Espaçamento reduzido e plantio cruzado associados a diferentes densidades de plantas em soja

Balbinot, Alvadi Antônio; Procópio, S. de O.; Costa, Joaquim Mariano; Kosinski, Cristiano Luiz; Panison, Fernando; Debiasi, Henrique; Franchini, J. C.

doi:10.5433/1679-0359.2015v36n5p2977-2986

Cited by 3 publications

(4 citation statements)

References 9 publications

(18 reference statements)

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“…Each cell corresponds to 1 m 2 containing approximately 30 soybean plants, totaling 300 000 plants per hectare, a density routinely used on Brazilian farms. 32 Each cell can be occupied by multiple insect life stages simultaneously. It was assumed that the study of the dynamics of the stink bug and the parasitoid populations took place between the early reproductive stage (soybean development stage R 1 ), when E. heros usually starts to colonize a soybean area, until the crop ripens and the stink bugs disperse to alternative host plants, 33 corresponding to a period of approximately 80 days.…”

Section: Methodsmentioning

confidence: 99%

“…Four rows and columns (i = {1, 2, 203, 204} and j = {1, 2, 203, 204}) were used as xed edges throughout the simulation, resulting in an area available for insects of 200 × 200 cells, representing 4 hectares of soybean cultivation. Each cell corresponds to 1 m 2 containing approximately 30 soybean plants, totaling 300,000 plants per hectare, a density routinely used on Brazilian farms (Balbinot Junior et al 2015). Each cell can be occupied by multiple insect life stages simultaneously.…”

Section: Computational Modelingmentioning

confidence: 99%

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Release strategies of Telenomus podisi for control of Euschistus heros: a computational modeling approach

Weber

Garcia

Bueno

et al. 2022

Pest Management Science

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The egg-parasitoid wasp Telenomus podisi has received attention as a biological-control agent for one of the most important soybean pests in Brazil, the stink bug Euschistus heros. As yet, no studies have conclusively established strategies for the release of T. podisi. We developed a computational model employing cellular automata to investigate release strategies for T. podisi in soybean crops, in order to optimize the use of these wasps in managing E. heros. A computational model was developed, using cellular automata in the C programming language and assuming a two-dimensional grid of cells corresponding to a soybean eld. The biological dynamics of E. heros and T. podisi were programmed. The following parameters for release strategy were investigated: release mode, number of releases, number of parasitoids per hectare per release, and spacing between release points or strips. The sensitivities of the release and movement parameters were analyzed. The release strategies capable of maintaining an E. heros population below the Economic Threshold level involved releasing a total of at least 15,000 female parasitoids per hectare, in three or four releases of 5,000 or more. A 25-m spacing between release points or strips was indicated. The theoretical results produced by the computational model are expected to guide future eld studies to improve T. podisi release plans for managing E. heros in soybeans.

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Section: Methodsmentioning

confidence: 99%

Section: Computational Modelingmentioning

confidence: 99%

Release strategies of Telenomus podisi for control of Euschistus heros: a computational modeling approach

Weber

Garcia

Bueno

et al. 2022

Pest Management Science

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“…The number of branches per plant (NBPL) was not selected in the stepwise model for PROD prediction, except for twin row spacing in the 2014/15 cropping season. Soybeans can produce a large number of branches, but with small sizes and low grain yield, or even unproductive ones (Balbinot Junior et al, 2015a). Generally, one of the main variables for phenotypic plasticity evaluations of a cultivar is NBPL .…”

Section: Stepwise Regressionmentioning

confidence: 99%

“…This leads to a research updating towards plant spatial arrangement, aiming to increase grain yield and crop profitability (Balbinot Junior et al, 2015a;Werner et al, 2016). Hence, alternative spatial arrangements such as narrow row spacing (0.20 to 0.30 m) (Balbinot Junior et al, 2015b) and crossed rows have been studied, in which half of the seeds are sown in one direction and the other half to the transverse direction (Balbinot Junior et al, 2015a).…”

Section: Introductionmentioning

confidence: 99%

Analysis of phenotypic plasticity in indeterminate soybean cultivars under different row spacing

Balbinot¹,

Oliveira²,

Zucareli³

et al. 2018

Aust J Crop Sci

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This study aimed to evaluate how branch and stem variables contribute to grain yield per plant of two indeterminate soybean cultivars at varied row spacing. Four experiments were conducted in the 2013/14 and 2014/15 cropping seasons under a randomized complete block design with three replications. Each experiment consisted of one row spacing: 0.2 m (narrow row), 0.5 m (traditional), 0.5 m (crossed rows), and 0.2/0.8 m (twin rows). We evaluated two cultivars (BRS 359 RR and BMX RR Potência) and three seeding rates: 150, 300, and 450 thousand seeds ha -1. Regarding phenotypic plasticity, grain production per plant was regarded as a dependent variable, while the number of branches per plant, the percentage of grain production from branches, and yield components of branches and stems as independent variables. Data underwent stepwise regression and principal component analysis. The results showed that number of pods per plant from branches is the most determinant variable of plasticity trait, regardless of row spacing. The number of pods per plant from branches and stems, the number of branches per plant, and the percentage of grain production from branches were associated with the plasticity. The number of grains per pod and the thousandgrain mass from branches and stems had no significant contribution to the soybean plasticity. Keywords:Glycine max (L.) Merrill; row spacing; seeding rate; stem; branches. Abbreviations: PROD_grain production per plant; NBPL_number of branches per plant; NPPLB_ number of pods per plant from branches; NPPLS_number of pods per plant from stems; NGPB_ number of grains per pod from branches; NGPS_number of grains per pod from stems; TGMB_thousand-grain mass from branches; TGMS_thousand-grain mass from stems; PGB_grain production from branches in %; SCWB_sequential climatological water balance; PCA_principal component analysis

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Densidade de plantas e desempenho produtivo da soja

Dörr,

Pinz,

Bratz

et al. 2023

R. G. Secr.

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A soja (Glycine max (L.) Merril) é uma espécie pertencente à família Fabaceae, com centro de origem e domesticação no continente Asiático. A área semeada aumenta a cada safra no Brasil, desde que foi introduzida no país no século XX. Por ser uma commodity de grande importância na alimentação humana e animal, o aumento da produtividade das lavouras é um desafio constante. Para isso devemos observar o comportamento das plantas em relação aos componentes do rendimento, como o número de plantas na área, número de vagens por planta, número de grãos por vagem e peso de grãos, que são determinantes para o potencial produtivo de uma lavoura. A população de plantas na área, por exemplo, pode influenciar sobre diversas as variáveis agronômicas, e desta forma, influenciando na produtividade da lavoura. O objetivo do presente trabalho foi avaliar o efeito da densidade de plantas do genótipo TMG 7161 RR no desempenho agronômico da cultura soja O delineamento experimental foi o inteiramente casualizado, com 4 tratamentos e 6 repetições. Os tratamentos foram 4 densidades de plantas do genótipo TMG 7161 RR (22, 29, 33 e 44 plantas m-2). As variáveis analisadas foram o diâmetro do caule principal, altura da primeira inserção, altura final de plantas, número de ramificações por plantas, número de vagens por planta, número de sementes por vagem, peso de mil grãos e produtividade por planta e por área. O aumento da densidade de plantas na área proporciona plantas de maior tamanho e com maior altura da primeira inserção de vagem. O desempenho produtivo por planta de soja não é afetado pela densidade de plantas, entretanto a produção de grãos por área aumenta linearmente conforme o aumento da densidade de plantas até 44 plantas por metro quadrado.

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Espaçamento reduzido e plantio cruzado associados a diferentes densidades de plantas em soja

Cited by 3 publications

References 9 publications

Release strategies of Telenomus podisi for control of Euschistus heros: a computational modeling approach

Release strategies of Telenomus podisi for control of Euschistus heros: a computational modeling approach

Analysis of phenotypic plasticity in indeterminate soybean cultivars under different row spacing

Densidade de plantas e desempenho produtivo da soja

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