Strategic positioning of white oat genotypes in the organic system

Loro, Murilo Vieira; Carvalho, Ivan Ricardo; Silva, José Antônio Gonzalez da; Alban, Aljian Antônio; Challiol, Márcio Alberto; Lautenchleger, Francine

doi:10.18188/sap.v20i4.28638

Cited by 5 publications

(4 citation statements)

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“…FAEM 007 ( G 5 ) and IPR Andrômeda ( G 12 ) genotypes strongly contribute to the manifestation of the interaction, as they present the lower and upper extremes of the environmental index, respectively. Environmental variation provides changes in the relative average yield of genotypes, that is, the interaction G × E influences the GY of genotypes (Loro et al., 2022).…”

Section: Resultsmentioning

confidence: 99%

“…This fluctuation results from an environmental component, that is, from the interaction of genotypes × environments ( G × E ). Some positioning studies of white oat genotypes (Loro et al., 2022; Savick et al., 2023; Silva et al., 2015), wheat (Loro et al., 2023), and soybean (Pradebon et al., 2023) seek to understand the G × E interaction through methodologies like biometrics models to promote greater assertiveness in positioning.…”

Section: Introductionmentioning

confidence: 99%

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Decomposition of phenotypic variation of white oats by meteorological and geographic covariables

Schmidt¹,

Carvalho²,

Silva³

et al. 2023

Agronomy Journal

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White oat (Avena sativa L.) is a cold season grass, with a very important role, both in animal and human food, due to the chemical composition of its grains, which have, among other beneficial components, fiber soluble food products, beta‐glucans. Therefore, the demand for grains of the crop is maximized and it is important to increase grain production. This can be achieved through the adequate positioning of the genotypes in the growing environments to maximize the agronomic performance of the crop. Thus, the objective of this work was to decompose meteorological and geographic variables in the positioning of white oat genotypes. The study took place considering 39 genotypes of white oats in 21 environments (in 13 years), in six municipalities of Rio Grande do Sul, two locations in the state of Santa Catarina, ten in Paraná and three municipalities in the state of São Paulo. The average grain yield (kg ha−1) of the genotypes in each environment was used to determine the adaptability and stability of the genotypes through the application of the Genotype and Genotypes by Environments Interaction (GGE biplot) biometric method and the reaction norm. The reaction norm pointed out that the genotypes UPFPS Farroupilha, UPFA Gaudéria and URS Guará demonstrated general adaptability to all environments, while FAEM 006 and URS Charrua expressed stability, high grain yield and higher than average genetic value. The GGE biplot graphically demonstrated that the genotypes URS Monarca and IPR Artemis demonstrated the highest grain yield and high stability in the environments Eldorado do Sul ‐ RS (E7) and Pelotas ‐ RS. Identifying genotypes with superior agronomic performance in specific environments minimizes the effects of genotype x environment interaction. These white oat genotypes can be used as sources of alleles for the development of new genotypes.This article is protected by copyright. All rights reserved

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Decomposition of phenotypic variation of white oats by meteorological and geographic covariables

Schmidt¹,

Carvalho²,

Silva³

et al. 2023

Agronomy Journal

Self Cite

View full text Add to dashboard Cite

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“…Advancements in sustainable management practices for improving grain quality in the largest oat producing region in Brazil have pointed out the need for adjustment seeding density based on the currently most grown cultivars, which are characterized by short cycles and short plants (Silva et al, 2012;Romitti et al, 2017;Loro et al, 2021). A higher number of plants per area can improve plant competitiveness and suppress weeds, increase straw volume to prevent erosion, control soil moisture, and result in better maturation uniformity, reducing the use of preharvest agrochemicals.…”

Section: Introductionmentioning

confidence: 99%

Seeding density and lodging control using a calcium and potassium-based organomineral fertilizer in oat crops

Coppetti,

Da Silva,

Carvalho

et al. 2024

CLCS

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Technologies ensuring high crop yield and plant competitiveness without lodging can contribute to an efficient and sustainable management of oat crops. The objectives of this study were to evaluate the use of high seeding density in current oat cultivars grown in the northwestern Rio Grande do Sul (RS), Brazil; assess the effects of plant growth regulators on grain yield indicators, industrial grain quality, and stem structure; and evaluate a calcium and potassium-based organomineral product as a sustainable technology for controlling lodging. Two experiments were conducted in Augusto Pestana, RS, in a randomized block design. Experiment I (2021) was set up in a 4×3 factorial arrangement consisted of 4 oat seeding densities (100, 300, 600, and 900 seeds m-2) and 3 treatments with plant growth regulator (PGR) application (control; application of trinexapac-ethyl and organomineral product at the stage between the 1st and 2nd visible stem nodes). Experiment II (2022) was set up in a 4×4 factorial arrangement consisted of 4 seeding densities (100, 300, 600, and 900 seeds m-2) and 4 PGR application treatments (control; application of trinexapac-ethyl and organomineral product at the stage between the 1st and 2nd visible stem nodes; and sequential application of organomineral product at V4 and at the stage between the 1st and 2nd visible stem nodes). The results of both experiments showed the need for a higher seeding density (between 400 and 520 seeds m-2) than that recommended. High air temperatures and limiting soil water conditions increased the phytotoxic potential of trinexapac-ethyl in oat crops. Evaluations of the Ca and K-based organomineral product, as a sustainable technology for controlling plant lodging, requires further analysis in years with more favorable environmental conditions for oat crops.

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“…Multiple tools are genotype recommendations such as AMMI, GGE, REML/BLUP, and principal components. These are effective in recommending soybean genotypes , white oats (Savicki et al, 2023;Loro et al, 2022), and wheat (Segatto, et al, 2023).…”

Section: Introductionmentioning

confidence: 99%

Agronomic Performance and Selection of Ideal Soybean Genotypes

Vitor Tisott,

Carvalho,

Cesar Pradebon

et al. 2023

Agri-Environ Sci

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The study aimed to evaluate agronomic performance and select ideal soybean genotypes. The experiment happened at the Missions Agronomic Research and Results Center (CPRAM), located in Entre-Ijuís - Rio Grande do Sul, South Region of Brazil. The experiment used random blocks with 36 different types of soybeans in four different tests. The units of the experiment were 40 square meters. The research evaluated morphological and productive characters and meteorological data from the experiment's environment. The MGIDI index selected the genotypes DM 5958, BMX ZEUS, NS 6601, BMX FIBRA, and P 95R51 by potentiating the variables number of legumes per plant, the number of grains per plant, the thousand-grain weight, and the grain yield. The genotype selection with higher grain yield can be performed indirectly through the number of legumes per plant and legumes on the main stem.

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Strategic positioning of white oat genotypes in the organic system

Cited by 5 publications

References 0 publications

Decomposition of phenotypic variation of white oats by meteorological and geographic covariables

Decomposition of phenotypic variation of white oats by meteorological and geographic covariables

Seeding density and lodging control using a calcium and potassium-based organomineral fertilizer in oat crops

Agronomic Performance and Selection of Ideal Soybean Genotypes

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