Scientific Journals of INIA (Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria)
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Disease classification in Solanum melongena using deep learning
Get PDFAim of study: The application of pre-trained deep learning models, AlexNet and VGG16, for classification of five diseases (Epilachna beetle infestation, little leaf, Cercospora leaf spot, two-spotted spider mite and Tobacco Mosaic Virus (TMV)) and a healthy plant in Solanum melongena (brinjal in Asia, eggplant in USA and aubergine in UK) with images acquired from smartphones.Area of study: Images were acquired from fields located at Alangudi (Pudukkottai district), Tirumalaisamudram and Pillayarpatti (Thanjavur district) – Tamil Nadu, India.Material and methods: Most of earlier studies have been carried out with images of isolated leaf samples, whereas in this work the whole or part of the plant images were utilized for the dataset creation. Augmentation techniques were applied to the manually segmented images for increasing the dataset size. The classification capability of deep learning models was analysed before and after augmentation. A fully connected layer was added to the architecture and evaluated for its performance.Main results: The modified architecture of VGG16 trained with the augmented dataset resulted in an average validation accuracy of 96.7%. Despite the best accuracy, all the models were tested with sample images from the field and the modified VGG16 resulted in an accuracy of 93.33%.Research highlights: The findings provide a guidance for possible factors to be considered in future research relevant to the dataset creation and methodology for efficient prediction using deep learning models
Phylogenetic analysis and spatial distribution of bovine viral diarrhea virus (BVDV) in dairy cattle from Galicia (NW Spain)
Get PDFAim of study: To examine the frequency and diversity of bovine viral diarrhea viruses infecting dairy cattleArea of study: The study was carried out in Galicia (NW Spain), the main dairy cattle area of SpainMaterial and methods: A total of 157 BVDV isolates (from 140 dairy herds) were typed. Typing was based on a 288-bp sequence from the 5′ untranslated region of viral RNA genome. Subsequently, to investigate whether the presence of herds diagnosed with a particular strain was higher in some areas or during some specific time period, data were tested using a Bernouille approachMain results: Of the 157 isolates, 137 (87.3%) were typed as BVDV-1b, 10 (6.4%%) as 1d, 7 (4.4%) as 1e and 2 (1.3%) as 1f. One isolate was assigned to type 1p. Three of the strains found in the study (the three belonging to type 1b) showed significant spatial clustering.Research highlights: This report indicates that BVDV-1b was the predominant species, although there was an important genetic diversity in the study population. Spatial analysis indicated important drawbacks in the application of biosecurity measures, especially as regards purchase of cattle or after the reintroduction of animals from cattle concentration points
Growth performance and meat composition of rabbits fed diets supplemented with silkworm pupae meal
Get PDFAim of study: To determine the effect of different dietary levels of silkworm pupae meal (SWPM) on the growth performance of broiler rabbits and the chemical composition of their meat.Area of study: Southern Poland, Europe.Material and methods: Ninety Termond White rabbits were divided into three feeding groups. Control group rabbits were fed a diet containing 10% soybean meal (SBM). In the first experimental group, rabbits received a diet containing 5% SBM and 5% SWPM. The diet administered to the second experimental group was supplemented with 10% SWPM.Main results: Both partial and complete replacement of SBM with SWPM in diets contributed to a decrease in the final body weights of rabbits (2416.50 and 2390.78 vs. 2616.78 g), average daily gains (30.23 and 30.52 vs. 33.12 g) and feed intake (5.61 and 5.15 vs. 6.51 kg), but it improved the feed conversion ratio (3.28 and 3.05 vs. 3.41 kg/kg). Rabbits fed diets supplemented with SWPM were characterized by lower values of selected carcass parameters such as carcass weight and dressing percentage. Experimental diets had no significant effect on the proximate chemical composition of meat, but they increased the levels of fatty acids C18:3, C22:5 and C22:6.Research highlights: The results of this study can be put into practice to replace conventional protein and fat sources in rabbit diets with insect meals (SWPM) in the production of rabbit meat for human consumption. Our findings can also contribute to the recycling of sericultural waste
Effects of white shrimp (Litopenaeus vannamei) and tilapia nilotica (Oreochromis niloticus var. Spring) in monoculture and co-culture systems on water quality variables and production in brackish low-salinity water earthen ponds during rainy and dry seasons
Get PDFAim of study: To determine the effects of white shrimp (Litopenaeus vannamei) and tilapia nilotica (Oreochromis niloticus var. Spring) in monoculture and co-culture on water quality variables and production in earthen ponds during dry and rainy seasons.Area of study: A shrimp farm (total area 20 ha) at Chiripa, San Blas Nayarit, Northwest coast of Mexico (21° 37' 34.53 " N; 105° 18' 16.31" W).Material and methods: Two production cycles were performed in a completely randomized design consisting of two treatments and three replications each during rainy season (September-December) and dry season (February-May). Shrimp was the main crop and tilapia the secondary species.Main results: White shrimp (10 org/m2) can be co-cultured with Nile tilapia at a stocking high density (4 org/m2), leading to improved water quality and better utilization of nutrients in dry season than in rainy season. However, the shrimp’ highest weight was recorded in the tilapia-shrimp co-culture ponds during rainy season due to higher water temperature and better quality of live food. The mean individual weight, biomass and survival of the shrimp, in co-culture ponds were greater than those of the shrimp monoculture, in the two seasons studied.Research highlights: There was a trend towards greater concentration of nutrients in the water of the monoculture ponds and, lower dissolved oxygen and higher BOD5 in co-culture ponds in the dry season than in the rainy season
A sinusoidal equation as alternative to conventional growth functions to describe the evolution of growth in quail
Get PDFAim of study: The aim of the present study was to introduce a sinusoidal equation into poultry science by applying it to temporal growth data from quail.Material and methods: To examine the performance of the sinusoidal equation in describing the growth patterns of quail, four conventional growth functions (Gompertz, logistic, López and Richards) were used as reference in this study. Comparison of models was carried out by analysing model behaviour when fitting the curves using nonlinear regression and assessing statistical performance. Maximum log-likelihood estimation, mean squared error, Akaike and Bayesian information criteria were used to evaluate the general goodness-of-fit of each model to the different data profiles.Main results: The selected sinusoidal equation precisely describes the growth dynamics of quail. Comparison of the growth functions in terms of the goodness-of-fit criteria revealed that the sinusoidal equation was one of the most appropriate functions to describe the age-related changes of bodyweight in quail.Research highlights: To the best of our knowledge there are no studies available on the use of sinusoidal equations to describe the evolution of growth in quail. The sinusoidal equation used in this study represents a suitable alternative to conventional growth functions to describe the growth curves for a range of strains/lines of male and female Japanese quail
Wood species identification from Atlantic forest by near infrared spectroscopy
Get PDFAim of study: Fast and reliable wood identification solutions are needed to combat the illegal trade in native woods. In this study, multivariate analysis was applied in near-infrared (NIR) spectra to identify wood of the Atlantic Forest species.Area of study: Planted forests located in the Vale Natural Reserve in the county of Sooretama (19 ° 01'09 "S 40 ° 05'51" W), Espírito Santo, Brazil.Material and methods: Three trees of 12 native species from homogeneous plantations. The principal component analysis (PCA) and partial least squares regression by discriminant function (PLS-DA) were performed on the woods spectral signatures.Main results: The PCA scores allowed to agroup some wood species from their spectra. The percentage of correct classifications generated by the PLS-DA model was 93.2%. In the independent validation, the PLS-DA model correctly classified 91.3% of the samples.Research highlights: The PLS-DA models were adequate to classify and identify the twelve native wood species based on the respective NIR spectra, showing good ability to classify independent native wood samples.Keywords: native woods; NIR spectra; principal components; partial least squares regression
Inhibitory action of essential oils against proteases activity of Paenibacillus larvae, the etiological agent of American Foulbrood disease
Get PDFAmerican foulbrood (AFB) is a disease affecting the larva of Apis mellifera. The etiological agent is Paenibacillus larvae, which releases metalloproteases involved in the degradation of larval tissues. Through quorum sensing (QS) mechanism, bacteria are able to activate specific genes such as virulence factors. The exoproteases regulation of P. larvae could be associated with QS. A promising mechanism of AFB control is to block QS mechanism with essential oils (EO). The aim of this study was to investigate the potential presence of QS signals in the regulation of P. larvae proteases and the effect of seven EOs on the exoproteases activity of P. larvae. From growth curves and evaluation of the presence of proteases by milk agar plates assay, it was observed protease activity during the late exponential phase of growth. Early production of protease activity (15 hours earlier than control) was observed when a low density culture was incubated with late exponential spent medium (SM) suggesting the presence of factor(s) inducing this activity. SM was obtained by the ultrafiltration of P. larvae cultures on late growth phase and was free of proteases. Proteolytic activity was quantified on P. larvae cultures in presence of sublethal concentration of EO by azocasein method. The EOs, except S. chilensis EO, reduced significantly protease activity (more than 50%). We report for the first time evidence on the possible role of QS on P. larvae and the antiproteolytic activity of EOs (except for S. chilensis) on exoproteases, an interesting therapeutic strategy to control AFB
Development of an index based on ultrasonographic measurements for the objective appraisal of body condition in Andalusian horses
Get PDFBody condition scoring (BCS) is an indirect measure of the level of subcutaneous fat; however, by measuring the subcutaneous fat thicknesses (SFT), the precision of the degree of fatness assessment is improved. The aims were: 1) to develop an alternative body fat scoring index (BFSI) based on ultrasonographic measurements; 2) to assess the agreement between BCS and the new index applied to Andalusian horses; 3) to adjust the BCS cut-off values (if necessary) for overweight and obesity in this breed. One hundred and sixty-six Andalusian horses were included in this cross sectional study. On each horse, BCS, body fat percentage (BF%) and ultrasonography of SFT at localized deposits were evaluated. According to BFSI five possible body categories were established. Only one horse (0.6%) was classified as emaciated, 9.0% as thin, 74.7% as normal, 11.4% as overweight and 4.2% as obese. Despite higher BCS and SFT values were observed compared to other breeds, most of the horses evaluated presented a normal body condition under the new BFSI. BCS and BFSI were significantly associated (p<0.001), however, the concordance was low (weighted Cohen’s kappa coefficient, 0.262 ± 0.071; p=0.004). Using BFSI, obese horses had significantly greater BF% than the rest of categories (p<0.001). BCS showed a good diagnostic accuracy for detection overweight (AUC = 0.759 ± 0.055; p<0.001) and obese (AUC = 0.878 ± 0.050; p=0.001) horses; redefining the cut-off values for overweight and obesity condition as 7.5/9 and 8.5/9 respectively in Andalusian horses