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Biostimuatori su (ne-hranjive) tvari ili mikroorganizmi koji pospješuju procese hranidbe biljaka i doprinose smanjenju posljedica stresa uzrokovanog abiotičkim i biotičkim čimbenicima. Mogu biti mikrobni (korisne bakterije i gljive) i nemikrobni (huminske kiseline, aminokiseline, ekstrakti morskih algi, kitozan i anorganski biostimulansi). Različitim mehanizmima djelovanja biostimulatori potiču učinkovitije iskorištavanje hraniva, otpornost biljaka na stres i povoljno djeluju na kvalitativna svojstva biljaka. Uslijed restrikcija u primjeni sredstava za zaštitu bilja i gnojiva, kao dio alternativnih rješenja pojavljuju se biostimulatori., Biostimulants are (non-nutrient) substances or microorganisms that improve plant nutrition processes and help reduce the effects of stress caused by abiotic and biotic influences. They can be microbial (beneficial bacteria and fungi) and non-microbial (humic acids, amino acids, seaweed extracts, chitosan and inorganic biostimulants). Through their various mechanisms of action, biostimulants enhance the efficiency of nutrient utilization, the stress resistance of plants and have a positive effect on the qualitative characteristics of plants. Due to the limitation of applicable pesticides and fertilizers, biostimulants are also a part of the alternative solutions.

Heteroptera species are a growing problem in the cultivation of horticultural crops, and intensive chemical control of these pests is not sustainable. Therefore, natural products are used in sustainable pest management. We investigated the potential of aqueous coffee and caffeine extracts in the control of three heteropteran species Nezara viridula (L.), Halyomorpha halys (Stål), and Corythucha ciliata (Say). The Soxhlet extraction method was used to prepare the aqueous coffee extracts. Contact efficacy was evaluated by spraying the pests with the aqueous extract of coffee and the aqueous solution of pure caffeine. Significant efficacy of coffee and caffeine standard was found for control of adult H. halys (97% coffee ; 83% caffeine) and adult C. ciliata (47% coffee ; 70% caffeine). Low efficacy was observed for control of N. viridula nymphs (33% coffee ; 28% caffeine), while no insecticidal efficacy was observed for adult N. viridula. There was no statistically significant difference in efficacy between coffee extract and caffeine standard, suggesting that these caffeine levels are sufficient for pest control, while the influence of other various compounds in coffee extract (e.g., polyphenols) could not be detected. This study opens a perspective for the production of natural plant extracts using only water as the extraction medium for pest control.

Box tree moth (Cydalima perspectalis, Walker) is an invasive species present in Croatia since 2012 where causes great damage to plants of the genus Buxus. The pest spreads rapidly, has high reproductive potential and good adaptability. Its known natural dispersal velocity is up to10 km per year. Understanding flight characteristics of insect pests is essential for designing effective strategies and programs for their management. The aim of this study was to assess flight propensity of C. perspectalis and to evaluate its invasive character using flight mill technology. C. perspectalis flew a maximum distance of 15.6 km (virgin females) and spent a maximum time in flight of 241 minutes (4 hours). The average speed of C. perspectalis ranged from 1.1 m/s to 1.6 m/s. Knowledge of C. perspectalis wing characteristics and flight performances are of great importance in assessing dispersal and provide important insights into migratory activities.

The Mediterranean fruit fly (Ceratitis capitata, Wiedemann) is an invasive and quarantine pest, infesting more than 360 different plant species in tropical, subtropical, and Mediterranean climates. It originated in warm regions of Africa and has been causing significant damage in Croatia since the 1950s. Initially, the Mediterranean fruit fly was found exclusively in citrus growing areas and posed a greater threat especially to growers in the Neretva region. Today, the pest is widespread along the entire Adriatic coast and is sporadically found on the mainland as well. In Croatia, it causes the greatest damage and economic losses in the cultivation of mandarins, but its presence has also been noted in the cultivation of peaches and figs, which it also severely damages. The aim of this work was to determine the variability of populations of the Mediterranean fruit fly based on wing shape, from different hosts (peach, fig and mandarin) from different cultivation areas in the Republic of Croatia. Through variability and assessment of phenotypic plasticity, which determines the invasive character of the pest, geometric morphometrics methods were to be used to determine the potential for adaptation and future spread of the pest to new areas and new plant hosts. The study tested 10 different populations from peach, fig, and mandarine, as well as a sterile population grown under laboratory conditions. It was found that the hosts in which the Mediterranean fruit fly develops influence the shape of the wings, i.e., condition their variability. In addition, high phenotypic plasticity was found, which is a prerequisite for the invasiveness and spread of the Mediterranean fruit fly to new areas and new hosts in the future.

Fireflies (Coleoptera: Lampyridae) are among the most charismatic of all insects. With more than 2000 species in 100 genera, the worldwide diversity of lampyrids is impressive and includes both diurnal and nocturnal species. Fireflies, like numerous other insects, have experienced a worldwide decline in their distribution and abundance. Currently, 64 species of fireflies are known in continental Europe. In Croatia, seven species have been described and voucher specimens are kept in natural museums in Zagreb, Split and Varaždin. The last revision of fireflies in Croatia was made by Mikšić in 1986, who stated that the common firefly, Lampyris noctiluca (Linnaeus, 1767), L. zenkeri Germar, 1817 and L. lusitanica Motschulsky, 1854 occur in Croatia. L. noctiluca is the most common of the three species and is widespread on the Croatian mainland, while it is rare in coastal areas. After a detailed analysis of the evidence from the Citizen Science Project “Krešo Krijesnica”, the following four species of fireflies were identified in the Republic of Croatia: L. noctiluca, Lampyris germariensis (Jacquelin du Val, 1860), Lamprohiza splendidula (Linnaeus, 1767), Luciola italica (Linnaeus, 1767). Identification was based on the color of the emitting light and the appearance of the luminescent organ. The most important morphological characteristics and identification keys will be presented at the symposium.

The effectiveness of pest control depends on monitoring methods, most of which are outdated and irrelevant. For example, the pear leaf blister moth (Leucoptera malifoliella (O. Costa, 1836)) is an important apple pest whose larvae damage leaves. Its monitoring is done with pheromone traps, which are time-consuming to inspect and may result in delayed pest control. The most effective time for its control is an early stage of damage occurrence (mines), which is difficult to detect with classical monitoring techniques. Artificial neural networks (ANN) have recently been used for pest monitoring. Therefore, the aim of this study was to develop automatic systems for monitoring pear leaf blister moth and its damage using ANNs. The two ANNs were trained to detect the pear leaf blister moth and its damage using photographs collected in three apple orchards in Zagreb County. The model was developed for use in two prototype smart monitoring devices (pest monitoring device and vegetation monitoring device). The model was tested and the results were processed using a confusion matrix. The developed models showed high accuracy and precision in detecting pear leaf blister moth and its damage, while the monitoring devices showed good functionality in apple orchards. The developed system is effective for automatic monitoring of pear leaf blister moth and its damage, and therefore can significantly improve pest control and apple production in general.

U suvremenom uzgoju jabuke teži se primjeni inovativnih tehnologija kojima bi se optimizirala proizvodnja, te smanjio ljudski rad. Korištenjem digitalnih RGB kamera kao uređaja za prikupljanje vizualnih podataka (fotografija) voćari bi na vrijeme otkrili potencijalne probleme u nasadu te poduz preventivne i pravovremene agrotehničke, odnosno pomotehničke zahvate u cilju ublažavanja potencijalnih problema i smanjenja troškova proizvodnje. Obradom prikupljenih fotografija u progra za anotiranje stvorit će se ulazna baza podataka za strojno učenje. Strojno učenje dio je umjetne inteligencije bazirano na dubokom učenju (deep learning), odnosno korištenju umjetnih neuronskih mreža. Inovativni rezultat ovog projekta bit će sustav sačinjen od niza hardverskih i softverskih elemenata objedinjenih u jedinstvenu funkcionalnu cjelinu. Osnovni hardverski i softverski element čine autonomni robot-rover, različite vrste kamera s obzirom na namjenu i centralni web portal s pripadajućom mobilnom aplikacijom. Za svaku od pojedinih vrsta kamera bit će razvijeni zasebni analitički modeli koji će obrađivati fotografije unutar samih kamera. Kamere postavljene na robot rover u analitičkoj obradi fotografija imat će podršku TPU-a (Tensor Processing Unit) u svrhu brže obrade fotografija s obzirom na brzinu kretanja robot- rovera. Robot-rover bit će potpuno autonoma s obzirom na prethodno definiranu rutu kretanja po voćnjaku te neće imati potrebe za intervencijom čovjeka tijekom vegetacijske sezone. U sustavu će se definirati prepoznavanje 40-ak različitih vrsta pojava (nedostaci hraniva, simptomi napada bolesti i štetnika, morfološke i fiziološke promjene na plodu i listu jabuke i dr.). Primjena ovakvih inovativnih tehnologija vodi do značajnog unaprjeđenja optimizacije proizvodnje jabuke.

The Mediterranean fruit fly (Ceratitis capitata (Wiedemann 1824)) is considered one of the most significant tephritid fruit fly species worldwide. Its specific adaptive biology, invasive character and climate change have a very favorable effect on the establishment of its populations in new areas. Understanding the physiology and dispersal of Ceratitis capitata provides us with information on how certain variants spread their alleles across large-scale agricultural landscapes. The main objective of this study was to determine the variability in energetic traits of C. capitata evolved from three favorable host plants (peach, fig and mandarin) from different agroecological production areas. The wings and pronotum of each C. capitata from ten populations were dissected and mounted on slides using standard preparation techniques. The length (mm), width (mm) and area of the wings (mm) and the width of the pronotum (mm) of the C. capitata populations were measured. Aspect ratio was calculated as wing span2/wing area. The wing geometry and aspect ratio of ten C. capitata populations were calculated. Application of these methods provides a better understanding of the physiology and dispersal capabilities of C. capitata, including the potential for dispersal of this invasive species over large geographic distances.

Smeđa mramorasta stjenica (Halyomorpha halys Stål, 1855) je invazivna vrsta porijeklom iz Azije. U Hrvatskoj je zabilježena 2017. godine, a posljednjih godina bilježi se porast populacije i širenje štetnika u ratarskim usjevima i višegodišnjim nasadima. H. halys je izuzetno polifagna vrsta, a ekonomske štete u proizvodnji poljoprivrednih kultura iz porodica Rosaceae i Fabaceae već su zabilježene u nama susjednim državama (Sloveniji i Mađarskoj, te Italiji). Stoga, pouzdano praćenje štetnika u realnom vremenu korištenjem automatskih sustava za praćenje može pridonijeti ranoj detekciji i sprečavanju širenja vrste na nova područja. Zahvaljujući ključnim tehnološkim konceptima računalnog vida i umjetne inteligencije, ovakvi sustavi uz brzu detekciju pridonose pravovremenom suzbijanju štetnika, te smanjenoj upotrebi pesticida. Monitoring vrste H. halys korištenjem automatskih sustava za praćenje je u začetcima, a na tržištu se može pronaći samo jedan tip tzv. pametne lovke. Stoga se u sklopu ‘’AgriART‘’ projekta razvija model za automatsko praćenje smeđe mramoraste stjenice. Model se razvija stvaranjem ulazne baza podataka s fotografijama snimljenih pomoću RGB (red-green-blue) kamere u poljskim uvjetima, a metodom prepoznavanja Convolutional neural network (CNN), sustav detektira štetnika. Takav sustav trebao bi uvelike olakšati ranu detekciju i suzbijanje ove invazivne vrste, te na taj način spriječiti njezino brzo širenje i pridonijeti održivoj poljoprivrednoj proizvodnji u Hrvatskoj.

Morphological variation can affect the ability of species to disperse and adapt to new areas. Geometric morphometric methods are valuable tools for assessing the extent of phenotypic changes influenced by genetic variation. Such methods were used in this study to determine the morphological variability of the box tree moth Cydalima perspectalis, Walker from Croatia and to assess its invasive character. Box tree moth is an invasive species that spreads rapidly, has high reproductive potential, and is highly adaptable. A cross-site analysis was conducted, and the dataset was partitioned by geographic area, with the intraspecific variation found independently between northern and southern populations. Results indicate that wing shape is influenced by agroecological factors, with forewings being more plastic than hindwings. Northern populations have broader wings, while southern populations have more elongated wings. Wing characteristics of box tree moths are of great importance in assessing their spread, especially given their high invasive potential. Using this innovative and effective, yet simple and inexpensive method, we can detect differences in wing shape and size and use these differences as biomarkers of variation between and within populations. These results suggest that geometric morphometric methods can be used to study the biological adaptation of box tree moths in native and newly invaded areas.

Jabukov savijač (Cydia pomonella L.) ekonomski je štetnik koji uzrokuje velike gubitke u proizvodnji jabuke. Zbog ekonomske važnosti jabuke (Malus domestica Borkh.) širom svijeta, tržište zahtjeva proizvodnju visokokvalitetnog voća bez prisutnih šteta od jabukovog savijača. Jabukov savijač razvija jednu do četiri generacije godišnje ali zbog klimatskih promjena zabilježen je neočekivani porast populacije i broja generacija štetnika. U suzbijanju štetnika, proizvođači obično učestalo primjenjuju insekticidne tretmane koji uzrokuju razvoj rezistentnosti štetnika i opterećuju finalni proizvod, okoliš i druge ne ciljane organizme agrokemikalijama. S obzirom na navedeno, mnogo je razloga za korištenje sofisticiranijih tehnika praćenja štetnika koje bi poboljšale njegovo suzbijanje. Cilj ovog istraživanja je razviti sustav za automatsko praćenje i ranu detekciju jabukovog savijača korištenjem RGB kamere. Tijekom razdoblja leta jabukova savijača u 2022. godini prikupljeno je 140 fotografija štetnika, na kojima je kasnije anotirano 4000 jedinki vrste. Na temelju 90% anotiranih fotografija trenirana je konvolucijska neuronska mreža. Rezultati su pokazali da analitički model detektirao jabukovog savijača s 80% točnosti, što je potvrđeno korištenjem preostalih 10% anotiranih fotografija. Razvojem ovog pametnog sustava, proizvođači će moći učinkovitije pratiti te pravovremeno detektirati jabukovog savijača što će poboljšati suzbijanje štetnika, a time i proizvodnju jabuke.

Background: The Mediterranean fruit fly or medfly, Ceratitis capitata (Wiedemann) is one of the most economically important fruit flies globally. Its development depends on the geographic area, climatic conditions, and availability of host plants. Given its cosmopolitan distribution, invasive nature and its abundance and ability to thrive in numerous environments, medfly is an ideal model species to investigate the effects of environmental factors on size and shape variation. Geometric morphometrics (GM) can provide valuable information on phenotypic variability and population structure. Using geometric morphometric tools, the size and shape of the wing can be analysed independently to untangle biological patterns related to heritability and environmental sensitivity. Methods: Adult medfly populations were developed from peach that was infested in the field from two Croatian locations with different agroecological conditions and different pest management practices. First, Podstrana with conventional pesticide control and second Opuzen with sterile technology avoiding the use of pesticide. Wings of each fly were removed and laterally fixed according to the standard methods for subsequent morphometric analysis. On each medfly wing, 14 landmarks were placed at the nodes or ends of the veins. To distinguish between sexes and populations, a principal component analysis (PCA) was performed using the covariance matrix of the individuals’ wing shape and differences corroborated by a Procrustes ANOVA. A multivariate regression was performed to analyse whether there was an effect of size on wing shape (Allometry). Results: Results shown significant differences between medfly sexes and populations where shape variation was analysed independently by sex. The female medflies have more elongated and larger wings compared to the males. These wings are more aerodynamic and less prone to flight damage. This allows the females to fly more frequently and for longer periods of time, making them responsible for dispersal into new areas. Wing size and shape differ among populations with significant differences between agroecological systems and pest management practices. Conclusion: Wing size and shape showed variations between different agroecological systems suggesting metapopulation structure of medfly which is currently favouring sex-specific plasticity. These results show that geometric morphometric procedures can be used to provide key insight into the biological adaptation of medfly in newly invaded habitats, a significant process that ensures invasion success.

Box tree moth (Cydalima perspectalis, Walker) is an invasive species present in Croatia since 2012 where causes great damage to plants of the genus Buxus. The pest spreads rapidly, has high reproductive potential and good adaptability. Its known natural dispersal velocity is up to10 km per year. Understanding flight characteristics of insect pests is essential for designing effective strategies and programs for their management. The aim of this study was to asses wing shape variability, flight propensity and of C. perspectalis and to evaluate its invasive character using geometric morphometric methods and flight mill technology. An inter-sites analysis was performed, and the dataset was divided by geographic area, with intraspecific variation detected independently. Results show wing shape influenced by agroecological factors, with forewings found to be more plastic than hindwings. In terms of sexual differentiation, multivariate regression of wing shape revealed minimal differences between male and female forewings, yet female wing shapes were more variable and covered a large percentage of the shape space. C. perspectalis flew a maximum distance of 15.6 km (virgin females) and spent a maximum time in flight of 241 minutes (4 hours). The average speed of C. perspectalis ranged from 1.1 m/s to 1.6 m/s. Knowledge of C. perspectalis wing characteristics and flight performances are of great importance in assessing dispersal and provide important insights into migratory activities.

Excessive use and application of agrochemicals in current agricultural production has had a devastating influence on nature, the environment, and human health, as well as being a source Q8 of a variety of pollutants. To limit the use of agrochemicals, it is required to use and apply them in predetermined quantities and with a level of responsibility, while simultaneously beginning to use new approaches in the process of plant nutrition and protection for the development of functional foods. A deeper understanding of the impacts of novel chemicals in plant nutrition and plant protection processes, as well as their market worth, is required to achieve this.

Background: Olives have been cultivated in the Mediterranean region and in Croatia for more than 2, 500 years. Croatia has extremely favourable conditions for olive cultivation, and indigenous varieties and those introduced from Italy are grown on an area of 18, 600 hectares. Olive cultivation, and thus the production of quality olive oil, is limited by pests, the most important of which is the olive fruit fly. Olive varieties differ in their susceptibility to this pest, and 60 varieties are grown in Croatia. Methods: The susceptibility of two indigenous (Oblica and Istarska bjelica) and four varieties introduced from Italy (Ascolana Tenera, Frantoio, Leccino and Pendolino) to olive fruit fly infestation was investigated at two important cultivation sites in Croatia (Vodnjan and Benkovac). Three trees of each cultivar were selected, and 100 olive fruits were collected from each tree. The fruits were first visually inspected for olive fruit fly infestation and then prepared for pest development monitoring according to a standardised protocol. Pest development was monitored weekly. Results: The olive grove in Vodnjan had a significantly higher percentage of fruit infested with olive fruit fly. Most flies developed in the fruits of the indigenous Istrian variety Istarska bjelica (145 specimens), while the second most infested variety was the Italian variety Frantoio (119 specimens). The varieties Oblica, Ascolana Tenera and Pendolino had the same number of flies (75 - 79 specimens), and the small-fruited variety Leccino had the lowest number of flies (70 specimens). In the olive grove of Benkovac, the intensity of olive fruit fly infestation was much lower, and in this area the Ascolana Tenera variety was the most frequently infested (59 specimens), followed by Leccino (47 specimens). The varieties Pendolino, Oblica and Istarska bjelica were about equally frequently infested (26 - 39 specimens), and the variety Frantoio was the least infested (12 specimens). Conclusion: Varieties with large fruits (Ascolana Tenera) and varieties with long ripening period (Istarska bjelica and Frantoio) are more susceptible to olive fruit fly infestation than other varieties. Favourable climatic conditions for olive fruit fly development in the study areas and insufficient pest control measures in Vodnjan also contributed to the heavy infestation. Cultivation of the varieties Istarska bjelica and Ascolana Tenera is threatened by this pest in the studied areas.

In view of the increasingly evident climatic changes that affect nature, natural processes and, consequently, all human activities on Earth, which, of course, includes agricultural production as food production factory in openfield, arises the need to apply new techniques and technologies in a modern fruit production. Since we can no longer fully rely on established production processes with established production procedures/measures, it is necessary to control plantations more frequently to identify problems in production related to proper growth and development of the plant and fruit, which mainly concerns proper plant nutrition, as well as plant protection. All this requires additional human involvement and work, and thus additional time. In modern apple growing, efforts are being made to use innovative technologies that optimize production but also reduce human work. One of these innovative technologies can be the use of RGB digital cameras [a camera equipped with a standard complementary metal-oxide semiconductor (CMOS) sensor used to take color photos of objects] as a tool for collecting data in machine learning process. The usage of RGB cameras in machine learning could provide fruit growers to detect and prevent potential damage caused by a deficiency of a particular nutrient in a timely manner. Also, it would allow them to respond in time by taking agrotechnical measures that could mitigate the harmful effects of a potential problem, reduce production costs, and thus increase profits. So, this study aims to investigate the use of the RBG camera as a non- destructive tool to detect nutrient deficiencies for building a model based on machine learning. For this purpose, 5 productive orchards were selected in which 200 images per day were taken within 5-time intervals in one day. The images were captured manually and later processed in an annotation program (LabelImg). On each individual image, all leaves were annotated and classified as either 'healthy leaf' or 'leaf deficient in nitrogen, phosphorus, potassium, calcium, magnesium, iron, zinc, or manganese'. From September 2021 to June 2022, more than 3200 images were collected and almost 7500 annotations were made regarding the nutritional apple leaf status. The most numerous class was healthy leaf with about 6000 annotations. Based on a large number of annotations, a model capable of distinguishing healthy leaves from nutrient deficient leaves will be created. Final goal will be developing software/application and constructing a robot- rover with 4 RGB cameras built-in, that would be able to drive autonomously through the orchard and providing real-time information to the fruit growers on the condition of the orchard. Such continuous monitoring with RGB cameras through the orchard could be a key factor in planning and implementing a greater number of agrotechnical and pomotechnical activities, timely application of fertilizers, rational and more effective use of human work, and ultimately better fruit quality. The application of such new technologies would significantly improve fruit production.

Apple (Malus domestica Borkh.) is one of the world's highest-yielding fruit crops. In addition to codling moth (Cydia pomonella L.), which is considered the most important apple pest, other lepidopterans, fruit flies, and true bug species also threaten production, affecting fruit quality and preventing its commercialization. Early detection and monitoring of pests is critical to preventing damage from pests. Due to new climatic conditions, the phenology of pests changes frequently and it is very difficult to predict their occurrence. Therefore, there is an increasing need to develop and use new smart technologies for pest monitoring (smart traps, sensors, etc.). Such methods can greatly facilitate site-specific management and consequently reduce the use of pesticides and their residues. The aim of this work is to provide an overview of methods for automatic monitoring of economically important apple pests in order to improve sustainable pest management in apple production.

Climate change has significant impacts on winter wheat (Triticum aestivum L.) production through the occurrence of various environmental stress parameters. In this sense, drought stress and pest infestation, especially in sensitive phenophases, are the main threats to wheat production stability and final yield loss. These stress factors lead to changes in the physiological response of winter wheat plants and can be monitored by various multi- and hyperspectral remote sensing systems (satellite, airborne, and proximal). One of the best known and most accurate methods for monitoring plant stress is proximal remote sensing. As plant responses to environmental stress are numerous and complex, their physiological effects affect the signal in different regions of the electromagnetic spectrum, such as visible (VIS), near infrared (NIR), and shortwave infrared (SWIR). Through their feeding, pests cause changes in plant pigments and cell structure, resulting in variations in VIS and NIR reflectance, while plant water content has been associated with variations in certain bands in the SWIR region of the spectrum. Picture 1. Workflow for detection and evaluation of environmental stress in crops using proximal sensing methods for precise agricultural management decisions The availability of hyperspectral data has led to the definition of vegetation indices (VI), which, by combining the values of different regions of spectrum with plant (or soil) characteristics, can quantify many agronomic variables and estimate the severity of plant stress. In addition to VI, the total spectral signature (reflectance) or its derivatives and principal components (PC) are often used to assess plant condition. Chemometric (multivariate) and machine learning models are commonly used to determine the relationship between groundthruth parameters (water content in plants/ soil, level of pest infestation, etc.) and leaf/canopy spectral characteristics. These include principal component analysis (PCA), partial least squares regression (PLSR) and principal component regression (PCR), artificial neural networks (ANN) and support vector machines (SVM).

Codling moth is a cosmopolitan pest that causes economically significant damage in apple production. The damage is visible on the fruits, which lose their organoleptic properties and market value. Therefore, the use of artificial intelligence offers a good perspective for the early detection of the pest and its damage in the field. Information and communication technology has contributed to the use of intelligent devices throughout the agricultural chain. In the context of precision agriculture, the artificial intelligence system is a comprehensive solution for the digitalization of agriculture. In practice, this system involves the creation of an information database, and in the case of pest monitoring, red-green-blue (RGB) and hyperspectral imaging cameras (HSI) can be used. These cameras record the occurrence of pests and damage in orchards. Later, these photos are processed using machine learning methods. Based on all the data, accurate models are developed to identify the target pest and facilitate monitoring and management. Inhibiting factors for the use of cameras can be the high market price, the lack of certain electronic components, and the required expertise. Nonetheless, high-precision classification models for pest monitoring represent the future of agriculture and offer a new opportunity to reduce economic losses caused by codling moth.

Climate change and extreme weather events have significant impacts on winter wheat (Triticum aestivum L.) production and its arthropod pests. Under these new climatic conditions, pest infestations are expected to be severe. Insects tend to reduce the photosynthetic activity of wheat plants and negatively affect their growth and development, ultimately leading to even greater yield losses. Inaccurate decision making in an integrated pest management program can result in ineffective control in infested areas. To achieve more effective control of pest populations, it is important to assess infestations in a timely manner to reduce the negative impact on crops. Great efforts have been made to prevent and manage these negative impacts, including remote sensing of damage symptoms. Proximal remote sensing provides a fast, accurate, non-invasive, and simple method for monitoring and assessing pest damage to various crops. The efficiency of pest monitoring in the field could be improved by knowing the solar radiation reflected from the leaves and canopies of winter wheat. Canopy and leaf reflectance is measured using a spectroradiometer in the wavelength range of 350-2500 nm on experimental crops of five winter wheat cultivars at crucial phenophases. This summary represents an ongoing research effort aimed at detecting stress caused by insect pests and evaluating stress levels in different winter wheat cultivars. Chemometric analysis of spectral response patterns is used to isolate sensitive wavelengths that indicate early signs of infestation. Results of similar studies showed that spectral reflectance of leaves in the visible (VIS, 350-700 nm) and near infrared (NIR, 700-1300 nm) range decreased with increasing aphid infestation and that there were significant differences in blue, green, red, NIR, and shortwave infrared (SWIR) between different severity levels of aphid infestation. The spectroradiometric method can also be used to test the commonly used spectral vegetation indices (e.g. NDVI, RVI, etc.) as indicators of stress in winter wheat cultivars. The results obtained made it possible to distinguish the different levels of infestation and to distinguish healthy wheat plants from insect-infested plants based on their reflectance.

Invazivne vrste štetnika i klimatske promjene predstavljaju najznačajnije ekološke probleme s kojima se svijet danas suočava. Navedeni čimbenici smatraju se prijetnjom za brojne ekosustave, posebice za osjetljivi sektor poljoprivrede. Globalno zatopljenje ima snažan utjecaj na reprodukciju, opstanak, rasprostranjenost i dinamiku populacija invazivnih štetnika, kao i na odnose između različitih vrsta kukaca, okoliša te njihovih prirodnih neprijatelja. Kao rezultat interakcije invazivnih vrsta štetnika i klimatskih promjena postoji ozbiljan rizik od ekonomskih gubitaka prinosa, kao i izazov osiguranja hrane za brzorastuće stanovništvo. Cilj je ovog rada istražiti vezu između klimatskih promjena i procesa invazije ekonomski važnih poljoprivrednih štetnika. Nedostatak kontrole sustava uvoza i izvoza roba, kao i ljudska mobilnost, doveli su do povećane introdukcije invazivnih štetnika, dok klimatske promjene reduciraju prepreke njihovom uspostavljanju i daljnjem širenju. Kako bi se ograničila ekološka i gospodarska šteta, važno je razumjeti čimbenike koji utječu na proces invazije štetnika u kontekstu klimatskih promjena. U ovom su radu istaknuti glavni biotički čimbenici koji utječu na proces biološke invazije: fenološka plastičnost i strategije prilagodbe životnih ciklusa te abiotički čimbenici koji utječu na njih. Naposljetku, predstavljen je način upravljanja invazijom poljoprivrednih štetnika, koji uključuje metode prevencije, eradikacije te ranu procjenu mogućnosti invazije štetnika korištenjem modela predikcije.

One of the most important apple pests are insects from the order of butterflies (Lepidoptera) - the codling moth (Cydia pomonella (Linnaeus, 1758), whose larvae feed on apple fruit, making it unusable for the market, and the pear leaf blister moth (Leucoptera maifoliella (O. Costa, 1836), whose larvae develop in apple leaves. Classical pest monitoring methods are unreliable and time- consuming, resulting in greater damage to apple production. The use of artificial neural networks (ANN) has recently shown great potential for pest monitoring. Therefore, the aim of this paper is to present ANNs as a pest detection tool that can be used for automatic monitoring of Lepidoptera apple pests (Figure 1). Looking at the examples from the literature where ANNs are used for apple pest monitoring and comparing their accuracy, it can be seen that all effective models for codling moth detection have an accuracy of over 90% in most cases compared to manual counts by human experts. The model for pear leaf blister moth is still pending, but since it belongs to the same order as codling moth (Lepidoptera), the model accuracy should also be high. In addition, ANNs have been used to detect damage to leaves caused by the pear leaf blister moth and also achieved high accuracy. Further development of ANNs for detection and monitoring of important apple pests is certain. Thus, this study reveals an unexplored potential for the use of ANNs in monitoring apple pests from the order Lepidoptera. Therefore, this work advocates more efficient and rapid monitoring that allows for targeted and effective pest control without unnecessary insecticide treatments and thus without negative agricultural impacts on the environment and human health.

Smeđa mramorasta stjenica relativno je novi član Hrvatske entomofaune čija se biologija i ekologija još uvijek istražuje. Vrsta je poznata po polifagnosti, a zabilježena štetnost u uzgoju ratarskih, povrtlarskih te voćnih vrsta diljem svijeta dokaz je njezine invazivnosti. Cilj istraživanja bio je utvrditi spolni dimorfizam vrste Halyomorpha halys na temelju fenotipskih karakteristika s dorzalne i ventralne strane tijela. Od svakog spola izdvojeno je 60 primjeraka stjenice. Svaka jedinka fotografirana je digitalnom kamerom s dorzalne i ventralne strane tijela, a zatim su im uklonjeni, preparirani i fotografirani prednji i stražnji par krila. Na temelju fotografija dorzalne strane tijela mjerene su vrijednosti duljine tijela, širine pronotuma, površine tijela te površine prednjeg i stražnjeg para krila. Razlike na ventralnoj strani tijela utvrđivane su vizualnim pregledom. Rezultati istraživanja pokazali su da se mužjaci i ženke značajno razlikuju u svim mjerenim vrijednostima, a spolni dimorfizam u veličini tijela kretao se u korist ženki. Navedene karakteristike (veća i snažnija građa tijela a posebice krila) čine ženke pogodnijim spolom za migratorne letove a time i odgovornim za brzo širenje populacije na nova područja. Razlike između spolova zabilježene su i u obojenosti s ventralne strane tijela. Kod mužjaka je crvena pigmentacija sternuma bila značajno više izražena u odnosu na ženke što je dodatna potvrda spolnog dimorfizma vrste u obojenosti tijela.

Posljednjih godina uočen je značajan pad broja krijesnica zbog čega je pokrenut projekt građanske znanosti ‘Krešo Krijesnica’. Trajao je od 2019. do 2021. godine, a cilj mu je bio prikupiti podatke o brojnosti i lokaciji krijesnica na području Republike Hrvatske. Građani su educirani o biologiji, identifikaciji i prikupljanju podataka. Ukupno je prikupljeno preko 1700 prijava te analizirano preko 400 fotografija i videozapisa. Obradom je identificirano preko 10.000 jedinki vrsta Lampyris noctilua, Lampyris germariensis, Lamprohiza splendidula i Luciola italica. Pregledom muzejskih zbirki Coleoptera u Hrvatskoj zabilježeno je sedam vrsta krijesnica. U zbirkama Novaka i Koče u Hrvatskom prirodoslovnom muzeju nalaze se L. germariensis, L. noctiluca, L. splendidula, L. italica, Luciola lusitanica, Lampyris zenkeri i Phosphaenus hemipterus. U zbirci Karaman u Prirodoslovnom muzeju u Splitu inventirane su L. germariensis i L. zenkeri. U zbirci Košćec Gradskog muzeja Varaždin zabilježene su L. noctiluca, L. splendidula i P. hemipterus, dok u zbirkama Prirodoslovnog muzeja u Rijeci i Prirodoslovnog odjela Muzeja Slavonije u Osijeku krijesnice nisu popisane. U Katalogu Coleoptera palearktičke regije za područje Hrvatske navodi se ukupno osam vrsta, a jedina vrsta koja nije utvrđena tijekom pregleda zbirki je Lamprohiza germari. Fauna krijesnica u Hrvatskoj nije proučavana posljednjih 70 godina i potrebno je provesti opsežna terenska istraživanja kako bi se utvrdio broj i sastav vrsta ove porodice.

Pear leaf blister moth (Lepidoptera: Lionetiidae) is an economically dangerous insect in apple orchards worldwide. During the growing season, the moth develops several generations that cause damage directly to the leaves. The larvae live inside the leaves and feed on the mesophyll tissue, causing defoliation of the leaves and later affecting bud differentiation. In more severe infestations, fruit organoleptic characteristics may also be affected. In the context of precision agriculture, the introduction of new technologies and early detection of pests through the use of automated monitoring systems for economically important apple pests can improve pest control and reduce damage to apple crops. The objective of this study is to develop an automatic monitoring system based on pear leaf blister moth detection using an RGB camera. During a period of 11 weeks, a series of 250 images were taken, and 4150 moths were annotated in the images. A convolutional neural network was trained based on 90% of the annotated images. The results showed that the analytical model trained in this way was able to identify the pear leaf blister moth with 70% accuracy, which was verified using the remaining 10% of the captured images. These preliminary results show that the system can contribute to more accurate and early detection of pests, but still needs to be improved with a larger training data set.

U suvremenoj voćarskoj proizvodnji teži se stvaranju optimalnih uvjeta za uzgoj voćaka, postizanje visokog priroda i što bolje kvalitete ploda. Klimatske promjene postale su velik problem današnjice negativne posljedice odražavaju se sve više na uzgoj voćaka, kvalitetu ploda te pojavu bolesti i šte što u konačnici utječe na ekonomsku isplativost proizvodnje. Napretkom tehnologije, detekcija kro strojno učenje ima veliki potencijal za mogućnost primjene RGB kamera u voćnjacima koje bi pom proizvođačima u ranom otkrivanju problema na točnoj lokaciji u samom nasadu. Pomoću digitalnih kamera [kamera opremljena standardnim komplementarnim metal- oksidni poluvodičkim (CMOS) senzorom putem kojeg se dobivaju fotografije objekata u boji] i strojnog učenja, voćari bi na vrijem mogli detektirati potencijalnu štetu koja može biti prouzrokovana ekonomski značajnim štetnicima, bolestima kao i vanjskim nepovoljnim utjecajima i reagirati na odgovarajući način. Provedeno je preliminarno istraživanje u kojem je izvršeno fotografiranje RGB kamerom nasumično odabranih s jabuke, prikupljanje i obrada te anotiranje fotografija u računalnom programu Labellmg gdje su ozn zdravi listovi i plodovi kao i oni zahvaćeni bolešću, štetnikom, nedostatkom hraniva, odnosno određenom deformacijom. Temeljem manjeg broja fotografija (oko 1000) i anotacija (oko 4000) po metode prepoznavanja Convolutional neural network (CNN) dobiveni su pozitivni rezultati kojima j utvrđeno kako se može prepoznati razlika između zdravog ploda i lista od onih napadnutih od stra određenog štetnika odnosno zaraženog bolestima kao i prisutnih posljedica nepovoljnih okolišnih kao što su na primjer mraz i tuča. Takav kontinuirani nadzor RGB kamerama kroz nasad mogao b ključni čimbenik u planiranju i provedbi većeg broja agrotehničkih i pomotehničkih zahvata, uštedi zaštitnih sredstava i radnih sati, a u konačnici poboljšanoj kvaliteti plodova. Primjenom ovakvih no tehnologija došlo bi do značajnog unaprjeđenja voćarske proizvodnje.

Box tree moth Cydalima perspectalis (Walker) (Lepidoptera: Pyralidae) is an invasive moth originating from East Asia and present in Croatia since 2012. Its natural dispersal velocity of up to10 km per year is of particular concern. Understanding flight characteristics of insect pests is essential for designing effective strategies and programs for their management. The aim of this research was to use a flight mill to test flight propensity, performance and flight patterns of the box tree moth. The flight-testing mill consisted of a flight mill, a testing chamber and a data logging and processing unit. Flight characteristics such as duration and number of flights as well as velocity and distance of individual flights were monitored by four flight mill chambers in a C. perspectalis population under naturally occurring conditions. In 24-hour experiments, C. perspectalis flew a maximum distance of 15.6 km (virgin females) and spent a maximum time in flight of 241 minutes (4 hours). The average speed of C. perspectalis ranged from 1.1 m/s (the slowest flying/virgin females) to 1.6 m/s (laboratory males). The performed flight- testing systems proved to be efficacious and useful tools in unveiling essential flight characteristics of invasive flying insects. Flight mills contribute to the understanding of physiological traits and provide important insights into migratory activities ; this is of particular importance for the highly invasive C. perspectalis.

Compared to other fruit fly species the Mediterranean fruit fly or medfly, Ceratitis capitata (Wiedemann) is the most important fruit fly due to its ability to survive adverse and often unfavorable conditions. It is highly polyphagous since it inhabits over 200 plants species. Medfly is quarantine pest in Croatia (A2 list). It feeds on soft and juicy fruits such as mandarin and other citrus fruits, peach, apricot, pear, apple, etc. Damage caused by this pest is severe. Tissue around oviposition injection spot changes color, spot expands over few days and tissue beneath begins to rot causing a dent on the surface. Such fruit is completely unusable and has no market value. Damages are highest in summer and autumn. Agroecological factors such as soil structure, soil pH, weather conditions and suppression measures contribute to morphological variability of medfly. Morphological variation can affect species ability to spread and adjust to new areas. Geometric morphometric procedures are valuable tools for evaluating levels of phenotypic changes influenced by genetic changes. Such procedures were used in this survey in order to estimate influence of biotic (suppression and cultivation measures) and abiotic factors (weather conditions, soil) on medfly's wing size and shape. Based on different phenotypes we investigated the impact of change in medfly wings on its ability to expand into new areas. Morphology of medfly's wings has been analyzed by standard geometric morphometric procedure based on location of 14 markers placed on insect's wing veins. This innovative and effective but yet simple and cheap method establishes differences in wings shapes and sizes allowing us to use those differences as biomarkers of inter and intra-population variation. Implication of this experiment suggests that geometric morphometric procedures can be used for population research with contribution to research of biological adaptation of medfly.

Ozone (O3) is a strong oxidant with a long history of safe use in many fields such as agricultural sector, food, textile, industrial and paper sectors, in the disinfection of water (drinking water and in the processing of waste water), etc. Environmental friendly properties are its main advantage compared to traditional pesticides and fungicides. It can be easily generated at treatment site by using only electricity and air. Therefore, O3 usage has following safety advantages over conventional pesticides: there are no residues on products or within products ; no presence of toxic chemicals ; no hazards of plant protection product mixtures ; no issues with disposal of insecticide leftovers and no disposable packaging. Insect infestation within commercial storages are a major concern for food industry. The presence of insects and their remains in grain and stored food may pose a serious health risk to humans and livestock. In most cases, in commercial storages pests are managed by a combination of different methods such as cleaning and cooling, fumigation or treatment of the stored material with contact insecticides. Available pesticides for treatment of grain and other stored products are decreasing due to environmental and safety concerns among consumers and society. Thus the need for alternative pest control methods is rising. The use of O3 is one of the potential methods although the ozone mode of action on insects is not completely known. Insect ´s respiratory system is most likely a target spot since it is a respiratory toxicant. The main goal of this investigation was to determine efficacy of ozone in the suppression of insect pests. The investigation has been conducted on seven different insect species which were in different growing stages (adults: Sitophilus granarius, Blatta lateralis, Blaptica dubia, Gryllus campestris ; larvae: Pachnoda sinuata flaviventris, Tenebrio molitor i Zophobas morio). Different exposure durations to ozonation process were tested. In addition to ozone efficacy, the walking response time and velocity of Sitophilus granarius were investigated. The results showed promising ozone effects on insects’ ability to move by slowing down response time, decreasing velocity or finally causing mortality. The highest efficiency of ozonation has been determined on adult insects’ stages while efficiency of larvae treatment had very low or no effect. Ozone efficiency increases with time of exposure. Above mentioned ozone features can be used in storage system providing a realistic choice in pest control either as a suppressant or a means of disabling movement which would ensure extended time for target application of treatment.

Američki cvrčak invazivni je štetnik zabilježen u većini vinorodnih područja Republike Hrvatske. Glavni je vektor fitoplazme Flavescence dorée koja uzrokuje bolest zlatnu žuticu vinove loze. Cilj je istraživanja bio utvrditi dinamiku ulova štetnika s obzirom na fenofaze razvoja vinove loze. Populacija cvrčka praćena je u 2018. i 2019. godini pomoću Csalomon® SZs žutih ljepljivih ploča u dvama vinogradima (Gradunje i Vrškojice) na području Svetog Ivana Zeline. U vinogradu Gradunje ulovljena su 232 odrasla štetnika, a u vinogradu Vrškojice 686 jedinka. Pojava štetnika zabilježena je nakon fenofaze cvatnje i oplodnje vinove loze, a tijekom fenofaze rasta i razvoja bobica opažena je njegova najveća brojnost. Značajan pad populacije zabilježen je u fenofazi dozrijevanja grožđa u kojoj je i završila aktivnost štetnika. Ustanovljena prisutnost i brojnost štetnika ozbiljno ugrožava uzgoj vinove loze na području istraživanja. Kako bi se spriječilo širenje zlatne žutice, ključno je prilagoditi vrijeme primjene insekticidnih tretmana dinamici ulova štetnika.

The hypothesis of this study was that different plant hosts of the medfly Ceratitis capitata may cause variability as a prerequisite for its invasiveness. The main objective was to determine population variability based on medfly wing shape in three favorable medfly host plants (peach, fig and mandarin) from different agroecological growing areas with different pest management practices, and to evaluate phenotypic plasticity as a basis for future expansion into new areas and new hosts. Using geometric morphometric methods across 14 specific landmarks on the medfly wings, 10 populations were tested from infested peach, fig and mandarin fruits, as well as laboratory- grown sterile populations. The studies led to the following main findings: (1) all of the medfly populations that were studied exhibited sexual dimorphism in wing shape ; (2) the hosts in which the medfly develops influence wing shape and condition its variability ; (3) there is significant variability between laboratory mass- reared sterile and wild individuals in male and female populations ; (4) a high phenotypic plasticity of medfly populations was observed along the study sites. Even the low but clearly detected variability between different agroecological conditions and localized variability indicate genotypic stability and high phenotypic plasticity, which can be considered as a prerequisite for medfly invasiveness and dispersal to new areas.

Klimatske promjene uzrokuju nejednoliku raspodjelu oborina, temperatura i pojavu klimatskih ekstrema širom svijeta. Brojni znanstvenici dokazali su da klimatske promjene značajno utječu na pojavu štetnih kukaca te smatraju da će one u budućnosti biti još izraženije. Globalno zagrijavanje i ostale klimatske promjene pokretači su značajnih promjena u populaciji štetnih kukaca, uključujući širenje njihovog geografskog areala, interakcije između fitofagnih kukaca i njihovih biljaka domaćina te prirodnih neprijatelja, kao i pojačanu opasnost od introdukcije invazivnih vrsta štetnika. Takve promjene mogu dovesti i do izumiranja osjetljivijih vrsta kukaca. Porast temperature utječe na pojačanu pojavu štetnih kukaca, intenzitet njihova napada kao i rast populacije, što predstavlja značajnu prijetnju za normalnu funkciju i održivost ekosustava. Navedene promjene u intenzitetu pojave štetnika popraćene su ozbiljnim ekološkim i ekonomskim posljedicama, a također mogu i umanjiti učinkovitost postojećih metoda i strategija zaštite biljnih vrsta od štetnika u raznim ekosustavima. Kako bi se ublažio rizik od negativnih posljedica utjecaja klimatskih promjena na štetne kukce, potrebno je identificirati nekoliko strategija zaštite. Te strategije uključuju: (I) identifikaciju osjetljivih područja na pojačan intenzitet napada štetnika ; (II) evaluaciju učinkovitosti postojećih strategija zaštite ; (III) uspostavljanje praćenja (monitoringa) pojave štetnih kukaca i populacijske dinamike za ranu detekciju i prevenciju njihova širenja ; (IV) razvoj modela za predviđanje promjena u interakciji između biljnih vrsta, fitofagnih kukaca i njihovih prirodnih neprijatelja uslijed različitih scenarija promjena klime ; (V) procjenu učinkovitosti te poboljšanje postojećih mjera integrirane zaštite bilja od štetnih kukaca za unaprjeđenje otpornosti ekosustava.

Climate change is one of the greatest concerns of today’s world and has significantly altered or is continuously altering Earth’s ecosystems. It can be explained as the phenomenon involving changes in environmental factors like temperature, humidity and precipitation through a long period of time. The unprecedented temperature rise has resulted in increased events of droughts, floods, heat waves and other extreme weather conditions on a global scale. Far reaching effects of climate change are now greatly visible on agriculture sector, on which relies the food production, food safety and economy of the most parts of the world. Current and future climate change is projected to have significant impact on the cultivation of agricultural crops resulting in lower yields and higher costs. Climate change also have notable impact on pests of these agricultural crops by influencing their reproduction, development, survival and spread as well as the relation between pests and their environment. As a significant driver of agricultural crops and their pest population dynamics, climate change will require adaptive management strategies. This means that we need to take proper measures to mitigate harmful effects of climate change and adapt to its consequences. In order to do so, the key is transition to sustainable and modern agriculture which must be driven by new technologies, research and innovation. In 2020, the European Regional Development Fund has supported the project "AgroSPARC - Advanced and predictive agriculture for resilience to climate change" which is carried out by the Innovation Centre Nikola Tesla, Faculty of Electrical Engineering and Computing and the Faculty of Agriculture at the University of Zagreb in Croatia. Therefore, the key priorities of this project are building resilience and adapting to present and future climate risks. The main focus of the project is to use artificial intelligence to develop mathematical models for different phenophases of wheat and use these models to forecast crop yields and forewarn of insect pests in the terms of climate change predictions. Analysis of a large data sets will be carried out in relation to various climatic conditions, which will be artificially generated and permuted in prototype climate chambers. These data sets will be correlated with established indicators of wheat growth and development at different phenophases and different intensities of the insect pest infestation. A system based on artificial neural networks will be developed. Artificial neural networks classify and select data on climatic conditions in prototype climate chamber, real-time weather forecasts and indicators of crop development and then learn and verify numerical models of different phenophases of wheat based on large experimental data sets. This activity involves determining neural network structure ; inputs, outputs, number of different layers, number of neurons per layer, etc. When determining the structure, the available domain knowledge in agronomy is expected to significantly increase the efficiency in the implementation of activities and reduce time frame for obtaining results as well as the accuracy of the final results. The mathematical models will be available publicly and interactively via an online portal to forecast different phenophases of wheat and forewarn of the most significant insect pests of wheat under real and hypothetical climatic