A regression analysis method for the prediction of olive oil sensory attributes

This article documents an approach to predicting positive sensory attributes – fruitiness, bitterness, pungency-of virgin olive oil from its chemical characteristics, using machine learning methods. The dataset used in this study included forty-nine olive oil samples of the Koroneiki variety from nine selected olive mills, evenly distributed in the region of Messinia, Greece. The samples were analyzed for free acidity, peroxide value, the UV absorption for the determination of the extinction coefficients, phenolic compounds (total secoiridoid phenols, oleocanthal, oleacein, oleuropein aglycon and ligstroside aglycon) and sterol compounds (total sterols, cholesterol, campesterol, stigmasterol, d7-stigmasterol, erythrodiol, uvaol, b-sitosterol). Sensory analysis of the samples took place 20–30 days after their sampling date and the intensity of three positive attributes (fruitiness, bitterness and pungency) was measured. The authors used the least absolute shrinkage and selection operator (Lasso) for feature selection and then applied ordinary least squares (OLS) methods to build the final models. Three Python-based forecasting machine learning models for each sensory characteristic (fruitiness, bitterness, and pungency) were built and evaluated in comparison to one another in terms of the performance metrics of root mean squared error (RMSE) and mean absolute percentage error (MAPE), using repeated 5-fold cross-validation. The interacting effects among the sensory features were also considered for developing the two regression models, while the third model was only based on chemical attributes. The results obtained, revealed a significant relationship between each sensory attribute and the intensity of the other two, with the respective prediction models demonstrating a highly satisfactory level of performance. Furthermore, models that employed only chemical indices as predictors provided strong evidence that chemical indices alone were sufficient to predict the intensities of the sensory attributes. The findings of this study establish the predictive value of the constructed models, which might be utilized to support panels in training and calibration

Toxicity and Influence of Sublethal Exposure to Sulfoxaflor on the Aphidophagous Predator <i>Hippodamia variegata</i> (Coleoptera: Coccinellidae)

Hippodamia variegata (Goeze), the variegated ladybug, is a predator of many insect pests, especially aphids. Sulfoxaflor is a chemical insecticide that can be used to control many sap-feeding insect pests, for instance, plant bugs and aphids, as an alternative to neonicotinoids in different crops. To improve the combination of the H. variegata and sulfoxaflor in an IPM (integrated pest management) program, we studied the ecological toxicity of the insecticide to the coccinellid predator at sublethal and lethal doses. We examined the influence of sulfoxaflor on larvae of H. variegata using exposure doses of 3, 6, 12, 24, 48 (maximum recommended field rate (MRFR)), and 96 ng a.i. per insect. In a 15-day toxicity test, we observed decreased adult emergence percentage and survival, as well as an increased hazard quotient. The LD50 (dose causing 50% mortality) of H. variegata due to sulfoxaflor decreased from 97.03 to 35.97 ng a.i. per insect. The total effect assessment indicated that sulfoxaflor could be grouped as slightly harmful for H. variegata. Additionally, most of the life table parameters were significantly decreased after exposure to sulfoxaflor. Overall, the results present a negative influence of sulfoxaflor on H. variegata when applied at the recommended field dose for controlling aphids in Greece, which demonstrates that this insecticide may only be employed with care when used in IPM programs

Toxicity and Lethal Effect of Greenhouse Insecticides on Coccinella septempunctata (Coleoptera: Coccinellidae) as Biological Control Agent of Myzus persicae (Hemiptera: Aphididae)

Deltamethrin and imidacloprid are commonly used insecticides for controlling sub-sucking insects in greenhouses. However, their application may cause sublethal effects on the aphid coccinellid predator Coccinella septempunctata (Coleoptera: Coccinellidae). Here, we study (i) the toxicity and the effect of two sublethal doses (LD10 and LD30) of deltamethrin and imidacloprid on C. septempunctata in a laboratory microcosm and (ii) the residual toxicity of the two insecticides in a greenhouse. The results showed that both insecticides reduced fecundity, longevity, the intrinsic rate of increase, the finite rate of increase and the net reproductive rate. However, the developmental time of the fourth instar larvae was prolonged by both insecticides at LD10 and LD30. Deltamethrin residues were toxic 21 DAT (days after treatment) to C. septempunctata fourth instar larvae. In contrast, imidacloprid began in the slightly harmful category (75%) 1 DAT and declined to the harmless category (18.33%) 21 DAT. These results indicate that deltamethrin and imidacloprid have potential risks to C. septempunctata. This study provides information to guide the development of integrated pest management (IPM) strategies in greenhouses