Corn (Zea mays L.) seeding rate optimization in Iowa, USA

Collecting soil, topography, and yield information has become more feasible and reliable with advancements in precision technologies. Combined with the accessibility of precision technologies and services to farmers, there has been increased interest and ability to make site-specific crop management decisions. The objective of this research was to develop procedures to optimize corn seeding rates and maximize yield using soil and topographic parameters. Experimental treatments included five seeding rates (61 750; 74 100; 86 450; 98 800; and 111 150 seeds ha−1) in a randomized complete block design in three central Iowa fields from 2012 to 2014 (nine site-years). Soil samples were analyzed for available phosphorus (Olsen method), exchangeable potassium (ammonium-acetate method), pH, soil organic matter (SOM), cation exchange capacity (CEC), and texture. Topographic data (in-field elevation, slope, aspect, and curvature) were determined from publically available light detection and ranging data. In four site-years, no interaction occurred between seeding rate and the descriptive variables. Three of the site-years resulted in a negative linear seeding rate response which made it impossible to determine an optimum seeding rate above the lowest seeding rate treatment. The seeding rate optimization process in five site-years resulted in seeding rate by variable interactions; four site-years had a single seeding rate by variable interaction (pH, in-field elevation, or curvature) and one site-year had three seeding rate by variable interactions (pH, CEC, and SOM). Meaningful seeding rate optimizations occurred in only three of nine site-years. There was not a consistent descriptive variable interaction with seeding rate as a result of weather variability

Corn (\u3ci\u3eZea mays L.\u3c/i\u3e) seeding rate optimization in Iowa, USA

Collecting soil, topography, and yield information has become more feasible and reliable with advancements in precision technologies. Combined with the accessibility of precision technologies and services to farmers, there has been increased interest and ability to make site-specific crop management decisions. The objective of this research was to develop procedures to optimize corn seeding rates and maximize yield using soil and topographic parameters. Experimental treatments included five seeding rates (61 750; 74 100; 86 450; 98 800; and 111 150 seeds ha-1) in a randomized complete block design in three central Iowa fields from 2012 to 2014 (nine site-years). Soil samples were analyzed for available phosphorus (Olsen method), exchangeable potassium (ammonium-acetate method), pH, soil organic matter (SOM), cation exchange capacity (CEC), and texture. Topographic data (in-field elevation, slope, aspect, and curvature) were determined from publically available light detection and ranging data. In four site-years, no interaction occurred between seeding rate and the descriptive variables. Three of the site-years resulted in a negative linear seeding rate response which made it impossible to determine an optimum seeding rate above the lowest seeding rate treatment. The seeding rate optimization process in five site-years resulted in seeding rate by variable interactions; four site-years had a single seeding rate by variable interaction (pH, in-field elevation, or curvature) and one site-year had three seeding rate by variable interactions (pH, CEC, and SOM). Meaningful seeding rate optimizations occurred in only three of nine site-years. There was not a consistent descriptive variable interaction with seeding rate as a result of weather variability. Referenc

Corn (\u3ci\u3eZea mays L.\u3c/i\u3e) seeding rate optimization in Iowa, USA

Collecting soil, topography, and yield information has become more feasible and reliable with advancements in precision technologies. Combined with the accessibility of precision technologies and services to farmers, there has been increased interest and ability to make site-specific crop management decisions. The objective of this research was to develop procedures to optimize corn seeding rates and maximize yield using soil and topographic parameters. Experimental treatments included five seeding rates (61 750; 74 100; 86 450; 98 800; and 111 150 seeds ha-1) in a randomized complete block design in three central Iowa fields from 2012 to 2014 (nine site-years). Soil samples were analyzed for available phosphorus (Olsen method), exchangeable potassium (ammonium-acetate method), pH, soil organic matter (SOM), cation exchange capacity (CEC), and texture. Topographic data (in-field elevation, slope, aspect, and curvature) were determined from publically available light detection and ranging data. In four site-years, no interaction occurred between seeding rate and the descriptive variables. Three of the site-years resulted in a negative linear seeding rate response which made it impossible to determine an optimum seeding rate above the lowest seeding rate treatment. The seeding rate optimization process in five site-years resulted in seeding rate by variable interactions; four site-years had a single seeding rate by variable interaction (pH, in-field elevation, or curvature) and one site-year had three seeding rate by variable interactions (pH, CEC, and SOM). Meaningful seeding rate optimizations occurred in only three of nine site-years. There was not a consistent descriptive variable interaction with seeding rate as a result of weather variability. Referenc

Weak Localization Coexisting with a Magnetic Field in a Normal-Metal--Superconductor Microbridge

A random-matrix theory is presented which shows that breaking time-reversal symmetry by itself does {\em not} suppress the weak-localization correction to the conductance of a disordered metal wire attached to a superconductor. Suppression of weak localization requires applying a magnetic field as well as raising the voltage, to break both time-reversal symmetry and electron-hole degeneracy. A magnetic-field dependent contact resistance obscured this anomaly in previous numerical simulations.Comment: 8 pages, REVTeX-3.0, 1 figur

Management and Tillage Infl uence Barley Forage Productivity and Water Use in Dryland Cropping Systems

Annual cereal forages are resilient in water use (WU), water use efficiency (WUE), and weed control compared with grain crops in dryland systems. The combined influence of tillage and management systems on annual cereal forage productivity and WU is not well documented. We conducted a field study for the effects of tillage (no-till and tilled) and management (ecological and conventional) systems on WU and performance of forage barley (Hordeum vulgare L.) and weed biomass in two crop rotations (wheat [Triticum aestivum L.]–forage barley–pea [Pisum sativum L.] and wheat–forage barley–corn [Zea mays L.] –pea) from 2004 to 2010 in eastern Montana. Conventional management included recommended seeding rates, broadcast N fertilization, and short stubble height of wheat. Ecological management included 33% greater seeding rates, banded N fertilization at planting, and taller wheat stubble. Forage barley in ecological management had 28 more plants m–2, 2 cm greater height, 65 more tillers m–2, 606 kg ha–1 greater crop biomass, 3.5 kg ha–1 mm–1greater WUE, and 47% reduction in weed biomass at harvest than in conventional management. Pre-plant and post-harvest soil water contents were similar among tillage and management systems, but barley WU was 13 mm greater in 4-yr than 3-yr rotation. Tillage had little effect on barley performance and WU. Dryland forage barley with higher seeding rate and banded N fertilization in more diversified rotation produced more yield and used water more efficiently than that with conventional seeding rate, broadcast N fertilization, and less diversified rotation in the semiarid northern Great Plains

Limiting nutrients for bean production on contrasting soil types of Lake Victoria Crescent of Uganda

Common bean (Phaseolus vulgaris L.) is one of the most important grain legumes in East Africa, but its yield has remained below the genetic potential. Declining soil fertility is among the primary constraints to bean production in most East African bean producing regions. Often existing recommendations are generic and inept to guide farm level decision making on nutrient replenishment. A greenhouse nutrient omission study was conducted to determine the limiting nutrients in three soils of Masaka District, commonly cropped to beans: “Liddugavu” a Phaeozem, “Limyufumyufu” a Cambisol and “Luyinjayinga” an Umbrisol soil. Nine treatments; (i) complete nutrient treatment, (ii) N omitted, (iii) P omitted, (iv) K omitted, (v) Mg omitted, (vi) S omitted, (vii) Ca omitted, (viii) Micronutrients omitted and (ix) control without nutrients. Each treatment was randomly assigned to the three soils and replicated three times using a completely randomised design. Nitrogen, phosphorus and potassium were limiting nutrients for bean production in Umbrisol (Luyinjayinja) while in Cambisol (‘Limyufumyufu), common bean production was most limited by soil acidity. The performance varied with soil types, with beans grown on the Phaeozem registering greater leaf number and growth, confirming both scientist’s and local farmer’s knowledge that this soil has greater potential than the other two soils

Time Interval Between Cover Crop Termination and Planting Influences Corn Seedling Disease, Plant Growth, and Yield

Experiments were established in a controlled-growth chamber and in the field to evaluate the effect of the length of time intervals between winter rye cover crop termination and corn planting on corn seedling disease, corn growth, and grain yield in 2014 and 2015. Rye termination dates ranged from 25 days before planting (DBP) to 2 days after planting (DAP) corn in the field and from 21 DBP to 1 DAP in controlled studies. Results were similar in both environments. In general, shorter intervals increased seedling disease and reduced corn emergence, shoot growth, and grain yield of corn following winter rye compared with corn planted 10 or more days after rye termination or without rye. Incidence of Pythium spp. increased with shorter intervals (less than 8 DBP); incidence of Fusarium spp. was not consistent between runs and experiments. In 2014, in the 1-DAP treatment, number of ears and grain yield were reduced (P = 0.05 and 0.02, respectively). In 2015, all termination intervals reduced plant population, number of ears, and yield (P = 0.01), with the 2-DBP treatment causing the biggest decrease. A 10- to 14-day interval between rye termination and corn planting should be followed to improve corn yield following a rye cover crop