Scielo RSS <![CDATA[Scientia Agricola]]> vol. 74 num. 1 lang. es <![CDATA[SciELO Logo]]> <![CDATA[Genome association study through nonlinear mixed models revealed new candidate genes for pig growth curves]]> ABSTRACT: Genome association analyses have been successful in identifying quantitative trait loci (QTLs) for pig body weights measured at a single age. However, when considering the whole weight trajectories over time in the context of genome association analyses, it is important to look at the markers that affect growth curve parameters. The easiest way to consider them is via the two-step method, in which the growth curve parameters and marker effects are estimated separately, thereby resulting in a reduction of the statistical power and the precision of estimates. One efficient solution is to adopt nonlinear mixed models (NMM), which enables a joint modeling of the individual growth curves and marker effects. Our aim was to propose a genome association analysis for growth curves in pigs based on NMM as well as to compare it with the traditional two-step method. In addition, we also aimed to identify the nearest candidate genes related to significant SNP (single nucleotide polymorphism) markers. The NMM presented a higher number of significant SNPs for adult weight (A) and maturity rate (K), and provided a direct way to test SNP significance simultaneously for both the A and K parameters. Furthermore, all significant SNPs from the two-step method were also reported in the NMM analysis. The ontology of the three candidate genes (SH3BGRL2, MAPK14, and MYL9) derived from significant SNPs (simultaneously affecting A and K) allows us to make inferences with regards to their contribution to the pig growth process in the population studied. <![CDATA[Parametrization of the Davis Growth Model using data of crossbred Zebu cattle]]> ABSTRACT: The system of differential equations proposed by Oltjen et al. [1986, named Davis Growth Model (DGM)] to represent cattle growth has been parameterized with data from Bos taurus (British) and Bos indicus (Nellore) breeds. The DGM has been successfully used for simulation and decision support in the United States. However, the effect of about 30 years of genetic improvement and the use of different breeds may affect the model parameter values, which also may need to be re-estimated for crossbred animals. The aim of this study was to estimate parameter values and confidence intervals for the DGM with growth and body composition data from Zebu crossbred animals. Confidence intervals and asymptotic distribution were generated through nonparametric bootstrap with data from a field experiment conducted in Brazil. The parameters showed normal probability distribution for most scenarios. The rate constant for deoxyribonucleic acid (DNA) synthesis had a minimum increase of 156 % and the maximum of 389 %, compared to the original values and the maintenance requirement had a minimum increase of 126 % and maximum of 160 % compared to the original values. Lower limits of 95 % confidence intervals for the parameters related to maintenance and protein accretion rates were higher than the original estimates of the DGM, evidencing genetic differences of the Zebu crossbred animals in relation to the original DGM parameters. <![CDATA[Biology and nutrition of <em>Spodoptera frugiperda</em> (Lepidoptera: Noctuidae) fed on different food sources]]> ABSTRACT: We studied Spodoptera frugiperda development using different food sources in the laboratory and field. Newly hatched larvae were fed soybean, cotton, maize, wheat, and oat leaves. An artificial diet was used as the control. Duration of pre-pupal, pupal, and larva-adult period, pupal weight, sex ratio, survival, larva feeding preferences, oviposition preferences, and nutritional quality of different hosts were evaluated. Insects fed on wheat showed the shortest larva-adult period. The insects fed on cotton and soybean had longer larval development cycles and pupae of lower weight. Feeding preference was evident for third instar larvae and did not differ between wheat, oat, maize, and soybean, which were the preferred hosts. Moths oviposited to a greater extent on the upper canopy of wheat than that of other plants in both the no-choice and free-choice tests. Treatments influenced insect growth, food consumption, and digestion when nutritional variables were analyzed. Thus, grasses were better hosts for S. frugiperda development. Cotton was the least preferred food, followed by soybean. The present study can improve our understanding of S. frugiperda in these different crops and help in developing management strategies. Even though S. frugiperda is considered to be polyphagous, this pest is closely associated with grasses (maize, wheat, oat) and has lower potential as a soybean or cotton feeder. Howerver, S. frugiperda food intake regulation appears to be triggered by a complex of different mechanisms. Thus, S. frugiperda can also damage soybean and cotton and adapt to them in the absence of preferred hosts. <![CDATA[Optimization of spray deposition and Tetranychus urticae control with air assisted and electrostatic sprayer]]> ABSTRACT: Improved spray deposition can be attained by electrostatically charging spray droplets, which increases the attraction of droplets to plants and decreases operator exposure to pesticide and losses to the environment. However, this technique alone is not sufficient to achieve desirable penetration of the spray solution into the crop canopy; thus, air assistance can be added to the electrostatic spraying to further improve spray deposition. This study was conducted to compare different spraying technologies on spray deposition and two-spotted spider mite control in cut chrysanthemum. Treatments included in the study were: conventional TJ 8003 double flat fan nozzles, conventional TXVK-3 hollow cone nozzles, semi-stationary motorized jet launched spray with electrostatic spray system (ESS) and air assistance (AA), and semi-stationary motorized jet launched spray with AA only (no ESS). To evaluate the effect of these spraying technologies on the control of two-spotted spider mite, a control treatment was included that did not receive an acaricide application. The AA spraying technology, with or without ESS, optimized spray deposition and provided satisfactory two-spotted spider mite control up to 4 days after application. <![CDATA[Quantitative genetics theory for genomic selection and efficiency of genotypic value prediction in open-pollinated populations]]> ABSTRACT: Quantitative genetics theory for genomic selection has mainly focused on additive effects. This study presents quantitative genetics theory applied to genomic selection aiming to prove that prediction of genotypic value based on thousands of single nucleotide polymorphisms (SNPs) depends on linkage disequilibrium (LD) between markers and QTLs, assuming dominance and epistasis. Based on simulated data, we provided information on dominance and genotypic value prediction accuracy, assuming mass selection in an open-pollinated population, all quantitative trait loci (QTLs) of lower effect, and reduced sample size. We show that the predictor of dominance value is proportional to the square of the LD value and to the dominance deviation for each QTL that is in LD with each marker. The weighted (by the SNP frequencies) dominance value predictor has greater accuracy than the unweighted predictor. The linear × linear, linear × quadratic, quadratic × linear, and quadratic × quadratic SNP effects are proportional to the corresponding linear combinations of epistatic effects for QTLs and the LD values. LD between two markers with a common QTL causes a bias in the prediction of epistatic values. Compared to phenotypic selection, the efficiency of genomic selection for genotypic value prediction increases as trait heritability decreases. The degree of dominance did not affect the genotypic value prediction accuracy and the approach to maximum accuracy is asymptotic with increases in SNP density. The decrease in the sample size from 500 to 200 did not markedly reduce the genotypic value prediction accuracy. <![CDATA[Artificial neural network for prediction of the area under the disease progress curve of tomato late blight]]> ABSTRACT: Artificial neural networks (ANN) are computational models inspired by the neural systems of living beings capable of learning from examples and using them to solve problems such as non-linear prediction, and pattern recognition, in addition to several other applications. In this study, ANN were used to predict the value of the area under the disease progress curve (AUDPC) for the tomato late blight pathosystem. The AUDPC is widely used by epidemiologic studies of polycyclic diseases, especially those regarding quantitative resistance of genotypes. However, a series of six evaluations over time is necessary to obtain the final area value for this pathosystem. This study aimed to investigate the utilization of ANN to construct an AUDPC in the tomato late blight pathosystem, using a reduced number of severity evaluations. For this, four independent experiments were performed giving a total of 1836 plants infected with Phytophthora infestans pathogen. They were assessed every three days, comprised six opportunities and AUDPC calculations were performed by the conventional method. After the ANN were created it was possible to predict the AUDPC with correlations of 0.97 and 0.84 when compared to conventional methods, using 50 % and 67 % of the genotype evaluations, respectively. When using the ANN created in an experiment to predict the AUDPC of the other experiments the average correlation was 0.94, with two evaluations, 0.96, with three evaluations, between the predicted values of the ANN and they were observed in six evaluations. We present in this study a new paradigm for the use of AUDPC information in tomato experiments faced with P. infestans. This new proposed paradigm might be adapted to different pathosystems. <![CDATA[Survey of fungi associated with cassava root rot from different producing regions in Brazil]]> ABSTRACT: Although root rot is one of the major diseases affecting Brazilian cassava (Manihot esculenta Crantz.), little is known about the diversity of root rot pathogens. In this study, diseased plants exhibiting root rot symptoms were collected from cassava-producing regions in five Brazilian states: Bahia, Sergipe, Paraíba, Maranhão, Tocantins, and Paraná. Seventy isolates were obtained and assigned to species complexes based on rDNA's ITS (internal transcribed spacer of the ribosomal DNA) region (ITS1, ITS2 and 5.8S). A total of seven species complexes was found belonging to the genus Fusarium (56/74), followed by Lasiodiplodia (8/74), Neoscytalidium (6/74), and Diaporthe/Phomopsis complex (2/74), Phytophthora, and Corallomycetella (1/74 each). These species were distributed differently according to sample locations and states, but overall, the F. solani species complex (FSSC) was the most prevalent. A number of phylogenetic lineages had not been previously reported as being associated with cassava-root rot disease, such as: F. graminearum (FGSC), F. incarnatum-equiseti (FIESC) and F. chlamydosporum (FCSC) complexes, and a phylogenetic lineage most closely related to P. phaseolorum. Results suggest the need to improve knowledge of the species associated with cassava, including multilocus phylogeny for a more specific characterization, and differences in the resistance background associated with these species, as a strategy to incorporate resistance to multiple pathogens in cassava breeding programs. <![CDATA[Temporal progress and spatial patterns of quiescent diseases in guava influenced by sanitation practices]]> ABSTRACT: Postharvest diseases are a major problem in guava crops as the symptoms normally appear during fruit ripening. This study aimed to detect and characterize the temporal dynamics and spatial patterns of the most important guava diseases in orchards with and without removal of crop residues as a sanitation practice. The experiment was conducted in an orchard of ‘Pedro Sato’ guavas, over two consecutive seasons, and data were collected from the flowering to the fruit ripening stage. In immature guavas treated with paraquat and ethrel, Colletotrichum spp. was detected from the 5th day of incubation. Anthracnose was detected in flowers at incidences higher than 50 % and black spot in fruit larger than 5.5 cm in length. The monomolecular and the exponential models provided the best fit to anthracnose and black spot incidence progress curve data, respectively. Both diseases showed a predominantly random spatial pattern in the orchard. The removal of crop residues reduced the rate of disease progress in at least one season, and was effective in reducing the areas under the quiescent disease progress curves (AUDPC) of anthracnose. Anthracnose incidence increased from 57 to 96 % and black spot from 1 to 48 %, respectively, at fruit maturation levels 1 and 3. A negative correlation was found between disease incidence and the color of the fruit skin (°h). Fruit harvested during the later maturation stages showed higher incidence of the diseases. Due to the wide distribution and early infection of quiescent diseases, starting at flowering, preventive management should consider disease monitoring and removal of crop residues. <![CDATA[Replacement of native vegetation alters the soil microbial structure in the Pampa biome]]> ABSTRACT: Land use change is one of the the major factors related to soil degradation and alterations in soil microbial diversity and structure. In this study, we aimed to evaluate the microbial shifts caused by deforestation of a small area of a natural forest for the introduction of a pasture in the Brazilian Pampa. The microbial abundance and structure were evaluated by molecular approaches based on quantitative Polymerase Chain Reaction (qPCR) and Ribosomal Intergenic Spacer Analysis (RISA). The microbial communities did not present significant quantitative differences, but the environmental impact caused by deforestation changed the structure of the bacterial and archaeal communities. Taking into account the percentage of shared OTUs (operational taxonomic units) of each domain evaluated, we concluded that the domain Bacteria were more influenced by the deforestation than the Archaea. A total of 22 % of bacterial OTUs and 50 % of the archaeal OTUs were shared between forest and grassland leading us to conclude that the environment evaluated presented a core microbial community that did not suffer modification caused by land use change. <![CDATA[<em>Arabidopsis thaliana</em> as a model host for <em>Brevipalpus</em> mite-transmitted viruses]]> ABSTRACT: Brevipalpus-transmitted viruses (BTV) are a taxonomically diverse group of plant viruses which severely affect a number of major crops. Members of the group can be sub-classified into cytoplasmic (BTV-C) or nuclear type (BTV-N) according to the accumulation sites of virions in the infected plant cells. Both types of BTV produce only local infections near the point of inoculation by viruliferous mites. Features of BTV-plant interactions such as the failure of systemic spread in their natural hosts are poorly understood. In this study we evaluated Arabidopsis thaliana, a model plant commonly used for the study of plant-virus interactions, as an alternative host for BTV. Infection of Arabidopsis with the BTV-N Coffee ringspot virus and Clerodendrum chlorotic spot virus, and the BTV-C Solanum violaefolium ringspot virus, were mediated by viruliferous Brevipalpus mites collected in the wild. Upon infestation, local lesions appeared in 7 to 10 days on leaves of, at least, 80 % of the assayed plants. Presence of viral particles and characteristic cytopathic effects were detected by transmission electron microscopy (TEM) and the viral identities confirmed by specific reverse-transcriptase polymerase chain reaction (RT-PCR) and further amplicon sequencing. The high infection rate and reproducibility of symptoms of the three different viruses assayed validate A. thaliana as a feasible alternative experimental host for BTV. <![CDATA[Advances in induced resistance by natural compounds: towards new options for woody crop protection]]> ABSTRACT: The activation of defensive responses of plants is a promising tool for controlling pests in conventional agriculture. Over the last few years, several compounds have been studied to protect crops from pests, without displaying direct toxicity for pathogenic organisms. These compounds have the ability to induce a priming state on the plants that results in resistance (or tolerance) against subsequent infection by a pathogen. In terms of molecular response, induced plant defense involves a broad number of physical and biochemical changes such as callose deposition or phenolic compounds, activation of salicylic and/or jasmonic acid pathways or synthesis of defense-related enzymes. Despite the large number of studies performed to ascertain the physiological and biochemical basis of induced resistance, only a few resistance-activating compounds have been studied as a real alternative to classic means of control and the studies geared towards incorporating induced resistance into disease management programs are relatively rare. The incorporation of natural resistance inducer in pest management programs of woody crops, alone or in combination with classical methods, could be a reliable method for reducing the amount of chemical residues in the environment. In this review, we discuss the current knowledge of induced resistance in woody crops, focusing on the mode of action of compounds authorized for conventional agriculture. We conclude by discussing the environmental and economic advantages of applying resistance inducers to conventional agriculture with special emphasis on natural compounds.