Key management practices that explain soybean yield gaps across the North Central US

Increasing planting density is one of the key management practices to enhance soybean yield. A 2-yr field experiment was conducted in 2018 and 2019 including six planting densities and two soybean cultivars to determine the effects of planting density on branch number and yield, and analyze the contribution of branches to yield. The yield of ZZXA12938 was 4389 kg ha−1, which was significantly higher than that of ZH13 (+22.4%). In combination with planting year and cultivar, the soybean yield increased significantly by 16.2%, 31.4%, 41.4%, and 46.7% for every increase in density of 45,000 plants ha−1. Yield will not increase when planting density exceeds 315,000 plants ha−1. A correlation analysis showed that pod number per plant increased with the increased branch number, while pod number per unit area decreased; thus, soybean yield decreased. With the increase of branch number, the branch contribution to yield increased first, and then plateaued. ZH13 could produce a high yield under a lower planting density due to more branches, while ZZXA12938 had a higher yield potential under a higher planting density due to the smaller branch number and higher tolerance to close planting. Therefore, seed yield can be increased by selecting cultivars with a little branching capacity under moderately close planting.

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Assessing benefits of artificial drainage on soybean yield in the North Central US region

Agricultural Water Management ◽

10.1016/j.agwat.2020.106425 ◽

2021 ◽

Vol 243 ◽

pp. 106425

Author(s):

Spyridon Mourtzinis ◽

José F. Andrade ◽

Patricio Grassini ◽

Juan I. Rattalino Edreira ◽

Hans Kandel ◽

...

Keyword(s):

North Central ◽

Soybean Yield ◽

Artificial Drainage ◽

The North

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Impact of Management Practices on Prevalence of Soybean Sclerotinia Stem Rot in the North-Central United States and on Farmers' Decisions Under Uncertainty

Plant Disease ◽

10.1094/pdis.2003.87.9.1048 ◽

2003 ◽

Vol 87 (9) ◽

pp. 1048-1058 ◽

Cited By ~ 21

Author(s):

A. L. Mila ◽

A. L. Carriquiry ◽

J. Zhao ◽

X. B. Yang

Keyword(s):

United States ◽

Seed Treatment ◽

Management Practices ◽

The United States ◽

Stem Rot ◽

Sclerotinia Stem Rot ◽

Weather Variables ◽

North Central ◽

The North ◽

Attainable Yield

Regional prevalence of soybean Sclerotinia stem rot (SSR), caused by Sclerotinia sclerotiorum, was modeled using management practices (tillage, herbicide, manure and fertilizer application, and seed treatment with fungicide) and summer weather variables (mean monthly air temperature and precipitation for the months of June, July, August, and September) as inputs. Logistic regression analysis was used to estimate the probability of stem rot prevalence with disease data from four states in the north-central region of the United States (Illinois, Iowa, Minnesota, and Ohio). Goodness-of-fit criteria indicated that the resulting model explained well the observed frequency of occurrence. The relationship of management practices and weather variables with soybean yield was examined using multiple linear regression (R 2 = 0.27). Variables significant to SSR prevalence, including average air temperature during July and August, precipitation during July, tillage, seed treatment, liquid manure, fertilizer, and herbicide applications, were also associated with high attainable yield. The results suggested that SSR occurrence in the north-central region of the United States was associated with environments of high potential yield. Farmers' decisions about SSR management, when the effect of management practices on disease prevalence and expected attainable yield was taken into account, were examined. Bayesian decision procedures were used to combine information from our model (prediction) with farmers' subjective estimation of SSR incidence (personal estimate, based on farmers' previous experience with SSR incidence). MAXIMIN and MAXIMAX criteria were used to incorporate farmers' site-specific past experience with SSR incidence, and optimum actions were derived using the criterion of profit maximization. Our results suggest that management practices should be applied to increase attainable yield despite their association with high disease risk.

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Orchids on the edge: threatened orchid recovery in the North Central region, 2003-2009

Proceedings of the Royal Society of Victoria ◽

10.1071/rs10017 ◽

2010 ◽

Vol 122 (2) ◽

pp. 84 ◽

Cited By ~ 1

Author(s):

Geoff Nevill

Keyword(s):

Central Region ◽

Key Management ◽

North Central Region ◽

Knowledge Gaps ◽

Future Directions ◽

North Central ◽

Management Actions ◽

The North

This paper presents an overview of activities to conserve a suite of threatened orchid taxa within the North Central region between 2003 and 2009. Historical and current threats to orchid populations are outlined and management responses detailed, together with results of key management actions. Knowledge gaps are identified, with past and current actions to address some of these included. Future directions for the conservation of threatened orchids in the region are briefly discussed.

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A machine learning interpretation of the contribution of foliar fungicides to soybean yield in the north‐central United States

Scientific Reports ◽

10.1038/s41598-021-98230-2 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Denis A. Shah ◽

Thomas R. Butts ◽

Spyridon Mourtzinis ◽

Juan I. Rattalino Edreira ◽

Patricio Grassini ◽

...

Keyword(s):

United States ◽

Machine Learning ◽

Sowing Date ◽

Yield Response ◽

North Central ◽

Soybean Yield ◽

Factors Associated ◽

The North ◽

Central United States ◽

Foliar Fungicide

AbstractFoliar fungicide usage in soybeans in the north-central United States increased steadily over the past two decades. An agronomically-interpretable machine learning framework was used to understand the importance of foliar fungicides relative to other factors associated with realized soybean yields, as reported by growers surveyed from 2014 to 2016. A database of 2738 spatially referenced fields (of which 30% had been sprayed with foliar fungicides) was fit to a random forest model explaining soybean yield. Latitude (a proxy for unmeasured agronomic factors) and sowing date were the two most important factors associated with yield. Foliar fungicides ranked 7th out of 20 factors in terms of relative importance. Pairwise interactions between latitude, sowing date and foliar fungicide use indicated more yield benefit to using foliar fungicides in late-planted fields and in lower latitudes. There was a greater yield response to foliar fungicides in higher-yield environments, but less than a 100 kg/ha yield penalty for not using foliar fungicides in such environments. Except in a few production environments, yield gains due to foliar fungicides sufficiently offset the associated costs of the intervention when soybean prices are near-to-above average but do not negate the importance of disease scouting and fungicide resistance management.

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Soil carbon lost from Mollisols of the North Central U.S.A. with 20 years of agricultural best management practices

Agriculture Ecosystems & Environment ◽

10.1016/j.agee.2012.08.011 ◽

2012 ◽

Vol 162 ◽

pp. 68-76 ◽

Cited By ~ 46

Author(s):

Gregg R. Sanford ◽

Joshua L. Posner ◽

Randall D. Jackson ◽

Christopher J. Kucharik ◽

Janet L. Hedtcke ◽

...

Keyword(s):

Soil Carbon ◽

Best Management Practices ◽

Management Practices ◽

North Central ◽

Best Management ◽

The North ◽

Agricultural Best Management Practices

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Yield gap in milk production is considerable in Indian Himalayan state of Meghalaya

Journal of Dairy Research ◽

10.1017/s002202992100008x ◽

2021 ◽

pp. 1-7

Author(s):

Evans Kemboi ◽

S. M. Feroze ◽

Ram Singh ◽

Jabir Ahmed ◽

Hehlangki Tyngkan

Keyword(s):

Milk Production ◽

Milk Yield ◽

Management Practices ◽

Total Yield ◽

Stocking Density ◽

Farming System ◽

Smallholder Farming ◽

Yield Gap ◽

The North ◽

Yield Gaps

Abstract Yield gaps in milk production are here defined as the differentials between the actual yield obtained by the dairy farmer and the potential farm yield (production achieved by the top 10% of farmers: Gap 2) as well as the differential between this potential farm yield and the yield registered in the research stations (Gap 1). Assessment of yield gaps provides valuable information on potential production enhancement and drivers behind yield gaps. Milk production can be increased by narrowing the predominant large yield gaps in resource-poor smallholder farming system. Hence, this study assessed the milk yield gap and factors affecting the yield gap in Ri-Bhoi district of Meghalaya, a state located in the north-eastern Himalayan region of India. This research paper provides a scope for exploring the possibilities for improving dairy production in the state as well as contributing to literature through incorporating crucial determinants responsible for milk yield gap. A sample of 81 respondents was drawn purposely from two blocks of the district. The results indicated that the average number of cattle per household was 9.38 in standard animal units. The total yield gap was estimated at 6.20 l (91.06%) per day, composed of 0.80 l (11.76%) per day of yield gap I and 5.40 l (79.30%) per day of yield gap II. This demonstrates that the top performing farms were achieving a production level not dissimilar to that obtained on the research stations, but many were doing far less well. The size of cattle shed, dairy farming experience, concentrate price and human labour were the important determinants of the yield gap. Hence, encouraging the right stocking density of cattle, training on the preparations of home-made concentrates, access to cheap and quality concentrates, incorporating training and experience sharing on proper dairy management practices and use of technology could benefit the dairy farmers of the region.

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