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With improved crop yields and reduced atmospheric S deposition, Mid‐South U.S. soils may require S fertilization in deficient soils. The objectives of this study were to identify optimal at‐planting S rate for corn (Zea mays L.) and soybean [Glycine max (L.) Merr.] yield, and evaluate the impact of S rate on crop growth, leaf nutrient level, and seed S. Small plot replicated field studies were conducted in 2015 and 2016 at a S‐deficient site in Milan, TN. Ammonium sulfate [(NH4)2SO4] was broadcast applied at planting at 0, 10, 20, and 30 lb S acre–1. Soybean leaf S concentration at early bloom was similar to the zero S control, but concentrations of Fe, Mn, and Cu were reduced, and Zn was increased. These effects increased with S rate. Corn leaf tissue S concentration increased with S rate at sixth‐leaf and silking, while Fe, Mn, and Cu decreased as S rate increased, similar to the soybean experiment. Soybean seed S level increased with rate of S, while corn seed S increased with lowest S rate but did not respond to S rate. Seed N and seed weight were not affected by S rate for either crop. The small increase in soybean yield was not significant. Corn yield increased with applied S in both years. Overall, application of S fertilizer at ≥10 lb S acre–1 improved corn but not soybean yield in a low soil organic matter (SOM), S deficient medium‐textured soil. Core Ideas: Sulfur fertilizer increased grain yield in corn but not soybean.Corn leaf S and soybean seed S increased with S rate.Sulfur did not affect seed weight or seed N in corn or soybean. [ABSTRACT FROM AUTHOR]

Cotton producers in the U.S. Mid-South often plant in cool, wet conditions to lengthen the growing season and maximize yield potential. Although multiple studies have been conducted to determine optimum planting windows and seeding rates, few studies have evaluated the interaction of these parameters. To make a replant decision, the yield potential of the current stand versus the yield potential of the replant must be estimated. The objective of this study was to determine the impact of plant population and planting date on lint yield and fiber quality. Field experiments were conducted in 10 site-years from 2016 to 2018 in Tennessee, Mississippi, and Missouri. Treatments included five seeding rates (10.5, 6.75, 3, 1.5, and 0.75 seeds m-1) and multiple planting dates (typically early May, mid-May, and early June). Although yields were lowest at later planting dates and low populations, results suggested a uniform population of 74,000 plants ha-1 will not warrant a replant at any date, and uniform populations as low as 49,000 plants ha-1 planted after 5 May also will not warrant replanting. Fiber quality was impacted by environment and planting date, with micronaire decreasing and length, strength, and uniformity increasing as planting date was delayed. These data will assist with replant decisions by providing estimates of the current stand relative to the yield potential of a successful (or unsuccessful) replant. Furthermore, results suggest producers could reduce seeding rates at later planting dates without reducing yield potential. [ABSTRACT FROM AUTHOR]

Core IdeasCereal rye and wheat cover crops produced similar levels of biomass as a multi‐species mix.A preemergence herbicide was required to achieve acceptable, consistent levels of weed control.Cover crop treatment did not significantly impact soybean yields.A wheat–soybean double crop system reduced soybean yields in four of five site‐years. The integration of cover crops into soybean (Glycine max) production has many potential benefits, but little information has been collected on the impact of multiple‐species cover crops on the subsequent soybean crop relative to the common wheat (Triticum aestivum)–soybean double crop. Experiments were established at the West Tennessee Research and Education Center in Jackson, TN in the fall of 2014, 2015, and 2016 and the Research and Education Center in Milan, TN in the fall of 2014 and 2015. Winter treatments included a winter–fallow, cover crops including cereal rye (Secale cereal), wheat, crimson clover (Trifolium incarnatum), and a five‐way mixture [cereal rye, oats (Avena sativa), oilseed radish (Raphanus sativus), crimson clover, and hairy vetch (Vicia villosa), referred to as mix], and wheat for grain. Treatments were split to evaluate weed suppression relative to the preemergence herbicide, S‐metolachlor + metribuzin. Largest levels of biomass (commonly 4000+ lb/acre) were associated with the wheat for grain, cereal rye, and mix treatments. Weed control was greatest in cereal rye, wheat for cover and mix treatments, but no treatment provided consistent, acceptable weed control without the use of the preemergence herbicide. Soybean yields were not impacted by cover. The delayed planting of soybeans after wheat for grain negatively impacted yields in four of five site‐years by an average of 20 bushels/acre. Results suggest impacts of single‐ or multiple‐species cover crops on soybean yields may be negligible. Market prices, incentives, and long‐term benefits may be more important than short‐term costs/benefits when selecting a production system. [ABSTRACT FROM AUTHOR]

The objectives of this study were to determine the effects of risk exposure on optimal N fertilizer rates for continuous corn (Zea mays L.), corn grown after cotton (Gossypium ssp.), and corn grown after soybean \Glycine max (L.) Merr.] and identify the optimal corn rotation for risk-averse corn producers. Data were collected from a 7-yr, corn-rotation, N-fertilizer experiment in Tennessee. Partial budgets were used to calculate net returns to N for corn grown after corn, corn grown after cotton, and corn grown after soybean. The flexible moment method was used for risk analysis, a unique application of this method that provides producers with information concerning traditional risk effects on decisions about crop rotations and N rates augmented by the effects of downside risk. Results from this study show rotating corn with cotton and soybean increased yields and net returns relative to continuous corn, but profit-maximizing N rates for corn were not greatly impacted by the crop planted in the previous year. Optimal N rates decreased for producers with more risk aversion, indicating that N fertilizer is a risk-increasing input. Downside risk was found for continuous corn and corn grown after soybean, increasing the risk premiums for these rotations above the risk premium for corn grown after cotton. Slightly to moderately risk-averse corn producers would prefer growing corn after soybean, but highly risk-averse producers would prefer rotating corn with cotton. Results provide corn producers with enhanced information about the effects of risk exposure on choices among corn rotations and N fertilizer rates. [ABSTRACT FROM AUTHOR]

The strength of the relationships of corn (Zea mays L.) yield, plant biomass, and leaf N concentration with early- to mid-growing season combined normalized difference vegetation index (NDVI) and plant height measurements has not been adequately documented. The objective of this study was to compare the strength among the relationships of corn yield, plant biomass, and leaf N with combined and respective NDVI and plant height measurements taken during the early to mid-season under major cropping systems. Two field N rate response studies in non-irrigated corn after soybean [Glycine max (L.) Merr.] (CS), non-irrigated corn after cotton [Gossypium hirsutum (L.)] (CCT), non-irrigated corn after corn (CC), and irrigated corn after soybean (ICS) were conducted at Jackson and Milan, TN, from 2008 through 2010. Regressions of corn yield, plant biomass, and leaf N concentration with NDVI x plant height and NDVI + plant height were slightly to markedly stronger in terms of R² values than those of corn yield, plant biomass, and leaf N with NDVI alone during 6-leaf growth stage (V6) to 12-leaf growth stage (V12) regardless of cropping system. No strength difference was observed between the regressions of corn yield, plant biomass, and leaf N with NDVI x plant height or NDVI + plant height and with plant height alone. Our results suggest that the benefits are variable in using combined NDVI and plant height measurements to assess corn growth and N nutrition and/or predict corn yield relative to the utilization of NDVI measurements alone during the early- to mid-season. [ABSTRACT FROM AUTHOR]

BACKGROUND: The physiological basis for using non-destructive high-resolution measurements of plant height through plant height sensing to guide variable-rate nitrogen (N) applications on corn ( Zea mays L.) during early (six-leaf growth stage, V6) to mid (V12) season is largely unknown. This study was conducted to assess the relationships of plant biomass and leaf N with plant height in early- to mid-season corn under six different N rate treatments. RESULTS: Corn plant biomass was significantly and positively related to plant height under an exponential model when both were measured at V6. This relationship explained 62-78% of the variations in corn biomass production. Leaf N concentration was, in general, significantly and positively related to plant height when both were measured at V6, V8, V10 and V12. This relationship became stronger as the growing season progressed from V6 to V12. The relationship of leaf N with plant height in early- to mid-season corn was affected by initial soil N fertility and abnormal weather conditions. CONCLUSION: The relationship of leaf N concentration with plant height may provide a physiological basis for using plant height sensing to guide variable-rate N applications on corn. Copyright © 2012 Society of Chemical Industry [ABSTRACT FROM AUTHOR]

The relationship between corn (Zea mays L.) yield and plant height has been poorly documented in major corn production systems. This study was conducted to assess the relationship of corn yield with plant height under four major corn production systems at Milan, TN from 2008 through 2010. Six N treatments at rates of 0, 62, 123, 185, 247, and 308 kg N ha-1 with four replications were evaluated in a randomized complete block design in the following corn production systems: nonirrigated corn after corn, nonirrigated corn after soybean [Glycine max (L.) Merr.], nonirrigated corn after cotton [Gossypium hirsutum (L.)], and irrigated corn after soybean. The regression of corn yield with plant height was significant and positive at 6-leaf growth stage (V6), 10-leaf growth stage (Yb), and 12-leaf growth stage (V12), and mostly became stronger as plant growth progressed from V6 to Y10 and to V12 under an exponential model in the four corn production systems for all 3 yr. In general, corn yield was strongly related with plant height measurements made at Y10 and V12. Factors affecting the responses of plant height measured at V6, Y10, and V12 or/and yield to the N treatments may have contributed to the variations of determination coeffient (R2) values across years. In conclusion, corn yield may be predicted with plant height measurements collected during Y10 to V12. This prediction provides a physiological basis for the utilization of high resolution plant height measurements to guide variable-rate N applications within the field on corn at around V10 and to more accurately estimate yield for earlier grain marketing purposes. [ABSTRACT FROM AUTHOR]

Highlights • We developed an approach to evaluate influence of management on yield using both producer and experimental data. • We assessed influence of row spacing on US soybean yield. • Experimental data showed a consistent yield advantage of narrow versus wide row spacing. • However, data from producer fields indicate no yield difference between narrow and wide rows. • This complementary approach can help evaluate yield increase derived from a management practice. Abstract Narrowing row width in soybean fields leads to earlier canopy closure, which may increase capture of incoming solar radiation during critical crop stages for yield determination. Theoretically, this should enhance seed yield. However, in prior studies, the impact of narrowing row spacing on soybean yield has been inconsistent. To explore on a broader scale the potential factors underlying this inconsistency, we evaluated the yield difference between narrow (NR; ≈38 cm) and wide (WR; ≈76 cm) row spacing using two sources of yield and management information: (i) data collected from 4879 soybean production fields via a multi-year, multi-state survey of soybean producers in the North Central US region; and (ii) data extracted from 129 site-year experiments that quantified NR-WR yield difference. The producer fields were allocated to their respective climate-soil domains to enable analysis of the NR-WR yield difference within each domain. The experimental trial data originated from three US geographic regions: south, central, and north. Key crop developmental stages in each trial were estimated using a soybean crop simulation model to discern if changes in crop phenology or any weather variable occurring before versus after a specific crop stage modulated the magnitude of the NR-WR yield difference. Analysis of experimental trial data indicated that, while NR yields were overall higher than WR yields, the NR-WR yield difference varied by region: 540 (south), 104 (central), and 240 kg ha−1 (north); the respective NR yields were greater than WR yields in 92%, 68%, and 84% of the cases. In the north and south regions, the NR-WR yield difference increased when the crop cycle length decreased as a consequence of later sowing date, earlier cultivar maturity group, and/or higher temperature. The relatively smaller (and occasionally negative) NR-WR yield difference detected in the central region was likely the result of environmental conditions that favored canopy closure irrespective of row spacing. In contrast to the analysis of the experimental database, no consistent NR-WR yield differences were detected in the producer field database. We hypothesize that the apparent absence of a significant NR-WR effect in the producer dataset is likely associated with the background management used with narrow spacing, together with yield losses due to wheel damage and greater disease pressure. This complementary approach using both producer and experimental data can help evaluate if practices documented in experimental trials to enhance yield realize equivalent yield increases in producer fields and, if not, explore underlying causes for the discrepancy. [ABSTRACT FROM AUTHOR]