Minimum Temperature Threshold Research Articles

Predicting eastern oyster (Crassostrea virginica) settlement using growing degree days along the north shore of Nova Scotia, Canada

The supply of oyster spat is crucial for the sustainability and development of the oyster aquaculture industry. While hatcheries worldwide are increasing spat production, wild spat collection remains prevalent in Atlantic Canada. Existing monitoring programs aid in wild spat collection but are costly and labour-intensive, relying on fieldwork and expert personnel. To complement monitoring programs, mathematical models with varying complexity have been used to predict the settlement of commercially valuable bivalves. These models consider various environmental parameters such as temperature, winds, tides, and food concentrations. In this study, we explore the prediction of settlement in Eastern oysters (Crassostrea virginica) using a simple Growing Degree Day (GDD) model, which considers only one parameter, temperature. The GDD model estimates Larval Development Time (LDT) based on accumulated heat units (°C·day) above a species-specific minimum temperature threshold for growth. By calibrating the model with literature data and validating it with field observations from four estuaries in Nova Scotia, we aimed to provide a tool for farmers to predict the onset of oyster settlement based on observed seawater temperature. The model effectively predicted the onset of oyster settlement based on observed seawater temperature. The GDD model is a simple and easily implementable tool that can enhance the success of wild spat collection efforts and contribute to the robustness of the oyster aquaculture industry.

A study on microclimate monitoring and control inside greenhouse using fans automation

<span>Efficient microclimate management is crucial in enhancing crop yields in greenhouses. Factors like temperature, relative humidity, and ultraviolet (UV) index significantly impact crop quality. The absence of adequate ventilation mechanisms in greenhouses presents a challenge for temperature regulation. This study proposes a solution for tropical greenhouses by designing a system that automatically activates fans when temperatures rise above 30 °C. This system regulates temperature and cultivates optimal growth conditions for crops. It is supported by a web page that enables monitoring and adjustment of microclimate data. To accommodate individual crop requirements, the minimum temperature threshold for fan activation can be modified, enhancing the system's adaptability. The impact of the UV index on greenhouse temperature is also considered. The automation system decreases the temperature by around ±3 °C when the UV index hits 10. Nonetheless, its cooling impact wanes beyond the UV index of 10. A greenhouse automation system, equipped with fans and internet access, proves quite useful for agricultural environment management. It tackles the temperature control issue and offers varied solutions.</span>

Determination of minimum threshold temperature and degree day requirements for the development of Spodoptera litura on different host plants

Determination of minimum threshold temperature and degree day requirements for the development of Spodoptera litura on different host plants

Thermal risk analysis for winter-spring maize (Zea mays L.) in the Yaqui Valley Sonora, Mexico

The state of Sonora in Mexico contributed with 2.8 % of the maize national production (788,885.77 t) in 2021; however, its production has been affected by low temperatures. The objective was to analyze the effect of minimum (MINTT < 3 °C) and maximum temperature threshold levels (MAXTT > 33 °C) on maize production. Five commercial fields sown with hybrid Hipotótamo and five with DK-4050 were selected in the Yaqui Valley. Temperature data were obtained from the automated weather station network in the state from December 2021 to June 2022. The minimum temperatures recorded between March 8 and 10, 2022, covered about 35 % of the total area sown with maize in southern Sonora. Foliar damage as shown by necrosis between the 5th and 10th leaf oscillated from 3 to 12 %, and it was associated with a temperature range of 1.05 and 4.30 ºC. Frost severity was not significant, so the crop recovered by the production of new leaves. From April, different periods of days with different continuous hours with MAXTT were recorded by weather stations; the highest number of periods occurred in fields B-419 and B-1101 with six. The highest number of hours with MAXTT was recorded in B-1922 with 374, followed by B-419 with 288. Hipopótamo showed the highest grain yield in field B-1101 (16.62 t ha-1). Damage by MAXTT to maize production during 2021-2022 winter-spring season, caused a reduction of 1.53 t ha-1 in relation to the regional average in the previous season.

The Preliminary Study on the Biology of An Invasive Species, Halyomorpha halys (Hemiptera: Pentatomidae) in Northwest Türkiye

The Brown marmorated stink bug (BMSB) [Halyomorpha halys (Hemiptera: Pentatomidae)] is a polyphagous pest causing significant damage to approximately 300 crops, such as nuts, vegetables, and ornamentals. In 2017, the BMSB was discovered for the first time in Türkiye. There is currently no published data available on the biology of the pest in Türkiye. This preliminary study was carried out in Sakarya province, where the BMSB has observed a low population since 2021. In this study, some biological parameters such as voltinism, mortality rates, egg hatching rates, and egg-adult developmental times of the 1st and 2nd generations of the insect populations were determined. The study was carried out under semi-field conditions and laboratory. Considering the BMSB's minimum temperature threshold, which has yet to be determined in Turkey, the accumulation of degree days was calculated using the references to four possible thresholds (DD12, 12.5, 13, 13.5) and was determined to be between 536.91 - 608.69 DD. The average egg-adult developmental time was 47.85 days for the 1st generation at naturally fluctuating temperatures and 47.13 days for the 2nd generation under laboratory conditions at 25 ֯C. The hatching rate of egg masses was determined to 90.63% in the 1st generation and 57.75% in the 2nd generation. Total mortality in the first generation was 22.97% and 90.24% in the second generation. It was revealed that the insect could produce two generations in Türkiye, but the number of egg-producing adults and eggs laid in the second generation was significantly lower than that in the first. This preliminary study was carried out with a limited number of samples due to the initial infesting in the region and, therefore more comprehensive research is needed to reveal the the biology of BMSB in the country.

Effects of Temperature on the Developmental and Reproductive Biology of North American Bean Thrips, Caliothrips fasciatus (Pergande) (Thysanoptera: Thripidae: Panchaetothripinae).

North American bean thrips, Caliothrips fasciatus, native to California U.S., has been detected inside the navels of navel oranges exported from California for more than 120 years. Despite this long history of accidental movement into new areas, this thrips has failed to establish populations outside of its native range. The cold accumulation hypothesis postulates that increasing levels of cold stress experienced by thrips overwintering inside navels is compounded when harvested fruit is shipped under cold storage conditions. Consequently, the fitness of surviving thrips is compromised, which greatly diminishes invasion potential. At the time this study was conducted, the effects of temperature on C. fasciatus fitness were unknown. To address this shortcoming, the effects of nine fluctuating temperatures that averaged 8, 10, 15, 20, 25, 30, 32, 35, and 37 °C over a 24 h period on the developmental and reproductive biology of C. fasciatus were evaluated. One linear and five nonlinear regression functions were fit to egg-to-adult development rate data for parent and offspring thrips to characterize thermal performance curves. Estimates of minimum, optimal, and maximum temperature thresholds for development were in the ranges of -4.37-6.52 °C (i.e., Tmin), 31.19-32.52 °C (i.e., Topt), and 35.07-37.98 °C (i.e., Tmax), respectively. Degree day accumulation to complete development, estimated from linear regression, ranged 370.37-384.61. Average development times for eggs, first and second instar larvae, propupae, pupae, and adult longevity, and mean lifetime fecundity of females were significantly affected by temperature. These biological responses to temperature may provide insight into how this abiotic variable affects the invasion potential of C. fasciatus.

Towards a Better Understanding of Texturization during High-Moisture Extrusion (HME)-Part I: Modeling the Texturability of Plant-Based Proteins.

This study focused on predicting high-moisture texturization of plant-based proteins (soy protein concentrate (SPC), soy protein isolate (SPI), pea protein isolate (PPI)) at different water contents (57.5%, 60%, 65%, 70%, and 72.5% (w/w db)) to optimize and guarantee the production of high-moisture meat analogs (HMMA). Therefore, high-moisture extrusion (HME) experiments were performed, and the texture of the obtained high-moisture extruded samples (HMES) was sensory evaluated and categorized into poorly-textured, textured, or well-textured. In parallel, data on heat capacity (cp) and phase transition behavior of the plant-based proteins were determined using differential scanning calorimetry (DSC). Based on the DSC data, a model for predicting cp of hydrated, but not extruded, plant-based proteins was developed. Furthermore, based on the aforementioned model for predicting cp and DSC data on phase transition behavior of the plant-based proteins in combination with conducted HME trials and the mentioned model for predicting cp, a texturization indicator was developed, which could be used to calculate the minimum threshold temperature required to texturize plant-based proteins during HME. The outcome of this study could help to minimize the resources of expensive extrusion trials in the industry to produce HMMA with defined textures.

A facultative mutualism facilitates European seagrass meadows

Coastal ecosystem functioning often hinges on habitat‐forming foundation species that engage in positive interactions (e.g. facilitation and mutualism) to reduce environmental stress. Seagrasses are important foundation species in coastal zones but are rapidly declining with losses typically linked to intensifying global change‐related environmental stress. There is growing evidence that loss or disruption of positive interactions can amplify coastal ecosystem degradation as it compromises its stress mitigating capacity. Multiple recent studies highlight that seagrass can engage in a facultative mutualistic relationship with lucinid bivalves that alleviate sulphide toxicity. So far, however, the generality of this mutualism, and how its strength and relative importance depend on environmental conditions, remains to be investigated. Here we study the importance of the seagrass‐lucinid mutualistic interaction on a continental‐scale using a field survey across Europe. We found that the lucinid bivalve Loripes orbiculatus is associated with the seagrasses Zostera noltii and Zostera marina across a large latitudinal range. At locations where the average minimum temperature was above 1 °C, L. orbiculatus was present in 79% of the Zostera meadows; whereas, it was absent below this temperature. At locations above this minimum temperature threshold, mud content was the second most important determinant explaining the presence or absence of L. orbiculatus. Further analyses suggest that the presence of the lucinids have a positive effect on seagrass biomass by mitigating sulphide stress. Finally, results of a structural equation model (SEM) support the existence of a mutualistic feedback between L. orbiculatus and Z. noltii. We argue that this seagrass‐lucinid mutualism should be more solidly integrated into management practices to improve seagrass ecosystem resilience to global change as well as the success of restoration efforts.

Pest categorisation of Paracoccus marginatus.

The EFSA Panel on Plant Health performed a pest categorisation of Paracoccus marginatus (Hemiptera: Sternorrhyncha: Pseudococcidae), the papaya scale, for the EU. It is native to Central America and since the 1990s, it has spread rapidly in mainly tropical areas of the Caribbean, islands in the Indian and Pacific Oceans, Africa and southern Asia. Large populations were detected in northern Israel in 2016. It has not been reported within the EU. It is not listed in Annex II of Commission Implementing Regulation (EU) 2019/2072. It reproduces sexually and there are up to 11 generations per year in India. The estimated minimum, optimum and maximum temperature thresholds for the adult females are 13.9, 28.4 and 32.1°C, respectively. First-instar nymphs may move to neighbouring plants by crawling, or be passively dispersed by wind, or hitchhiking on clothing, equipment or animals. It is highly polyphagous, feeding on plants in 172 genera and 54 families. It is an important pest of custard apple (Annona spp.), papaya (Carica papaya) and Hibiscus spp. It also feeds on a wide range of plants cultivated in the EU such as eggplant (Solanum melongena), avocado (Persea americana), citrus (Citrus spp.), cotton (Gossypium hirsutum), grapevine (Vitis vinifera), guava (Psidium guajava), mango (Mangifera indica), passionfruit (Passiflora edulis), pomegranate (Punica granatum), pepper (Capsicum annuum) and tomato (Solanum lycopersicum). Plants for planting, fruits, vegetables and cut flowers are the main potential pathways for entry of P. marginatus into the EU. Climatic conditions in the warmest areas of Cyprus, Greece, Italy and Spain, where host plants occur, would likely allow this species to successfully establish and spread. Reductions in yield and quality of some cultivated hosts including Annona spp., Hibiscus spp. and papaya are anticipated if establishment occurs. Phytosanitary measures are available to reduce the likelihood of entry and spread. P. marginatus meets the criteria that are within the remit of EFSA to assess for this species to be regarded as a potential Union quarantine pest.

A Wildfire Detection Algorithm Based on the Dynamic Brightness Temperature Threshold

Satellite remote sensing plays an important role in wildfire detection. Methods using the brightness and temperature difference of remote sensing images to determine if a wildfire has occurred are one of the main research directions of forest fire monitoring. However, common wildfire detection algorithms are mainly based on a fixed brightness temperature threshold to distinguish wildfire pixels and non-wildfire pixels, which reduces the applicability of the algorithm in different space–time regions. This paper presents an adaptive wildfire detection algorithm, DBTDW, based on a dynamic brightness temperature threshold. First, a regression dataset, MODIS_DT_Fire, was constructed based on moderate resolution imaging spectroradiometry (MODIS) to determine the wildfire brightness temperature threshold. Then, based on the meteorological information, normalized difference vegetation index (NDVI) information, and elevation information provided by the dataset, the DBTDW algorithm was used to calculate and obtain the minimum brightness temperature threshold of the burning area by using the Planck algorithm and Otsu algorithm. Finally, six regression models were trained to establish the correlation between factors and the dynamic brightness temperature threshold of wildfire. The root-mean-square error (RMSE) and mean absolute error (MAE) were used to evaluate the regression performance. The results show that under the XGBoost model, the DBTDW algorithm has the best prediction effect on the dynamic brightness temperature threshold of wildfire (leave-one-out method: RMSE/MAE = 0.0730). Compared with the method based on a fixed brightness temperature threshold, the method proposed in this paper to adaptively determine the brightness temperature threshold of wildfire has higher universality, which will help improve the effectiveness of satellite remote fire detection.

Optimal scheduling method of regenerative electric heating for emergency residential building heating: An affine arithmetic‐based model predictive control approach

AbstractResidential heating faces the challenge of heating interruption when an electric power outage occurs. As a promising heating electrification form, regenerative electric heating (REH) equipped with thermal energy storage (TES) has the flexibility of maintaining the building indoor temperature within the desired range during power outages and reducing the operation cost during normal operation states. However, the allocation and scheduling of the limited thermal energy in TES for the above two purposes is impacted by many uncertainties, for example, outdoor temperature, irradiation, and duration of power outages. Overestimation of the thermal energy required for power outages in the TES can improve the heating supply reliability, but it will also increase the REH operation cost to some extent, and vice versa. To address this problem, an affine arithmetic‐based model predictive control approach (AA‐MPC) for an optimal REH scheduling method is proposed to balance the heating supply reliability during power outages and operation economy of REH at the same time. An REH‐based residential building energy system model is developed to describe the building thermal load associated with the outdoor temperature and irradiation. Then, the required thermal energy for emergency building heating provided by the hot water tank (HWT) is determined using the minimum thermal demand of residents during a power outage, which is constrained by the minimum comfort temperature threshold. Based on this, an AA‐MPC approach that takes the thermal energy for emergency building heating as a time‐varying constraint of the HWT is developed to determine the optimal REH scheduling that considers emergency residential building heating under the above uncertainties. Numerical studies show that the proposed method can maintain minimum thermal demand for at least 2 h when a power outage occurs under uncertainties. At the same time, it can reduce the impact of uncertainties on the operation cost and reduce economic problems caused by emergency heating to a certain extent. Compared to the interval arithmetic‐based model predictive control approach, the operation cost intervals of the proposed method are reduced by 57.3%, 0.3%, and 32.5% under low, middle, and high prediction error levels respectively.

Spawning time of black sea bream Acanthopagrus schlegelii, related to underwater photoperiodism in oyster farms.

The embryonic development times, spawning timing and hatching rates of the black sea bream Acanthopagrus schlegelii were examined to investigate the potential effect of seawater temperature, tides and photoperiod on the reproductive rhythm of this species in Hiroshima Bay, Japan. Low temperatures decreased hatching rates and extended the hatching time, and the minimum temperature threshold for hatching was 15°C. Back-calculated spawning times indicated that the peak of spawning occurred just before sunset and the reduction in diurnal light intensity around the oyster rafts acted as a trigger for spawning. In contrast, no correlation was found between spawning rhythms and tidal cycle. The results highlight the important role of oyster farms in the reproductive cycle and population dynamics of A. schlegelii in Hiroshima Bay, the main spawning ground for this species in Japan. The study findings provide insights for the sustainable management of this important sparid species.

Establishing the lower thresholds for water sterilisation with shock waves and hot gas bubbles from the detonation of explosives in water

Water sterilisation requires the inactivation of waterborne pathogens, like E.coli, to such low levels that its use will not cause illness. Here, we examine a potential methodology for disinfecting water through the combined effect of hot expanding gases and shock waves from underwater explosions. Water pathogens located within the proximity of the explosive charge will be exposed to two different sterilisation conditions: firstly, the high-pressure shock wave moving within the fluid, and secondly, the expanding hot N2, O2, and CO2 bubbles that are products of the explosion. To simulate the first case, we used a flyer-plate technique to understand the lower threshold for inactivation. We did this with a novel capsule design in a single-stage light gas-gun and observed 0.813 Logs of E.coli inactivation after subjecting an entire bacterial broth to a minimum pressure of 3.53 GPa thereby indicating a lower threshold for shock pressure-induced inactivation. For the second case, we show that hot gas bubbles from different explosive gaseous products at 150°C in a bubble column established the minimum gas temperature thresholds required to successfully inactivate E.coli. This work shows that any benefit of using explosives to sterilise water will principally come from the release of hot gaseous bubbles rather than the effect of the shock. This new approach could be used in conflict areas or remote locations with no access to standard sterilisation technologies or power.

Disentangling thermal effects using life cycle simulation modelling on the biology and demographic parameters of Dolichogenidea gelechiidivoris, a parasitoid of Tuta absoluta

Dolichogenidea gelechiidivoris (Marsh) (Syn. Apanteles gelechiidivoris) (Hymenoptera: Braconidae), a konoibiont larval endoparasitoid of the South American tomato pinworm Tuta absoluta (Meyrick), was imported into Kenya in 2017 for the first classical biological control of T. absoluta in Africa. We determined the thermal thresholds of D. gelechiidivoris, with T. absoluta as host, using life cycle simulation modelling. Life-table data of D. gelechiidivoris were generated at six constant temperatures (10, 15, 20, 25, 30, and 35 °C, 65 ± 5% RH, and 12L: 12D photoperiod). Multiple non-linear functions were fitted to model some aspects of the biology of the parasitoid, including its longevity, mortality, reproduction, and senescence using Insect Life Cycle Modelling (ILCYM) software. The phenology models established were used to estimate life table parameters. Except at 35 °C, D. gelechiidivoris completed its development (i.e., egg-larval-pupa-adult) at all tested temperatures. The minimum temperature threshold from egg to cocoon was 7.0 °C and 5.9 °C from cocoon to adult wasp, while the maximum temperature thresholds were 34 °C and 36 °C, respectively. The optimal temperature for immature survival was 20–25 °C, while fecundity was optimum at 22.5 °C, with 69.5 eggs per female. Simulations of the population growth parameters indicated that the intrinsic rate of increase (rm) was maximum at 20 °C with 15 daughters per female per generation. Based on our findings the release of D. gelechiidivoris for inoculative augmentation in countries with temperatures ranging between 15 and 30 °C could be considered to control the pest.

Detecting accelerometer non-wear periods using change in acceleration combined with rate-of-change in temperature

BackgroundAccelerometery is commonly used to estimate physical activity, sleep, and sedentary behavior. In free-living conditions, periods of device removal (non-wear) can lead to misclassification of behavior with consequences for research outcomes and clinical decision making. Common methods for non-wear detection are limited by data transformations (e.g., activity counts) or algorithm parameters such as minimum durations or absolute temperature thresholds that risk over- or under-estimating non-wear time. This study aimed to advance non-wear detection methods by integrating a ‘rate-of-change’ criterion for temperature into a combined temperature-acceleration algorithm.MethodsData were from 39 participants with neurodegenerative disease (36% female; age: 45–83 years) who wore a tri-axial accelerometer (GENEActiv) on their wrist 24-h per day for 7-days as part of a multi-sensor protocol. The reference dataset was derived from visual inspection conducted by two expert analysts. Linear regression was used to establish temperature rate-of-change as a criterion for non-wear detection. A classification and regression tree (CART) decision tree classifier determined optimal parameters separately for non-wear start and end detection. Classifiers were trained using data from 15 participants (38.5%). Outputs from the CART analysis were supplemented based on edge cases and published parameters.ResultsThe dataset included 186 non-wear periods (85.5% < 60 min). Temperature rate-of-change over the first five minutes of non-wear was − 0.40 ± 0.17 °C/minute and 0.36 ± 0.21 °C/minute for the first five minutes following device donning. Performance of the DETACH (DEvice Temperature and Accelerometer CHange) algorithm was improved compared to existing algorithms with recall of 0.942 (95% CI 0.883 to 1.0), precision of 0.942 (95% CI 0.844 to 1.0), F1-Score of 0.942 (95% CI 0.880 to 1.0) and accuracy of 0.996 (0.994–1.000).ConclusionThe DETACH algorithm accurately detected non-wear intervals as short as five minutes; improving non-wear classification relative to current interval-based methods. Using temperature rate-of-change combined with acceleration results in a robust algorithm appropriate for use across different temperature ranges and settings. The ability to detect short non-wear periods is particularly relevant to free-living scenarios where brief but frequent removals occur, and for clinical application where misclassification of behavior may have important implications for healthcare decision-making.

Mapping Heat-Health Vulnerability Based on Remote Sensing: A Case Study in Karachi

As a result of global climate change, the frequency and intensity of heat waves have increased significantly. According to the World Meteorological Organization (WMO), extreme temperatures in southwestern Pakistan have exceeded 54 °C in successive years. The identification and assessment of heat-health vulnerability (HHV) are important for controlling heat-related diseases and mortality. At present, heat waves have many definitions. To better describe the heat wave mortality risk, we redefine the heat wave by regarding the most frequent temperature (MFT) as the minimum temperature threshold for HHV for the first time. In addition, different indicators that serve as relevant evaluation factors of exposure, sensitivity and adaptability are selected to conduct a kilometre-level HHV assessment. The hesitant analytic hierarchy process (H-AHP) method is used to evaluate each index weight. Finally, we incorporate the weights into the data layers to establish the final HHV assessment model. The vulnerability in the study area is divided into five levels, high, middle-high, medium, middle-low and low, with proportions of 3.06%, 46.55%, 41.85%, 8.53% and 0%, respectively. Health facilities and urbanization were found to provide advantages for vulnerability reduction. Our study improved the resolution to describe the spatial heterogeneity of HHV, which provided a reference for more detailed model construction. It can help local government formulate more targeted control measures to reduce morbidity and mortality during heat waves.

The anomalously cold January 2017 in the south‐eastern Europe in a warming climate

AbstractThe January 2017 wintry weather spread over the south‐eastern Europe and Turkey ‐which led to extremely low temperatures (−40°C) and snowstorms. This study strived to draw together key prominent dynamical mechanisms governing seasonal temperature variability in a warming climate, which can serve as a recognizable flow pattern and yield insights into their most important triggering mechanisms and maintenance. The connection between cold spells and atmospheric blocking was elucidated by utilizing an objective cold‐wave indicator and a two‐dimensional blocking indicator. The cold‐wave indicator ‐which uses a non‐parametric approach to diagnose a spatiotemporally varying minimum temperature threshold‐ gave an objective account of cold spells of January 2017. An analysis of cold‐wave activities indicated that parts of Europe and Turkey went through very cold weather conditions for approximately 7–12 days. Cold spells were closely related to the position of the blocking and the 500 hPa geopotential height anomalies. The horizontal distribution of surface temperature anomalies indicated that associated temperature anomalies were quite large in the south‐eastern Europe and Turkey. The persistence of the anticyclone over the eastern Atlantic steered the low pressure system towards the south‐eastern Europe and Turkey. The collocation of prominent atmospheric patterns led to the formation of extreme cold spells. Our results of two‐dimensional atmospheric blocking index revealed that blocking lasted for 5 days over the eastern Atlantic ‐which enabled anticyclonic conditions persisting. Diagnostics indicate that the imposed blocking over the north‐east Atlantic alters the direction and strength of the zonal flow in the south‐eastern Europe, which influences the behaviour of synoptic‐scale flow in its downstream. These results are consistent with the inferences drawn from surface temperature analyses, which accentuate the role of blocking imposed circulation on the anomalous low temperature anomalies. Characteristics of blocking at the north‐eastern Atlantic shed light on the winter climate variability over Europe and Turkey.

DAILY ACTIVITY OF THE HORSE FLIES (DIPTERA: TABANIDAE) IN THE CENTRAL BALKAN MOUNTAINS, BULGARIA

A study was conducted on the dynamics of tabanids daily activity in the Central Balkan Mountains in the 2011-2013 period. Tabanids have been found to fly 11 hours a day, with a peak in activity around 11:00. Their mass activation is in the temperature range 18-23°С and at 26°С maximum activity has been reported. In the present study a new, minimum temperature threshold for activation of T. quatuornоtatus Mg. in Bulgaria was registered (13°С).

Semi physical growth model of Lobesia botrana under laboratory conditions for Argentina’s Cuyo region

Lobesia botrana is a quarantine pest from Argentina and other countries in the world. It causes damage to the vine in its different growth stages leading to losses in wine production. To develop pest control strategies based on knowledge of the moth, different mathematical models can be found in specific literature to predict its biological cycle, establish its relationship with environmental variables, describe the voltinism of the pest, among others. Based on the proposed models, it is possible to establish a minimum temperature threshold considering the development of the moth and the number of degrees’ days (DD) that must be accumulated for there to be a change of stage. Many of these models are empirical. They are limited because they do not consider some variables such as growth and mortality rates, also they lack a conceptual basis. This makes that professionals or institutions interested in the development of decision support systems (DSS) may not use them. This also prevents them from being easily extrapolated to other regions of the world. In this work, a semi-physical model based on first principles (FPBSM) is proposed to describe how the different growth stages of the vine moth change quantitatively throughout its normal development time under controlled and specific laboratory conditions for the Cuyo region in Argentina. The proposed model, based on a white box structure, considers important parameters in the development of the moth, such as growth and mortality rates. Opposite to the models reported in the literature, the proposed model is conceptually more simple, easy to calculate or adjust, and Its parameters are interpretable in the model’s application context. The previous characteristics facilitate the proposal model’s use by sectors interested in the development of DSS systems. The reported mathematical model has been validated with experimental data for three different temperature conditions.

Temperature-dependent phenology of the parasitoid Fopius arisanus on the host Bactrocera dorsalis.

Fopius arisanus (Sonan), an egg-pupal parasitoid of numerous fruit fly species, was recently introduced into Africa for the control of the Oriental fruit fly, Bactrocera dorsalis (Hendel). In this study, life-table data of F. arisanus were generated under laboratory conditions at six constant temperatures (15, 20, 25, 30, 28 and 35°C; 75% RH, L12:D12 photoperiod) and under variable conditions in a screenhouse on B. dorsalis. Several non-linear functions were fitted to model species development, mortality, longevity and oviposition using the Insect Life Cycle Modeling (ILCYM) software. The established phenology models were stochastically simulated at variable temperatures to estimate the life table parameters. Fopius arisanus completed development from egg to adult at all the temperatures tested except at 35°C. Mean developmental time from egg to adult was inversely proportional to the temperature. The minimum temperature threshold (Tmin) from egg to adult was 8.15°C, while the maximum temperature threshold (Tmax) was estimated at 34.2°C. The optimal temperature for immature stages survival was predicted for 20-30°C. The optimum fecundity estimated was 251 eggs/female at 22°C. Following the stochastic simulations under natural conditions of the selected agro-ecological zones, it appears that the Humid Forest with Bimodal Rainfall provides a suitable thermal condition for potential population growth of F. arisanus. The present study shows the importance of temperature on the demographic parameters of F. arisanus. Implications of present findings on the biological control of B. dorsalis under climate change scenarios is discussed.