Use of climate information in soybean farming on the Argentinean pampas

Bert, Federico; Podestá, Guillermo; Satorre, Emilio H.; Messina, Carlos D.

doi:10.3354/cr033123

Cited by 5 publications

(7 citation statements)

References 42 publications

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“…Prior to the sowing date, which is one of the most yield-determining agronomic management decisions (Rattalino Edreira et al, 2017;Vitantonio-Mazzini et al, 2021), skillful probabilistic seasonal climate forecasts can provide information about expected rainfall in the growing season. Although several studies have documented the effect of the ENSO in the soybean yields in the South American Pampas (Araneda-Cabrera et al, 2021;Monzon et al, 2007), there is a lack of knowledge about the ability of probabilistic seasonal forecasts to support farmers management decisions and to optimize the agronomic management practices for each season (Bert et al, 2007).…”

Section: Introductionmentioning

confidence: 99%

Season-specific management strategies for rainfed soybean in the South American Pampas based on a seasonal precipitation forecast

Rizzo

Mazzilli

Ernst

et al. 2022

Agricultural Systems

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Global climate change is resulting in more frequent and more damaging extreme events affecting the performance of production systems. It is imperative to develop good season-specific crop management recommendations to help farmers to improve their adaptive capacity to a changing climate one season at a time. OBJECTIVE: We aimed to evaluate the skill of the International Research Institute for Climate and Society (IRI) seasonal precipitation forecasts and the interaction between the forecasted seasonal precipitation scenarios and management practices for rainfed soybean cropping systems using a crop simulation model. METHODS: We used a crop simulation model (CROPGRO-Soybean) coupled with weather data to assess the potential use of the IRI seasonal precipitation forecasts as a tool to optimize season-specific management strategies for rainfed soybean in Uruguay. We used a total of 620-668 IRI seasonal precipitation forecasts released from 2003 to 2016 for each of the five weather stations located in the main soybean producing area. The analysis was performed for two soybean cropping systems (i.e., sown as a single crop or as double-cropped soybean), for

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Section: Introductionmentioning

confidence: 99%

Season-specific management strategies for rainfed soybean in the South American Pampas based on a seasonal precipitation forecast

Rizzo

Mazzilli

Ernst

et al. 2022

Agricultural Systems

View full text Add to dashboard Cite

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“…In this sense, Bert et al. () propose that climatic forecast, together with planting date, is the first‐order hierarchical decision to seek yield potential or to handle water stress scenarios. These tools would allow adequate crop development patterns to match yield‐defining critical crop phenological periods with a better water balance.…”

Section: Discussionmentioning

confidence: 99%

“…For our conditions, after drought escape strategy is defined by early or delayed planting (Bert et al., ), ensuring maximum radiation capture provides high yielding levels in the years evaluated. This goal is achieved by 0.25 m row spacing, 60 pl per m 2 stand density and a genotype having high yield potential.…”

Section: Discussionmentioning

confidence: 99%

“…Our results suggest that stand density, row spacing and genotype selection are second-order hierarchical decisions in designing strategic managements facing to a possible climatic scenario context. In this sense, Bert et al (2007) propose that climatic forecast, together with planting date, is the first-order hierarchical decision to seek yield potential or to handle water stress scenarios. These tools would allow adequate crop development patterns to match yield-defining critical crop phenological periods with a better water balance.…”

Section: Total Canopy N Uptake N Use Efficiency and Harvest Indexmentioning

confidence: 99%

“…Deciding between stress tolerance versus yield potential management strategies relies on well-documented weather scenarios and extended climatic forecasts (Bert, Podestá, Satorre, & Messina, 2007;Bert, Satorre, Toranzo, & Podestá, 2006;Chapman & De la Vega, 2002). However, a yield potential strategy can have a disproportionally negative impact on yield in a water deficit scenario.…”

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confidence: 99%

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Exploring soybean management options for environments with contrasting water availability

Mauro

Borrás

Rugeroni³

et al. 2019

J Agronomy Crop Science

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Soybean is commonly cultivated under rainfed conditions being water availability the main constraint. We evaluated the performance of different managements under contrasting water availability to test possible trade‐offs among managements, and to determine physiological variables explaining these yield differences. Four treatments were designed through specific combinations of cultivar, row spacing and stand density. They were classified as stress tolerance or yield potential strategies and were evaluated under two contrasting water availability treatments. Treatments ranged from 349 to 954 mm total water availability. Water stress treatments yielded 72% and 59% of the well‐watered treatment each year, similar to frequent soybean water stress levels for our production region. Management treatments showed significant yield differences (p < 0.05), but the management × water availability interaction did not (p = 0.42). No management option helped reduce negative water stress effects. Highest yields were achieved using 0.25 m row spacing, a stand density of 60 pl per m2, and a high yield potential genotype. Yield variations were explained by differences in harvested seeds per unit area (R2 = 0.75; p < 0.001) and total N uptake at maturity (R2 = 0.93; p < 0.001) across environments. Because management strategies specifically tailored to cope with water shortages showed limited value, farmers need to target yield potential management options.

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Value of perfect ENSO phase predictions for agriculture: evaluating the impact of land tenure and decision objectives

et al. 2009

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In many places, predictions of regional climate variability associated with the El Niño-Southern Oscillation phenomenon offer the potential to improve farmers' decision outcomes, by mitigating the negative impacts of adverse conditions or by taking advantage of favorable conditions. While the notion that climate forecasts are potentially valuable has been established, questions of when they may be more or less valuable have proven harder to resolve. Using simulations, we estimate the expected value of seasonal climate information under alternative assumptions about (a) land tenure (ownership vs. short-term leases) and (b) the decision maker's objective function (expected utility vs. prospect theory value function maximization), Senior authorship is shared. 146Climatic Change (2009) 97:145-170 employing a full range of plausible parameter values for each objective function. This allows us to show the extent to which the value of information depends on risk preferences, loss aversion, wealth levels and expectations, as well as situational constraints. Our results demonstrate in a non-laboratory decision context that, in some cases, psychologically plausible deviations from expected utility maximization can lead to substantial differences in estimates of the expected value of climate forecasts. Efforts to foster effective use of climate information and forecasts in agriculture must be grounded in a firm understanding of the goals, objectives and constraints of decision makers.

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Use of climate information in soybean farming on the Argentinean pampas

Cited by 5 publications

References 42 publications

Season-specific management strategies for rainfed soybean in the South American Pampas based on a seasonal precipitation forecast

Season-specific management strategies for rainfed soybean in the South American Pampas based on a seasonal precipitation forecast

Exploring soybean management options for environments with contrasting water availability

Value of perfect ENSO phase predictions for agriculture: evaluating the impact of land tenure and decision objectives

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