Identification of Functional Genetic Variations Underlying Flooding Tolerance in Brazilian Soybean Genotypes.

Flooding is a frequent environmental stress that reduces soybean (Glycine max) growth and grain yield in many producing areas in the world, such as, e.g., in the United States, Southeast Asia and Southern Brazil. In these regions, soybean is frequently cultivated in lowland areas by rotating with rice (Oryza sativa), which provides numerous technical, economic and environmental benefits. Given these realities, this work aimed to characterize physiological responses, identify genes differentially expressed under flooding stress in Brazilian soybean genotypes with contrasting flooding tolerance, and select SNPs with potential use for marker-assisted selection. Soybean cultivars TECIRGA 6070 (flooding tolerant) and FUNDACEP 62 (flooding sensitive) were grown up to the V6 growth stage and then flooding stress was imposed. Total RNA was extracted from leaves 24 h after the stress was imposed and sequenced. In total, 421 induced and 291 repressed genes were identified in both genotypes. TECIRGA 6070 presented 284 and 460 genes up- and down-regulated, respectively, under flooding conditions. Of those, 100 and 148 genes were exclusively up- and down-regulated, respectively, in the tolerant genotype. Based on the RNA sequencing data, SNPs in differentially expressed genes in response to flooding stress were identified. Finally, 38 SNPs, located in genes with functional annotation for response to abiotic stresses, were found in TECIRGA 6070 and absent in FUNDACEP 62. To validate them, 22 SNPs were selected for designing KASP assays that were used to genotype a panel of 11 contrasting genotypes with known phenotypes. In addition, the phenotypic and grain yield impacts were analyzed in four field experiments using a panel of 166 Brazilian soybean genotypes. Five SNPs possibly related to flooding tolerance in Brazilian soybean genotypes were identified. The information generated from this research will be useful to develop soybean genotypes adapted to poorly drained soils or areas subject to flooding.

Molecular Characterisation of Soybean Osmotins and Their Involvement in Drought Stress Response.

Osmotins are multifunctional proteins belonging to the thaumatin-like family related to plant stress responses. To better understand the functions of soybean osmotins in drought stress response, the current study presents the characterisation of four previously described proteins and a novel putative soybean osmotin (GmOLPa-like). Gene and protein structure as well as gene expression analyses were conducted on different tissues and developmental stages of two soybean cultivars with varying dehydration sensitivities (BR16 and EMB48 are highly and slightly sensitive, respectively). The analysed osmotin sequences share the conserved amino acid signature and 3D structure of the thaumatin-like family. Some differences were observed in the conserved regions of protein sequences and in the electrostatic surface potential. P21-like present the most similar electrostatic potential to osmotins previously characterised as promoters of drought tolerance in Nicotiana tabacum and Solanum nigrum. Gene expression analysis indicated that soybean osmotins were differentially expressed in different organs (leaves and roots), developmental stages (R1 and V3), and cultivars in response to dehydration. In addition, under dehydration conditions, the highest level of gene expression was detected for GmOLPa-like and P21-like osmotins in the leaves and roots, respectively, of the less drought sensitive cultivar. Altogether, the results suggest an involvement of these genes in drought stress tolerance.

Proposal for an Embedded System Architecture Using a GNDVI Algorithm to Support UAV-Based Agrochemical Spraying.

An important area in precision agriculture is related to the efficient use of chemicals applied onto fields. Efforts have been made to diminish their use, aiming at cost reduction and fewer chemical residues in the final agricultural products. The use of unmanned aerial vehicles (UAVs) presents itself as an attractive and cheap alternative for spraying pesticides and fertilizers compared to conventional mass spraying performed by ordinary manned aircraft. Besides being cheaper than manned aircraft, small UAVs are capable of performing fine-grained instead of the mass spraying. Observing this improved method, this paper reports the design of an embedded real-time UAV spraying control system supported by onboard image processing. The proposal uses a normalized difference vegetation index (NDVI) algorithm to detect the exact locations in which the chemicals are needed. Using this information, the automated spraying control system performs punctual applications while the UAV navigates over the crops. The system architecture is designed to run on low-cost hardware, which demands an efficient NDVI algorithm. The experiments were conducted using Raspberry Pi 3 as the embedded hardware. First, experiments in a laboratory were conducted in which the algorithm was proved to be correct and efficient. Then, field tests in real conditions were conducted for validation purposes. These validation tests were performed in an agronomic research station with the Raspberry hardware integrated into a UAV flying over a field of crops. The average CPU usage was about 20% while memory consumption was about 70 MB for high definition images, with 4% CPU usage and 20.3 MB RAM being observed for low-resolution images. The average current measured to execute the proposed algorithm was 0.11 A. The obtained results prove that the proposed solution is efficient in terms of processing and energy consumption when used in embedded hardware and provides measurements which are coherent with the commercial GreenSeeker equipment.

Nitrogen management in wheat based on the normalized difference vegetation index (NDVI) / Manejo do nitrogênio em trigo baseado no índice de vegetação por diferença normalizada (NDVI)

ABSTRACT: Biomass production and nitrogen (N) accumulated in wheat shoots may be used for quantifying optimal topdressing nitrogen doses. The objective of this study was to develop and validate models for estimating the amount of biomass and nitrogen accumulated in shoots and the N topdressing dose of maximum technical efficiency in wheat using the normalized difference vegetation index (NDVI) measured by an active optical canopy sensor. Field experiments were carried out in two years and treatments consisted of N doses applied at plant emergence and as topdressing. NDVI, shoot biomass and N accumulated in shoots at the growth stage of six fully expanded leaves and grain yield were evaluated, being determined the topdressing N dose of maximum technical efficiency (DMTE). The NDVI was positively correlated to shoot biomass and N content in shoots and models for the relationship between these variables were developed and validated. The DMTE was negatively correlated with the NDVI value evaluated at the moment of N topdressing application. Thus, NDVI evaluation by an active optical canopy sensor can be used for nitrogen fertilization in variable rate, allowing the adjustment of applied N doses in different areas within a field.

RESUMO: A produção de biomassa e o conteúdo de nitrogênio (N) acumulado na parte aérea de trigo podem ser utilizados na quantificação da dose ótima de N em cobertura. O objetivo deste estudo foi desenvolver e validar modelos para a estimativa das quantidades de biomassa e nitrogênio acumulado na parte aérea e a dose de máxima eficiência técnica de N em cobertura em trigo utilizando o Índice de vegetação por diferença normalizada (NDVI) medido por sensor óptico ativo de dossel. Experimentos foram conduzidos a campo, em dois anos, e os tratamentos constaram de doses de N aplicadas na emergência das plantas e em cobertura. Foram avaliados o NDVI, a biomassa e a quantidade de N acumulada na parte aérea no estádio de seis folhas completamente expandidas e o rendimento de grãos, sendo determinada a dose de máxima eficiência técnica de N em cobertura (DMET). O NDVI apresentou correlação positiva com a biomassa e quantidade de N acumulada na parte aérea e modelos para as relações entre estas variáveis foram propostos e validados. A DMET correlacionou-se negativamente com o valor de NDVI avaliado no momento da aplicação de nitrogênio em cobertura. Assim, a avaliação do NDVI por sensor óptico ativo de dossel pode ser utilizada para a adubação nitrogenada em taxa variável, permitindo o ajuste da dose de N aplicada em diferentes locais da lavoura.

Variabilidade espacial da produtividade de milho irrigado e sua correlação com variáveis explicativas de planta / Spatial variability of grain yield of irrigated corn and its correlation with explanatory plant variables

RESUMO: Em decorrência da instabilidade da produtividade das principais culturas associada ao déficit hídrico, tem se tornado cada vez mais frequente a necessidade do uso de tecnologias como a irrigação e a agricultura de precisão (AP). O presente trabalho objetivou avaliar a variabilidade espacial da produtividade de grãos de milho e sua correlação com variáveis explicativas de planta em área irrigada. O estudo foi conduzido nas safras agrícolas 2010/2011 e 2011/2012, em área de 35ha, manejada em sistema plantio direto e irrigação por pivô central. Os componentes de produtividade e a produtividade de grãos foram avaliados seguindo uma malha amostral de 100x100m. A produtividade de grãos e a maior parte dos componentes de produtividade apresentaram baixa dispersão dos dados, condicionando a normalidade dos dados. A produtividade de grãos, mesmo com a irrigação, apresentou elevada variabilidade espacial. Na análise de trilha, verificaram-se altos coeficientes de determinação dos componentes de produtividade com a produtividade de grãos.

ABSTRACT: Due to yield instability of main crops associated to drought, the use of technologies such irrigation and precision agriculture (PA) have been recently adopted in large scale. This study had the objective to assess the spatial variability of corn yield and its correlation with explanatory plant variables in an irrigated field. The study was carried out during the growing seasons 2010/2011 and 2011/2012, in an area of 35ha managed under no-till and center-pivot irrigation. Corn yield and yield components were evaluated following a sampling grid of 100x100m. Grain yield and most yield components showed low dispersion data, resulting in data normality. Even under irrigation, corn yield showed high spatial variability. In path analysis, it was found high determination coefficients of corn yield with yield components.

Expression of an osmotin-like protein from Solanum nigrum confers drought tolerance in transgenic soybean.

BACKGROUND: Drought is by far the most important environmental factor contributing to yield losses in crops, including soybeans [Glycine max (L.) Merr.]. To address this problem, a gene that encodes an osmotin-like protein isolated from Solanum nigrum var. americanum (SnOLP) driven by the UBQ3 promoter from Arabidopsis thaliana was transferred into the soybean genome by particle bombardment. RESULTS: Two independently transformed soybean lines expressing SnOLP were produced. Segregation analyses indicated single-locus insertions for both lines. qPCR analysis suggested a single insertion of SnOLP in the genomes of both transgenic lines, but one copy of the hpt gene was inserted in the first line and two in the second line. Transgenic plants exhibited no remarkable phenotypic alterations in the seven analyzed generations. When subjected to water deficit, transgenic plants performed better than the control ones. Leaf physiological measurements revealed that transgenic soybean plants maintained higher leaf water potential at predawn, higher net CO2 assimilation rate, higher stomatal conductance and higher transpiration rate than non-transgenic plants. Grain production and 100-grain weight were affected by water supply. Decrease in grain productivity and 100-grain weight were observed for both transgenic and non-transgenic plants under water deficit; however, it was more pronounced for non-transgenic plants. Moreover, transgenic lines showed significantly higher 100-grain weight than non-transgenic plants under water shortage. CONCLUSIONS: This is the first report showing that expression of SnOLP in transgenic soybeans improved physiological responses and yield components of plants when subjected to water deficit, highlighting the potential of this gene for biotechnological applications.

Estimativa do potencial produtivo em trigo utilizando sensor óptico ativo para adubação nitrogenada em taxa variável / Wheat yield potential estimation using active optical sensor for site-specific nitrogen fertilization

A adubação nitrogenada em trigo é baseada no potencial produtivo da cultura, teor de matéria orgânica do solo e cultura antecessora. A definição do potencial produtivo é complexa, pois este varia com as condições meteorológicas de cada ano específico. O objetivo deste trabalho foi avaliar a relação entre o índice de vegetação por diferença normalizada (NDVI), medido por sensor óptico ativo e o rendimento de grãos em quatro cultivares de trigo, visando a desenvolver procedimentos para a adubação nitrogenada em cobertura em taxa variável. O experimento foi realizado em campo em 2009. Foram avaliados o NDVI em diferentes estádios de desenvolvimento e o rendimento de grãos. As leituras do NDVI ao longo do ciclo ativo foram eficientes em identificar variações de produtividade do trigo. Assim, o potencial de produtividade pode ser estimado através de medições desse índice durante a ontogenia da planta. Pode-se adotar um modelo único para descrever a relação entre NDVI e potencial produtivo para as cultivares testadas neste trabalho.

Nitrogen fertilization in spring wheat is based on yield potential, soil organic matter content and previous crop. Yield potential definition is difficult, since it is affected by weather conditions. The objective of this research was to evaluate the relationship between Normalized Difference Vegetation Index (NDVI) measured by an active sensor and grain yield of four wheat cultivars. The experiment was carried out at field conditions in 2009. NDVI in different growth stages and grain yield were evaluated. NDVI measured was efficient to detect growth variability generated by N availability and correlated well with grain yield for all cultivars tested, indicating that yield potential can be estimated by NDVI evaluations during crop ontogeny. One single model for the relationship between NDVI and yield potential can be used considering cultivars used in this research.

Densidade de plantas de milho híbrido em semeadura precoce no Rio Grande do Sul / Plant density of hybrid maize at early sowing date in Southern Brazil

A escolha da densidade de plantas e a sua adequação à época de semeadura são práticas de manejo importantes na determinação do rendimento de grãos de milho. Este trabalho foi realizado a fim de avaliar os efeitos da densidade de plantas sobre o rendimento de grãos e seus componentes em dois híbridos cultivados em semeadura precoce (agosto) no Rio Grande do Sul. O experimento foi conduzido em Eldorado do Sul, em 2006/07. Os tratamentos consistiram de quatro densidades de plantas (5,5; 7,3; 9,1 e 11pl m-2) e dois híbridos, um de folhas decumbentes (Dow 2B587) e outro de folhas eretas (NB 4214). A semeadura foi realizada em 22 de agosto de 2006. O rendimento de grãos do híbrido de folhas decumbentes aumentou linearmente com o incremento na densidade de 5,5 até 11pl m-2, alcançando 16t ha-1. Já no híbrido de folhas eretas, o rendimento aumentou de forma quadrática, sendo maximizado na densidade de 9,4pl m-2. O número de espigas por metro quadrado foi o componente que melhor explicou o aumento da produtividade com o incremento na densidade de plantas. O uso de densidades superiores a 9pl m-2 é uma estratégia efetiva para aumentar o rendimento de grãos sob alto nível de manejo em semeadura precoce (agosto).

The choice of plant density and sowing date are important management practices to determine maize grain yield. The objective of this study was to evaluate the effect of plant density on grain yield and its components for two maize hybrids at early sowing date (August) in the State of Rio Grande do Sul, Southern Brazil. The experiment was carried out in Eldorado do Sul (RS), during the 2006/07 growing season. Treatments consisted of four plant densities (5.5, 7.3, 9.1 and 11pl m-2) and two hybrids with contrasting leaf architecture, Dow 2B587 (decumbent leaves) and NB 4214 (erect leaves). The sowing date was August 22, 2006. Grain yield for the decumbent leaf hybrid increased linearly with the increment in plant density from 5.5 up to 11pl m-2, reaching 16t ha-1. Grain yield of the erect leaf hybrid, in turn, was maximized at 9.4pl m-2. The number of ears per square meter was the yield component that better explained maize productivity increase with increasing plant density. The use of plant populations higher than 9pl m-2 was an effective strategy to improve maize grain yield grown under high management level, at early sowing date (August) in Southern Brazil.