, oat, potato, coffee, sugarcane and vegetables.
Journal of Applied Entomology, 2003
Qualitative or semi-quantitative visual assessments are most often used for estimating population size of herbivorous insects. The precision of these estimates, however, is often difficult to establish. A Ôsimulation gameÕ with the horse chestnut leafminer, Cameraria ohridella Deschka & Dimic (Lep., Gracillariidae) shows that visual, semiquantitative assessments can provide accurate information. Damaged areas of 411 horse chestnut leaves collected in 100 sites were closely related to mine numbers despite some variability in mine and leaf size (R 2 ¼ 0.915; n ¼ 411; P < 0.001). On the basis of this relationship, two methods of population assessment are compared: (i) digital image processing of leaf damage and (ii) visual assessment using a damage key reflecting the relative infested area on each leaf (0, 0%; 1, 0-2%; 2, 2-5%; 3, 5-10%; 4, 10-25%; 5, 25-50%; 6, 50-75%; 7, 75-100%). Both methods used to estimate damage presented a similar, close relationship to the ÔrealÕ numbers of mines (R 2 ¼ 0.858; n ¼ 777; P < 0.001 for image processing and R 2 ¼ 0.905; n ¼ 777; P < 0.001 for visual assessment). The potential of using visual assessments as an accurate and fast method in situ at the tree scale is discussed.
LeafByte: A mobile application that measures leaf area and herbivory quickly and accurately
In both basic and applied studies, quantification of herbivory on foliage is a key metric in characterizing plant-herbivore interactions, which underpin many ecological, evolutionary, and agricultural processes. Current methods of quantifying herbivory are slow or inaccurate. We present LeafByte, a free iOS application for measuring leaf area and herbivory. LeafByte can save data automatically, read and record barcodes, handle both light and dark colored plant tissue, and be used non-destructively. We evaluate its accuracy and efficiency relative to existing herbivory assessment tools. LeafByte has the same accuracy as ImageJ, the field standard, but is 50% faster. Other tools, such as BioLeaf and grid quantification, are quick and accurate, but limited in the information they can provide. Visual estimation is quickest, but it only provides a coarse measure of leaf damage and tends to overestimate herbivory. LeafByte is a quick and accurate means of measuring leaf area and herbivory...
Behavioral Ecology and Sociobiology, 2017
Cry for help' hypothesis predicts that attraction of predators with chemical or visual cues can decrease insect damage of plants. Visual cues involve changes in photosynthetic activity and the reflectance of leaves, and there is some evidence that birds may use these changes as foraging cues. However, changes in the visual properties of leaves have not been quantified and it is not known how birds see these changes. We also presented and tested a new 'reduction in camouflage' hypothesis (not mutually exclusive with 'cry for help') stating that herbivore-mediated changes in leaf colour can increase the conspicuousness of herbivore against leaves. To define changes in the visual properties of leaves, their detectability to birds, and whether these changes affect the conspicuousness of herbivore, we manipulated the level of herbivory in silver birch trees (Betula pendula) with autumnal moth (Epirrita autumnata) larvae, and used blue tit (Cyanistes caeruleus) vision models to images of leaves and larvae. Hue, luminance (lightness), contrast, light transmission, chlorophyll content, photosynthetic activity and water content of the leaves were compared between herbivore-damaged and control trees. The leaves of herbivore-damaged trees had a decreased chlorophyll a concentration, increased contrast and they reflected more longer wavelengths. However, these changes are likely not obvious to birds. In contrast to our expectation, there were only minor differences in conspicuousness of larvae against the leaves of damaged trees, which may be very subtle to predator vision. Nevertheless, according to visual models, larvae should be easily detectable to birds from both herbivore-damaged and control trees. Keywords: trophic interactions, avian vision model, background matching, herbivory, camouflage Significance statement Herbivory affects photosynthetic machinery and light reflectance of leaves, and may thus provide visual foraging cues to birds, although it is not known how these changes appear to birds. We also hypothesised that the changes in leaves may reduce the camouflage of the herbivore. After applying herbivoretreatment and using the avian vision models, we found that the leaves of herbivore-damage may cause the leaves to appear to birds with higher contrast and greener or a more yellowish colour than control leaves. In addition, although the herbivore was visible to birds, it was slightly less conspicuous when on damaged trees, indicating that the herbivore can be adapted to changes in the food plant. Our results indicate that herbivory causes changes visual properties of leaves, but these changes are likely not obvious to birds. 'Reduction in camouflage' could thus work independently from 'cry for help', although they can also share plant physiological mechanisms, if the cry for help is mediated by vision. To study the effects of herbivory on the visual properties of leaves, we manipulated herbivoredamage in silver birches (Betula pendula) by adding leaf-chewing autumnal moth larvae (Epirrita autumnata) on the experimental trees. We applied an avian vision model of blue tit (Cyanistes caeruleus) to investigate whether herbivory causes optical changes in the leaves that may be visible to birds and whether these changes make the larvae potentially more detectable. In addition to using visual models, chlorophyll concentration, fluorescence induction (i.e. indicators of photosynthesis), light transmission, and water content of the intact leaves of herbivore-damaged and undamaged control trees were measured. Methods Study system Silver birch is one of the most common deciduous trees in Finland and it is a host to several insect species (Koponen 1983; Heimonen et al. 2015), including the autumnal moth. Because the autumnal moth is a common generalist (Silvonen et al. 2014), its camouflage may provide intermediate matching to several backgrounds, instead of close matching to a single host plant species (Merilaita et al. 1999; Houston et al. 2007), although to human eyes the larvae closely resemble the leaf colour of many deciduous species
Do They Ever Come Back? Responses of Leafhopper Communities to Extensification of Land Use
Journal of Insect Conservation, 2005
We studied leafhopper communities in meadows subject to progressive extensification of land use, particularly (i) delay of the first cut, (ii) cessation of fertilising and (iii) reduction of cutting events. Within a gradient from conventionally used high-productivity meadows (as control) through our extensified plots to extensively managed wet hay meadows (as control), we found an increasing species number correlated with extensification of land use. However, a separate analysis of generalists and specialists showed that the latter group increased significantly whereas generalists did not respond at all. Even after 12 years of extensification there was only little evidence for the recovery or recolonisation of former hay meadow insect communities. Instead the increase in species numbers was rather due to immigration of more xerophilous or mesophilous species. We conclude that leafhoppers principally respond positively to extensification of land use, but that restoration of former moisture conditions is necessary in order to achieve a full recovery of original hay meadow communities. Finally we propose a model extensification ecogram for meadow leafhoppers which can be used as a predictive tool for extensification and as an indicator of restoration progress and success. During the 1970s and 1980s, some European governments developed conservation programs to Journal of Insect Conservation (2005) 9:319-333
A Web Service for Assessing Insect Abundances for Meadow Birds by Image Analysis
biorxiv, 2019
Meadow birds are a group of species native to the Netherlands characterized by breeding in meadows that has been in decline over the last several decades, despite widespread conservation efforts. Agricultural intensification is thought to be one of the main causes of this decline, but no yearly data exists on the surrounding ecology of these birds. Recent efforts have tried to assess the food supply of meadow birds by setting sticky traps and counting the number of insects caught on them. However, this approach cannot be applied on a large scale since counting the insects is very labour intensive and unappealing to the volunteers that contribute to this research. To get a better assessment of the food supply at a larger scale, we present a system to automate counting of insects on sticky traps. The system is intended to process uploaded images and metadata using computer vision techniques to determine the number of insects found in photographs taken from the sticky traps.