Search

Made available in DSpace on 2022-05-01T07:59:07Z (GMT). No. of bitstreams: 0 Previous issue date: 2021-09-01 Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) Stimulant fertilization isthe supplementary application of low doses of foliar fertilizers to otherwise well-fertilized crops, and literature suggests that it may increase grain yield. However, the physiological mechanisms behind this potential yield increase are not well understood. This study investigated the effect of supplementary foliar nitrogen (N) in soybean [Glycine max (L.) Merr.] and maize (Zea mays) nutrition, photosynthetic parameters, antioxidant metabolism, agronomic parameters, and grain yield. We tested the presence or absence of low rates of late season (R3 and V10 of soybean and maize, respectively) foliar N fertilization in a main season soybean followed by an off-season maize. While there were no effects of N application on leaf nutrient concentration, the net photosynthetic rate, stomatal conductance, water use efficiency, and carboxylation efficiency increased due to foliar N fertilization in both crops. The improvement in photosynthesis occurred due to a concomitant increase in Rubisco activity and in the concentration of sugar in the leaves prior to grain filling. Foliar N fertilization also improved antioxidant metabolism, suggesting that fertilized plants were less affected by environmental stresses during their cycle. The improvement in the metabolic activity due to foliar N did not affect grains per plant but increased a hundred grain mass and grain yield of both soybean and maize. Our results suggest that foliar N applied as stimulant fertilizer is a promising strategy to increase yield of maize and soybean crops. Dep. of Crop Science College of Agricultural Sciences São Paulo State Univ. (UNESP) Dep. of Agronomy Kansas State Univ., 2004 Throckmorton Plant Sciences Center, 1712 Claflin Road Dep. of Crop Science College of Agricultural Sciences São Paulo State Univ. (UNESP) CNPq: 134588/2018-5 CNPq: 303119/2016-0

Nitrogen management is central to the economic and environmental dimensions of agricultural sustainability. Yield response to nitrogen fertilisation results from multiple interacting factors. Theoretical frameworks are lagging for the interaction between nitrogen and air temperature, the focus of this study. We analyse the relation between yield response to nitrogen fertiliser and air temperature in the critical period of yield formation for spring wheat in Australia, winter wheat in the US, and maize in both the US and Argentina. Our framework assumes (i) yield response to nitrogen fertiliser is primarily related to grain number per m2, (ii) grain number is a function of three traits: the duration of the critical period, growth rate during the critical period, and reproductive allocation, and (iii) all three traits vary non-linearly with temperature. We show that “high” nitrogen supply may be positive, neutral, or negative for yield under “high” temperature, depending on the part of the response curve captured experimentally. The relationship between yield response to nitrogen and mean temperature in the critical period was strong in wheat and weak in maize. Negative associations for both spring wheat in Australia and winter wheat with low initial soil nitrogen (< 20 kg N ha-1) in the US highlight the dominant influence of a shorter critical period with higher temperature; with high initial soil nitrogen (> 120 kg N ha-1) that favoured grain number and compromised grain fill, the relation between yield response to nitrogen and temperature was positive for winter wheat. The framework is particularly insightful where data did not match predictions; a non-linear function integrating development, carbon assimilation and reproductive partitioning bounded the pooled data for maize in the US and Argentina, where water regime, previous crop, and soil nitrogen overrode the effect of temperature on yield response to nitrogen fertilisation.

BACKGROUND Integrated wheat management strategies can affect grain yield and flour end-use properties. However, the effect of integrated management and its interaction with environmental factors on the phenolic acid profiles of wheat has not been reported. The phenolic acid profile has become another parameter for the evaluation of wheat quality due to its potential health benefits. RESULTS Year × location × management and year × management × genotype interactions were significant for the total phenolic content (TPC) of wheat samples. The year × location × management × genotype interaction was significant for the concentration of trans-ferulic acid and several other phenolic acids. Field management practices with no fungicide application (e.g., farmer's practice, enhanced fertility) may lead to increased accumulation of phenolic compounds, especially for WB4458, which is more susceptible to fungi infection. However, this effect was also related to growing year and location. Higher soil nitrogen content at sowing also seems to affect the TPC and phenolic acid concentration positively. CONCLUSION Wheat phenolic acid profiles are affected by genotype, field management, environment, and their interactions. Intensified field management, in particular, may lead to decreased concentration of wheat phytochemicals. The level of naturally occurring nitrogen in the soil may also affect the accumulation of wheat phytochemicals. © 2021 Society of Chemical Industry.

Nutrient management can reduce crop yield gaps, but available literature is mostly restricted to studies limited in time, geography, or in the number of nutrients evaluated. Our objective was to synthesize long-term experiments evaluating wheat (Triticum aestivum L.) yield and grain-N concentration (GNC) response to N, P, and K fertilizer rates and their interactions. We used data from three long-term (1966–2016) experiments conducted in Oklahoma (USA) comprising 155 site-years for yield (n = 8035) and 90 site-years for GNC (n = 4580). The last year of the experiments was the baseline to de-trend yield and GNC data. We first explored relationships between grain yield and GNC, grain N removal, apparent recovery of applied N in the grain (N recovery), and N-use efficiency (NUE) as affected by the presence and rate of N, P, and K across the entire dataset. Then, we subdivided the dataset into yield-environments based on the different data quartiles, and analyzed it using descriptive statistics, multi-level modeling, differences from the control, and conditional inference trees. Our main findings were: i) wheat yield was negatively related to GNC, but positively associated with N removal, N recovery, and NUE. ii) The co-application of P and, to a lesser extent, K, increased N removal and NUE but decreased GNC. iii) The proportion of variability in yield and GNC explained by fertilizer management increased with an increase in yield-environment. iv) Wheat yield response to N and to P were typically quadratic, although response to P was restricted to high yielding environments. v) Wheat GNC increased linearly with increases in N rate, but decreased with increases in P and K rate. vi) Conditional inference trees suggested that the co-application of P and K improved yields but decreased GNC. The co-application of P and K can increased wheat yield, N removal, and NUE, but the increases in yield were greater than those in N removal, thus decreasing GNC.

Crop production of a significant portion of the Great Plains has greatly simplified the landscape, which can affect insect pest outbreaks. The Hessian fly is an important economic pest of wheat, a major crop grown in the region. However, outbreaks are often limited to localized events, which may be difficult to predict. Better understanding of where Hessian fly outbreaks are more likely to occur would help producers make informed management decisions. Therefore, the objective of our study was to describe the spatial distribution of Hessian fly infestation within commercial wheat fields, while examining how a simplified landscape may contribute to the distribution of Hessian fly infestations. Spatial distribution modeling was conducted in select fields (n = 6) infested with Hessian fly puparia. A geographic information system was used to create sampling grids for each field (n = 34–50 sample points/field), with one meter row of plants sampled at each sample point. The number of puparia and plants infested at each sample point were used to construct Hessian fly distribution maps for each field. Correlations between environmental factors and fly distribution were then examined. Results show that host plants (wheat and grasses) adjacent to the borders of study fields did not affect the distribution of puparia or plants infested within the field. Rather, the proportion of wheat within a 1 km radius of sampled fields affected the level of Hessian fly infestation, with a smaller proportion of wheat within the 1 km radius increasing the probability of Hessian fly infestation in sampled fields. The results of this study show previously unknown distribution of Hessian fly infestation within commercial wheat fields, resulting in new hypotheses about Hessian fly management in agroecosystems.

We combined field studies to regional soil databases with the objective of presenting a protocol to forecast regional gains in winter wheat (Triticum aestivum L.) forage and grain yield and revenue, from liming or selecting a variety tolerant to acidic soils. First, we developed forage and grain yield response curves to soil pH using a variety by soil pH study conducted during 3 yr (2013–2015) at two Oklahoma locations. Second, we used a database of soil pH samples representing 93% of the wheat growing region of the state (n = 11,905) coupled with 15-yr average county yield and harvested area to estimate potential gains for grain-only and dual-purpose scenarios. Relative grain yield maximized at soil pH of 5.8 for sensitive varieties and 4.8 for tolerant varieties. Forage yield maximized at soil pH of 6.0 for sensitive varieties and 5.5 for tolerant varieties. About 35% of the region had pH limiting to dual-purpose and 28% to grain-only production. Liming could improve grain-only statewide yield in 0.14 Mg ha–¹ and revenue in US$19 ha–¹, and adoption of tolerant varieties could increase yield in 0.11 Mg ha–¹ and revenue in $10 ha–¹. Liming could improve dual-purpose revenue in $37 ha–¹ and variety selection in $28 ha–¹ due to improved yield and forage. Potential additional statewide wheat production resulting from variety selection is 53,800 Mg and from liming 82,500 Mg. Our protocol can be used to aid development of agricultural policies and research prioritization at regional levels where acidic soils are prevalent.

Made available in DSpace on 2020-12-10T20:07:09Z (GMT). No. of bitstreams: 0 Previous issue date: 2020-09-15 Kansas Wheat Alliance Kansas Agricultural Experiment Station (KAES) The complex and interactive effects of genotype (G), environment (E), and management (M) can be a barrier to the development of sound agronomic recommendations. We hypothesize that long-term variety performance trials (VPT) can be used to understand these effects and improve regional recommendations. Our objective was to explore long-term VPT data to improve management and variety-selection recommendations using winter wheat (Triticum aestivum L.) in the U.S. central Great Plains as a case-study. Data of grain yield, variety, and trial management were collected from 748 wheat VPT conducted in the states of Colorado, Kansas, and Oklahoma over nineteen harvest years (2000-2018) and 92 locations, resulting in 97,996 yield observations. Using 30-yr cumulative annual precipitation and growing degrees days, we partitioned the study region into 11 contiguous sub-regions, which we refer to as growing adaptation regions (GAR). We used variance component analysis, gradient boosted trees, and conditional inference trees to explore the management and variety trait effects within each GAR. For the variety trait analysis, the VPT dataset was reduced to account for varieties for which 17 agronomic traits and 11 disease/insect reaction ratings were available (65,264 yield observations). GAR accounted for 46 % of the total variation in grain yield, M for 32 %, residuals (including interactions) for 13 %, year for 7 %, and G for 2 %. Conditional inference trees identified interactions among management practices and their effects on yield within each GAR. For instance, water regime was the most important practice influencing wheat yield in the semi-arid western portion of the study region, followed by sowing date and fungicide. In dryland trials, there was typically an interaction between fungicide, sowing date, and tillage system, depending on GAR. Other management practices (e.g. dual-purpose management, crop rotation, and tillage practice) also significantly affected yield, depending on GAR. The main variety trait associated with increased yields depended on region and management combination. For instance, drought tolerance was the most important trait in dryland trials while stripe rust tolerance was more relevant in irrigated trials in the semi-arid region. In this research, we demonstrated an approach that uses widely available long-term VPT data to improve management and variety selection recommendations and can be used in other regions and crops for which long-term VPT data are available. Kansas State Univ, Dept Agron, Manhattan, KS 66506 USA Kansas State Univ, Dept Stat, Manhattan, KS 66506 USA Kansas State Univ, Dept Plant Pathol, Throckmorton Hall, Manhattan, KS 66506 USA Colorado State Univ, Dept Soil & Crop Sci, Ft Collins, CO 80523 USA Oklahoma State Univ, Dept Plant & Soil Sci, Stillwater, OK 74078 USA Sao Paulo State Univ, Dept Crop Prod, Jaboticabal, SP, Brazil Sao Paulo State Univ, Dept Crop Prod, Jaboticabal, SP, Brazil Kansas Wheat Alliance: GAGR004805BG5828

Foliar fungicides can account for a large portion of the yield gap in winter wheat (Triticum aestivum L.); however, their impacts on yield have been inconsistent in rainfed environments. We compiled a database of replicated field experiments and producer-reported fungicide and yield data from commercial fields to quantify the effects of fungicide application on winter wheat yield and yield stability. The database of field experiments (i.e., canopy level) included 56 non-inoculated environments spanning 12 growing seasons in eight Kansas locations, and was restricted to field experiments with direct comparisons between a foliar fungicide between Zadoks 40–55 and a side-by-side untreated control, resulting in 393 mean yield comparisons resulting from 3226 yield observations. The producer survey included genotype and fungicide management data from 654 commercial Kansas wheat fields cultivated across three growing seasons. Grain yield and weather conditions in the experimental and producer-reported database were similar, with seasonal precipitation ranging from ˜150 to 1035 mm and average grain yield of ˜3900 kg ha−1 with a ˜7000 kg ha−1 range. Foliar fungicide application resulted in 7.8 % average yield gain in the canopy-level data, ranging from −27 % to +97 %. Yield differences due to fungicide were strongly related to precipitation and to the ratio of precipitation and reference evapotranspiration (WS:WD) during the spring in the experimental data. Grain yield responsiveness to fungicide associated with the responsiveness of green canopy cover, kernel weight, biomass, and harvest index. Analysis of covariance suggested that grain yield usually decreased with increases in disease susceptibility in the absence of foliar fungicides; however, yield-disease relationships were either neutral or positive in the presence of fungicides. Average yield gain for resistant varieties was ˜166 kg ha−1 (5.6 %), which was lower than for intermediate (˜199 kg ha−1; 6.9 %) or susceptible genotypes (˜598 kg ha−1; 16.9 %). Foliar fungicides increased yield stability across genotypes at the canopy level and at the commercial field level. In the commercial-field level data, 53 % of the fields received foliar fungicide, with higher frequency in growing seasons with greater WS:WD (which were also higher yielding). The use of foliar fungicides was associated with improved yields and interacted with genotype’s resistance level to stripe rust and with growing seasons’ WS:WD. This work quantified and explained the yield benefits of foliar fungicide, and characterized its dependency on genotype-specific disease resistance and environmental conditions both at the canopy- and commercial field-levels.

With an annual production of ∼60 Mt, the U.S. accounts for about 8% of the global wheat (Triticum aestivum L.) production. Still, quantification of the yield gaps (YG) and major management factors to reduce it are scarce. We used Kansas, the largest wheat producing state in the U.S. located in the central Great Plains, for an initial assessment of on-farm yield and YG. We collected field-level management (37 variables), weather (8 variables), soil (two variables) and yield data from 656 commercial wheat fields over three harvest years (2016–2018) to (i) quantify management adoption levels, Ya, and YG, and (ii) identify interactions among management practices and weather variables using a data-rich approach. We also used our data as a case-study to detect whether differences in crop management among regions justified data clustering by crop zones. Water-limited yield potential (Yw) was simulated for each field-year using actual soil and weather data and the SSM-Wheat model. Fields were grouped in three climate zones based on their long-term climatology and important differences in cropping systems between zones. Grain yield averaged 3.8 Mg ha−1 and ranged from 0.3–7.1 Mg ha−1 across all regions and years. The YG averaged 44 %, with seasons with high Yw resulting in greater YG. Management practices most often associated with grain yield were management of nitrogen (N), phosphorus (P), and sulphur (S) fertilizer, as well as foliar fungicide and its interaction with variety reaction to major diseases, although these depended on in-season weather. Our analyses highlighted many other genotype × management × environment interactions explaining winter wheat Ya, such as regional-specific cultivar maturity and the dependency of sowing date (and its relation to seeding rate) on cropping system.

The impact of agricultural technologies on crop yield is influenced by the environment type (ENVT) as determined by weather and soil. Understanding the correlation between the ENVT of the testing site in relation to the ENVT of the target production region is important for the evaluation and scaling out of agricultural technologies. Here we propose and apply the first explicit method to characterize ENVTs for major rainfed maize, soybean, and wheat producing regions in the United States. We combined a tested spatial framework, Technology Extrapolation Domain (TED), with crop modeling, long-term (30-y) daily weather records, and soil and management databases to calculate the frequency of ENVTs per crop for major harvested areas. Each ENVT was determined based on the intensity of drought and heat stress during key crop stages for yield determination. The ENVT repeatability was calculated based on the frequency of the most dominant ENVT in each TED. We found that inter-annual variation in drought and heat stress was larger than spatial variation. Our ENVTs explained 2x to 7x larger portion of the variance in actual yield compared to the existing TED framework that is based on long-term annual climate means and soil water storage. For maize and soybean, ca. 30% of their harvested area was located in TEDs with highly repeatable ENVTs (>66% of years). In contrast, only 15% of the wheat harvested area was located in TEDs with high ENVT repeatability. In comparison to the TED framework, the ENVTs defined here can help better capture G×E×M interactions and determine the environmental correlation between testing sites and target production environments.

Although the U.S. southern Great Plains accounts for approximately 30% of total U.S. wheat ( Triticum aestivum L.) production, yields in the region have rarely surpassed 3.0 Mg ha −1 and quantification of the wheat yield gap (Y G ) and meteorological factors associated with potential wheat productivity are scarce. Our objectives were to identify spatial gradients in key weather variables and to assess the meteorological drivers of wheat productivity and resource-use efficiency, and to quantify the wheat Y G across Texas, Oklahoma, Colorado, and Kansas. Water-limited wheat grain yield (Y w ) was simulated for 30 consecutive years at 68 locations across the southern Great Plains using Simple Simulation Modeling-Wheat (SSM-Wheat), and actual soil and weather data, sowing date, and population density. Regional gradients in meteorological variables were determined for (i) the entire crop cycle, (ii) pre- and post-anthesis, or (iii) jointing-anthesis interval, and Y w were related back to these variables using linear and stepwise multiple-regression. Boundary function analysis determined water productivity (WP) and transpiration-use efficiency (TE). Strong latitudinal gradients occurred for temperatures and longitudinal gradients for precipitation (P), evapotranspirative demand (ET o ), and solar radiation (Rs). Wheat Y w averaged 5.2 Mg ha −1 and followed the longitudinal P gradient increasing from west (3.6 Mg ha −1 ) to east (6.9 Mg ha −1 ). Interannual Y w variability was large with coefficient of variation (CV) increasing from 13 to 51% east to west. Meteorological variables accounting for major portions of the Y w variability were water supply (P + PAW s ) in the west [82% of regression sums of squares (SS)] and cumulative solar radiation (R s ) during the anthesis − physiological maturity in the east (73% of SS). Temperatures during the anthesis-physiological maturity phase negatively affected grain yields across all locations and years (7% of SS). Wheat WP (17.2 kg ha −1 mm −1 ) and TE (20.8 kg ha −1 mm −1 ) benchmarks derived in this study align well with values reported for wheat grown in other regions of the world.

Increasing irrigated wheat yields is important to the overall profitability of limited-irrigation cropping systems in western Kansas. A simulation study was conducted to (1) validate APSIM‘s (Agricultural Production Systems sIMulator) ability to simulate wheat growth and yield in Kansas, and (2) apply the model to assess the response of wheat yield, biomass, and water productivity to irrigation allocation based on growth stage. The methodology involved combining short-term experimental data, long-term historical weather data (1950-2013), and mechanistic crop growth simulation to determine optimum irrigation management strategies. The model adequately simulated measured soil water in the profile. The goodness-of-fit test between the observed and simulated values for phenology, yield, biomass, and ET of the experimental cultivar in 2008-2009 in our study site agreed well with the ‘Batten winter‘ wheat cultivar in APSIM. Results indicated that, on average, an irrigation allocation of 100 mm increased wheat yield by 14% to 46% compared to rainfed (dryland) production. Application of an additional 100 mm of irrigation did not improve wheat yield substantially (on average -1 ). Higher water productivity for grain yield was obtained when irrigation was applied at booting and heading. Overall, irrigation water use efficiency for grain decreased with an increase in irrigation allocation. The highest irrigation water use efficiency was simulated for wheat grown with a limited irrigation allocation of 100 mm applied at booting and heading. This study demonstrates that limited irrigation targeted at sensitive growth stages could enhance wheat yields and improve water productivity of water-limited cropping systems.

Understanding factors underpinning the variability in nitrogen (N) utilization efficiency (NUtE) [i.e. grain yield per unit of N uptake at maturity (NupMAT)] is critical to direct future improvements in breeding and agronomic management. To our knowledge, no study has summarized changes in wheat NUtE across a wide range of experimental conditions. We performed a synthesis-analysis using published data to provide a global perspective of NUtE trends in wheat by (i) benchmarking against yield limited by NupMAT, and (ii) assessing factors contributing to the variation in NUtE. The final database encompassed 55 studies (n = 529). A nonlinear model explained yield as a function of NupMAT. The gap between actual yield and NupMAT-limited yield was negligible at the lowest range of NupMAT and increased to ∼2000 kg ha−1 as NupMAT levels increased. Hence, opportunities to enhance yield through improving NUtE would be more likely at greater-than-average yield and NupMAT levels. The negative correlation between grain protein concentration and the residuals between NUtE and NupMAT indicated a challenge to increase yield without penalizing grain protein. Further, there are greater opportunities to increase NUtE in fall- than winter-sown wheat. Identifying the determinants of NUtE will enable to narrow the gap between actual and NupMAT-limited yields.

Maximum reported grain yields for hard red winter wheat ( Triticum aestivum L.) in the southern Great Plains range from 6 to 8 Mg ha -1 and are significantly lower than yields achieved in other regions of the world. The lack of empirical data for wheat under nonlimiting conditions in this region, however, suggests that maximum reported grain yields for the region might not represent maximum attainable yields. Our objective was to perform the agronomic characterization of wheat grown under nonlimiting conditions across the southern Great Plains. Four dryland and two irrigated fields were sown to 'Iba' winter wheat in the 2012-2013 growing season and repeated during 2013-2014 in central Oklahoma. Fields were intensively managed for fertility for maximum yield and freedom from weeds, insects, and disease. Aboveground dry matter at maturity ranged from 9.95 to 20.5 Mg ha -1 , but harvest index (HI) did not surpass 0.41 and grain yields ranged from 3.06 to 7.68 Mg ha -1 . The highest yield was achieved under irrigated conditions in 2013-2014, but one dryland site produced 7.11 Mg ha -1 grain in 2012-2013. Maximum radiation-use efficiency (RUE) ranged from 0.8 to 1.9 g MJ -1 and water-use efficiency (WUE) from 7.8 to 12.6 kg ha -1 mm -1 . The wheat characteristics measured in this study were near or above maximum values reported in the literature for the region, and our data provide empirical evidence to support maximum attainable wheat yields of 7.68 Mg ha -1 when wheat is grown under nonlimiting conditions in the southern Great Plains.

Since 1980, average wheat (Triticum aestivum L.) yields have remained nearly stagnant in the southern Great Plains (SGP) and stagnant in the state of Oklahoma. Yield stagnation can sometimes be attributed to a relatively small gap between current and potential yields, but the magnitude of the yield gap for this region has not been well quantified. The objective of this study was to determine the wheat yield and production gaps in Oklahoma at state and county levels. This involved estimation of attainable yield (Y a ) using a frontier yield function and water-limited potential yield (Y p ) using estimated transpiration and transpiration efficiency. Yield gap and production gap relative to Y a and Y p were calculated using grain yields and harvested area for 19 counties. Current average yield (Y c ) was 2.06 Mg ha –1 at the state level, well below the maximum recorded yield at the plot level of 6.59 Mg ha –1 . The Y p of current wheat varieties is far above Y c in Oklahoma, and Y c represents 74% of Y a but only 30% of Y p at state level. For growing season rainfall (GSRF) amount

D eforestation and subsequent cultivation have been reported to result in loss of soil organic carbon (SOC) and soil productivity throughout the world (Matson et al. 1997). Decreased SOC due to cultivation of deforested land is well documented (Follett 2001; Janzen et al. 1998; Riezebos and Loerts 1998) and often happens two to five times faster in tropical than temperate environments (Matson et al. 1997; Six et al. 2002). Soil organic carbon decreases as a function of biomass removal, lower organic input, and greater biomass decomposition rates in the newly disturbed soil as compared to soil under native vegetation (Riezebos and Loerts 1998). The removal of native biomass also exposes the soil, rendering the surface prone to erosion (Prandini et al. 1977). Research has shown that the high environmental costs brought by changes in land use can be lessened if conservation tillage practices are adopted (Rhoton 2000; Rimal and Lal 2009). The data collected in southern Brazil and presented in this report indicate that almost three decades of no-tillage farming practices have the ability to restore SOC to near native levels. We are reporting long-term shifts in SOC, as well as observed soil erosion, in a 60 ha (148 ac) Brazilian…

Soil acidity has become a major yield-limiting factor in cropping systems of the Southern Great Plains, in which winter wheat (Triticum aestivumL.) is the predominant crop. Sunflower (Helianthus annuusL.) is a strong rotational crop with winter wheat due to its draught and heat tolerance. However, the effects of low soil pH on sunflower productivity have not been explored. The objective of this study was to determine the critical soil pH and aluminum concentration (AlKCl) for sunflower. Sunflower was grown in a randomized complete block design with three replications of a pH gradient ranging from 4.0 to 7.0 at three locations with varying soil types. Soil pH was altered using aluminum sulfate (Al2(SO4)3) and hydrated lime (Ca(OH)2). Plant height, vigor, and survivability were all negatively affected by soil acidity. Sunflower yield was reduced by 10% at or below soil pH 4.7 to 5.3 dependent upon location and soil type. Levels ofAlKClabove 6.35 mg kg−1reduced seed yield by 10% or greater. We concluded that sunflower may serve as a better rotational crop with winter wheat under acidic conditions when compared to other adaptable crops.