Row Crop Production Research Articles

Insect Pollinators in Iowa Cornfields: Community Identification and Trapping Method Analysis

Availability of mass flowering plants in landscapes dominated by agriculture can have a strong positive impact on the density of generalist, native pollinators. Row-crop production in Iowa accounts for 75% of the arable acres, with corn, Zea mays, representing the majority of hectares planted. To date, there has been no description of the insect pollinator community found within Iowa cornfields. We report a field study to determine the optimal sampling methodology to characterize the community of insect pollinators within cornfields. During 2012 and 2013, 3,616 insect pollinators representing 51 species were captured using bee bowls, and 945 individuals representing 10 species were captured using sticky cards. We examined the effects of trap type, height, and bowl color on the described community. Bee bowls captured a more abundant and species rich community than sticky cards with all species captured on sticky cards also present in bee bowls. Traps deployed at the height of the tassels describe a more abundant and species rich community of pollinators than traps at ear height (2x as many individuals) or ground height (4x as many individuals). Blue bowls captured more bees than white (2.75x as many individuals) or yellow bowls (3.5x as many individuals); and yellow bowls captured more flies than white (2x as many individuals) or blue (2.3x as many individuals). To provide the most complete description of the community of insect pollinators using cornfields as a resource, we suggest sampling-using bee bowls at the height of the tassels using all three bee bowl colors.

Prairies Thrive Where Row Crops Drown: A Comparison of Yields in Upland and Lowland Topographies in the Upper Midwest US

Cellulosic biofuel production is expected to increase in the US, and the targeted establishment of biofuel agriculture in marginal lands would reduce competition between biofuels and food crops. While poorly drained, seasonally saturated lowland landscape positions are marginal for production of row crops and switchgrass (Panicum virgatum L.), it is unclear whether species-diverse tallgrass prairie yield would suffer similarly in saturated lowlands. Prairie yields typically increase as graminoids become more dominant, but it is uncertain whether this trend is due to greater aboveground net primary productivity (ANPP) or higher harvest efficiency in graminoids compared to forbs. Belowground biomass, a factor that is important to ecosystem service provisioning, is reduced when switchgrass is grown in saturated lowlands, but it is not known whether the same is true in species-diverse prairie. Our objectives were to assess the effect of topography on yields and live belowground biomass in row crops and prairie, and to determine the mechanisms by which relative graminoid abundance influences tallgrass prairie yield. We measured yield, harvest efficiency, and live belowground biomass in upland and lowland landscape positions within maize silage (Zea mays L.), winter wheat (Triticum aestivum L.), and restored tallgrass prairie. Maize and winter wheat yields were reduced by more than 60% in poorly drained lowlands relative to well-drained uplands, but diverse prairie yields were equivalent in both topographic settings. Prairie yields increased by approximately 45% as the relative abundance of graminoids increased from 5% to 95%. However, this trend was due to higher harvest efficiency of graminoids rather than greater ANPP compared to forbs. In both row crops and prairie, live belowground biomass was similar between upland and lowland locations, indicating consistent biomass nutrient sequestration potential and soil organic matter inputs between topographic positions. While poorly drained, lowland landscape positions are marginal lands for row crops, they appear prime for the cultivation of species-diverse tallgrass prairie for cellulosic biofuel.

Multiple-Herbicide Resistance Is Widespread in Roadside Palmer Amaranth Populations.

Herbicide-resistant Palmer amaranth is a widespread issue in row-crop production in the Midsouthern US. Palmer amaranth is commonly found on roadside habitats in this region, but little is known on the degree of herbicide resistance in these populations. Herbicide resistance in roadside Palmer amaranth populations can represent the spread of an adaptive trait across a selective landscape. A large-scale survey was carried out in the Mississippi Delta region of eastern Arkansas to document the level of resistance in roadside Palmer amaranth populations to pyrithiobac and glyphosate, two important herbicides with broad history of use in the region. A total of 215 Palmer amaranth populations collected across 500 random survey sites were used in the evaluations. About 89 and 73% of the surveyed populations showed >90% survival to pyrithiobac and glyphosate, respectively. Further, only 3% of the populations were completely susceptible to glyphosate, while none of the populations was completely controlled by pyrithiobac. Among the 215 populations evaluated, 209 populations showed multiple resistance to both pyrithiobac and glyphosate at varying degrees. Dose-response assays confirmed the presence of high levels of herbicide resistance in the five selected populations (≥ 25-fold compared to a susceptible standard). Results demonstrate the prevalence of multiple-herbicide resistance in roadside Palmer amaranth populations in this region. Growers should be vigilant of Palmer amaranth infestation in roadsides adjacent to their fields and implement appropriate control measures to prevent likely spread of herbicide resistance into their fields.

Seed Production and Control of Sicklepod (Senna obtusifolia) and Pitted Morningglory (Ipomoea lacunosa) with 2,4-D, Dicamba, and Glyphosate Combinations

Sicklepod and pitted morningglory are two of the most important weed species in row-crop production in the southeastern United States. The upcoming introduction of soybean and cotton varieties resistant to 2,4-D and dicamba will increase the reliance on these auxinic herbicides. However, it is not clear how these herbicides will affect sicklepod and pitted morningglory control. Field experiments were conducted in 2013 and 2014 in Jay, FL to determine whether 2,4-D (560 and 1,120 g ae ha−1), dicamba (420 and 840 g ae ha−1), and glyphosate (1,060 g ae ha−1) alone or in combination applied when weed shoots were 11 (early POST [EPOST]) and 22 (late POST [LPOST]) cm long effectively control and prevent seed production of sicklepod and pitted morningglory. LPOST provided more effective control of sicklepod than EPOST. This was attributed to emergence of sicklepod seedlings after the EPOST application. When glyphosate was tank mixed with 2,4-D or dicamba, sicklepod control was higher (78 to 89% and 87 to 98% in 2013 and 2014, respectively) than for single-herbicide treatments (45 to 77% and 38 to 80% in 2013 and 2014, respectively) 6 wk after treatment (WAT). Pitted morningglory control was not affected by application timing, and 2,4-D provided 91 to 100% 6 WAT, which was equivalent to treatments with tank mixtures containing glyphosate. Dicamba applied at 420 g ha−1had the lowest pitted morningglory control (44 to 70% and 82 to 86% in 2013 and 2014, respectively). Sicklepod and pitted morningglory plants that survived and recovered from herbicide treatments produced the same number of viable seeds as nontreated plants in most treatments. The results of the present study indicated that the use of 2,4-D and dicamba alone will not provide adequate extended control of sicklepod, and the use of tank mixtures that combine auxinic herbicides with glyphosate or other POST herbicides will be necessary to manage sicklepod adequately in 2,4-D- or dicamba-resistant soybean and cotton. Because sicklepod plants that survived a single herbicide application are capable of producing abundant viable seeds, integrated approaches that include PRE herbicides and sequential POST control options may be necessary to ensure weed seed bank reductions.

Landscape patterns of bioenergy in a changing climate: implications for crop allocation and land-use competition.

Rural landscapes face changing climate, shifting development pressure, and loss of agricultural land. Perennial bioenergy crops grown on existing agricultural land may provide an opportunity to conserve rural landscapes while addressing increased demand for biofuels. However, increased bioenergy production and changing land use raise concerns for tradeoffs within the food-energy-environment trilemma. Heterogeneity of climate, soils, and land use complicate assessment of bioenergy potential in complex landscapes, creating challenges to evaluating future tradeoffs. The hypothesis addressed herein is that perennial bioenergy production can provide an opportunity to avoid agricultural land conversion to development. Using a process-based crop model, we assessed potential bioenergy crop growth through 2100 in a southern Appalachian Mountain region and asked: (1) how mean annual yield differed among three crops (switchgrass Panicum virgatum, giant miscanthus Miscanthus x giganteus, and hybrid poplar Populus x sp.) under current climate and climate change scenarios resulting from moderate and very high greenhouse gas emissions; (2) how maximum landscape yield, spatial allocation of crops, and bioenergy hotspots (areas with highest potential yield) varied among climate scenarios; and (3) how bioenergy hotspots overlapped with current crop production or lands with high development pressure. Under both climate change scenarios, mean annual yield of perennial grasses decreased (-4% to -39%), but yield of hybrid poplar increased (+8% to +20%) which suggests that a switch to woody crops would maximize bioenergy crop production. In total, maximum landscape yield increased by up to 90 000 Mg/yr (6%) in the 21st century due to increased poplar production. Bioenergy hotspots (> 18 Mg x ha(-1) x yr(-1)) consistently overlapped with high suburban/exurban development likelihood and existing row crop production. If bioenergy production is constrained to marginal (non-crop) lands, landscape yield decreased by 27%. The removal of lands with high development probability from crop production resulted in losses of up to 670 000 Mg/yr (40%). This study demonstrated that tradeoffs among bioenergy production, crop production, and exurban expansion in a mountainous changing rural landscape vary spatially with climate change over time. If markets develop, bioenergy crops could potentially counter losses of agricultural land to development.

Does the U.S. Cropland Data Layer Provide an Accurate Benchmark for Land‐Use Change Estimates?

Even though the cropland data layer (CDL) has been used in policy discussions it has not been independently validated using publically available information. The projects objective was to conduct an independent validation of the CDL. South Dakota was selected as a model system because it is located in a climate transition zone, with row crop production being the dominant practice in eastern South Dakota and the grazing of grassland being the dominant practice in western South Dakota. High resolution imagery was used to determine land‐uses (cropland, grassland, non‐agricultural, habitat, and water) at 14,400 points in 2006 and 2012. Based on comparisons between the CDL and ground collected data, a confusion table was constructed and the CDL user (% false positive = 100‐user accuracy) and producer (% false negatives = 100 – producer accuracy) accuracies determined. The % false positives and % false negatives are often referred to as Type I error and Type II error. In 2006, the CDL cropland producer accuracy (% of ground collected sites that were correctly identified) ranged from 89.2% in the east central to 42.6% in the Northwest, whereas the CDL grassland producer accuracy ranged from 95.2% in the Northwest to 38.9% in the Southeast. Similar results were reported for 2012. Grassland CDL producer and user accuracies were highest when grasslands were the dominant practice and cropland producer and user accuracies were highest when croplands were the dominant land‐use. These results suggest that inherent CDL errors introduce uncertainty into land‐use change calculations.

Biomass and integrated forage/biomass yields of switchgrass as affected by intercropped cool- and warm-season legumes

Switchgrass (Panicum virgatum L.) has potential as a biofuel feedstock for ethanol production on marginal soils not suitable for row crop production. Further, it is hypothe- sized that legumes may be interseeded into switchgrass to increase available soil nitrogen (N) and enhance switchgrass yields. Therefore the primary objective was to identify compatible legume species for intercropping with lowland switchgrass and determine if biomass yields and forage quality can be improved. Four cool- and two warm-season legume species were compared to application of 67 and 134 kg N ha -1 (59.8 and 119.6 lb N ac -1 ) during 2009 and 2010 over a range of soils at three research and education centers in Tennessee. Cool-season legumes were alfalfa (Medicago sativa L.), red clover (Trifolium pratense L.), crimson clover (Trifolium incarnatum L.), and hairy vetch (Vicia villosa L.), and warm-season legumes included Illinois bundle flower (Desmanthus illinoensis L.) and partridge pea (Chamaechrista fasciculata L.). Legumes were evaluated for establishment (plant densities) and their effects on switch- grass yield and forage quality under a one-cut biomass (single, postdormancy biofuel) and an integrated two-cut (biomass/forage (preanthesis)) system. In the one-cut system, switchgrass yields (16.6 Mg ha -1 (6.7 tn ac -1 )) from the current recommended rate (67 kg N ha -1 (59.8 lb N ac -1 )) exceeded (p < 0.05) legume treatment yields (average 13.5 Mg ha -1 (5.5 tn ac -1 )). In the integrated harvest system, switchgrass yields from red (13.4 Mg ha -1 (5.4 tn ac -1 )) and crimson clover (12.8 Mg ha -1 (5.2 tn ac -1 )) intercrops were not different from 67 kg N ha -1 (14.5 Mg ha -1 (5.9 tn ac -1 )). Crude protein levels were greater (p < 0.05) for 134 kg N ha -1 (119.6 lb N ac -1 ), compared to legume intercrops (except red clover). Partridge pea showed promise as a warm-season legume that can be grown compatibly with switchgrass for up to two years. Therefore, compatible legume-intercrop candidates, such as partridge pea and red clover, may enhance switchgrass yield and forage quality while displacing synthetic N in inte- grated biofuel/forage systems, but need to be further investigated in efforts to reduce nitrate (NO 3 ) leaching and emissions from fertilizing.

UAS imaging-based decision tools for arid winter wheat and irrigated potato production management

ABSTRACTSmall unmanned aerial systems (UAS) are gaining global attention for rapid image-based decision making in agricultural production. In this study, the aim was to evaluate UAS-based imagery for rapid assessment of wheat winter survival and spring stand in winter wheat production and crop necrosis in potato production. Both are critical aspects of field (arid) and row (irrigated) crop farming practices. Aerial images from 97 hard and 352 soft single nucleotide polymorphism winter wheat plots, and 32 potato field plots (with 1 and 2 years of green manure applications) were acquired using a multi-band imaging sensor integrated with UAS. The UAS-based imagery was useful in evaluating winter wheat plant winter survival and spring stand, with Pearson correlation coefficient (r) in the range 0.60–0.82 between imagery and ground reference data. Similarly, the image-based potato field necrosis assessment showed a strong relationship with ground reference data (r = 0.93 and 0.88 for 1 and 2 years of green manure application, respectively). Overall, UAS imagery provided quantifiable, timely, and unbiased field data with high spatial resolution (about 2.3 cm/pixel for images acquired at 100 m altitude) that can aid in field and row crop production decision making.

Cropping systems and the prevalence of giant ragweed (Ambrosia trifida): From the 1950’s to present

Over the course of the past two decades, giant ragweed (Ambrosia trifida L.) has become an important weed of arable lands in many parts of the United States and Canada. Its shift from a primarily ruderal weed to one commonly found in row crop production has coincided with advancements in maize and soybean production practices and the associated fluctuations in the area seeded to each of these major crops. A field trial was conducted over three years to explore how cropping systems practices representative of distinct eras of maize and soybean production (i.e., the 1950s, 1980s and 2000s) influenced giant ragweed’s ability to grow, develop and successfully reproduce within a crop field. Maize hybrids and soybean cultivars bred in each era were seeded in separate split plot designs with era of production practices as the whole plot and time of giant ragweed transplanting (i.e., at crop emergence or 14 days after) as the split plot. Results of this study indicate that historic changes brought about through maize breeding and shifts in cropping systems practices have increased the capacity of this crop to suppress the growth and reproduction of giant ragweed. Conversely, the phenotypic shift of soybean from a vine to a more upright row crop, coupled with the relative lack of change in production practices, has had little impact on its weed suppressive capacity. Giant ragweed’s ability to overtop soybean, even when placed at a competitive disadvantage by delayed emergence, creates a situation where the control of giant ragweed seed production is almost exclusively dependent on the availability and efficacy of in-crop herbicide options. In contrast, there is a clear potential for the suppression of giant ragweed fecundity when modern maize hybrids, planted at high plant population densities, are provided a 14d weed-free window following emergence.

FORAGES AND PASTURES SYMPOSIUM: Improving soil health and productivity on grasslands using managed grazing of livestock.

Beyond grazing, managed grasslands provide ecological services that may offer economic incentives for multifunctional use. Increasing biodiversity of plant communities may maximize net primary production by optimizing utilization of available light, water, and nutrient resources; enhance production stability in response to climatic stress; reduce invasion of exotic species; increase soil OM; reduce nutrient leaching or loading in surface runoff; and provide wildlife habitat. Strategically managed grazing may increase biodiversity of cool-season pastures by creating disturbance in plant communities through herbivory, treading, nutrient cycling, and plant seed dispersal. Soil OM will increase carbon and nutrient sequestration and water-holding capacity of soils and is greater in grazed pastures than nongrazed grasslands or land used for row crop or hay production. However, results of studies evaluating the effects of different grazing management systems on soil OM are limited and inconsistent. Although roots and organic residues of pasture forages create soil macropores that reduce soil compaction, grazing has increased soil bulk density or penetration resistance regardless of stocking rates or systems. But the effects of the duration of grazing and rest periods on soil compaction need further evaluation. Because vegetative cover dissipates the energy of falling raindrops and plant stems and tillers reduce the rate of surface water flow, managing grazing to maintain adequate vegetative cover will minimize the effects of treading on water infiltration in both upland and riparian locations. Through increased diversity of the plant community with alterations of habitat structure, grazing systems can be developed that enhance habitat for wildlife and insect pollinators. Although grazing management may enhance the ecological services provided by grasslands, environmental responses are controlled by variations in climate, soil, landscape position, and plant community resulting in considerable spatial and temporal variation in the responses. Furthermore, a single grazing management system may not maximize livestock productivity and each of the potential ecological services provided by grasslands. Therefore, production and ecological goals must be integrated to identify the optimal grazing management system.

Comparing Physical, Chemical, and Cold Stratification Methods for Alleviating Dormancy of Giant Ragweed (Ambrosia trifida) Seeds

Giant ragweed has become an increasingly important weed of arable land in many parts of North America. It is now a common weed of row crop production systems, a fact that can be attributed to earlier crop planting dates, reduced tillage, and the development of resistance to Group 2 and 9 herbicides. The propagation of giant ragweed seedlings for experimental purposes is a lengthy process because up to 90 d of stratification is often required to alleviate primary seed dormancy. The objective of this research was to evaluate physical, chemical, and cold stratification methods for alleviating seed dormancy in giant ragweed and reducing the length of cold stratification required. Results indicate that the most effective method for alleviating dormancy in seed of giant ragweed is to excise the embryo from its covering structures. By excising the embryo, 96% of viable giant ragweed seeds germinated with no stratification. In contrast, untreated seeds required a minimum of 6 wk of stratification to alleviate dormancy in a similar proportion of the population. Although excising embryos requires time and effort, the time savings relative to stratification make it an attractive method for propagating giant ragweed seedlings.

Farmer identities and responses to the social–biophysical environment

Row crop production in the United States (US) Midwest is responsible for a myriad of water pollution issues in the Mississippi River Basin and the Gulf of Mexico. US federal and state governments have spent billions of dollars since the 1930's to understand and develop biological and geophysical practices that will reduce the negative impacts of agriculture on these landscapes and water bodies. However, significantly fewer resources have been applied to understanding the human factor within this social–ecological system. Recently the social psychological framework known as farmer identity as been used to better understand how farmers view themselves as they perform their role as farmer. To empirically test this concept in the US state of Iowa, a farmer identity question was developed and data were collected as part of an annual survey of Iowa farmers. Four farmer identities (Productivist, Conservationist, Civic-minded, and Naturalist) are identified using principal components analysis and tested for their ability to predict support for farm policy scenarios related to soil and water resource protection. Results show that Productivist, Conservationist, and Naturalist identities were likely to be activated by soil and water policies; and the Civic-minded identity was not activated by soil and water policies in general but was significantly against more money for conservation because it might mean more regulation.

Surface Soil Quality Attributes following 12 Years of Conventional and Conservation Management on Irrigated Rotations in Southern Alberta

Rapid expansion of irrigated row crop production, viz., potato (Solanum tuberosum L.), dry bean (Phaseolus vulgaris L.), and sugar beet (Beta vulgaris L.), in southern Alberta in the late 1990s provided the impetus for a 12‐yr (2000–2011) study to evaluate cropping systems that maintained or improved soil quality. The study compared conservation (CONS) and conventional (CONV) management in rotations of 3‐ to 6‐yr duration. Conservation management included reduced tillage, cover crops, feedlot manure compost addition, and solid‐seeded narrow‐row dry bean production. After 12 yr, particulate organic matter C (POM‐C) and N (POM‐N) showed &gt;145% increases (POM‐C, 2.2–5.8 Mg ha−1; POM‐N, 0.20–0.49 Mg ha−1) with CONS management compared with 45 to 50% increases in total organic C and N (TOC, 10.2–15.3 Mg ha−1; TN, 1.06–1.53 Mg ha−1) and 20% increases in fine organic matter (FOM)‐C and ‐N (FOM‐C, 8.3–10.1 Mg ha−1; FOM‐N, 0.87–1.04 Mg ha−1). Aggregate stability of the pre‐wet &gt;1‐mm fraction increased significantly from 13% under CONV to 21% under CONS management. Overall, the 5‐yr CONS rotation (sugar beet–wheat (Triticum aestivum L.)–dry bean–potato–wheat) ranked highest for soil quality (100%), with CONV rotations substantially lower (33–38%). Adoption of CONS management enhanced a wide range of soil quality attributes that could safeguard sustainable expansion of irrigated specialty cropping in southern Alberta.

HIGH-SPEED CULTIVATION AND BANDING FOR WEED MANAGEMENT IN NO-TILL CORN

Replacing herbicides with mechanical cultivation can reduce pesticide use in row crop production. Although a majority of Iowa’s corn land is cultivated, most is cultivated only once and herbicide is broadcast applied. To increase grower confidence in reducing herbicide use and in using cultivation for interrow weed control, a three-year field experiment compared various single-cultivation plus band-herbicide application strategies with broadcast application strategy and no-control strategy. To cover larger acreages in a narrow window of time, cultivation speed was increased each year from 11.3 to 14.1 to 16.9 km/h (7.0, 8.8, and 10.5 mph). A 38-cm (15-in.) herbicide band treatment had less weed growth, and generally greater yield, extended leaf height, and corn population than did a 19-cm (7.5-in.) band treatment. Few differences were noted among cultivator styles. Weed management and grain yield were as good or better with the traditional low-crown sweep as with other styles. Its wider cutting width (56-cm or 22 in.) in 76-cm (30-in.) rows resulted in a lower corn population, however, when operated at 16.9 km/h (10.5 mph) with a crosswind. Differences in weed population and visual weed cover rankings when comparing single-cultivation with broadcast-only strategies varied with years. Grain yield from a treatment using a single cultivation with a low-crown sweep and a 38-cm (15-in.) wide herbicide band was statistically equivalent to that from a broadcast-only treatment in all three years. Results of this study indicate that herbicide use can be halved and weed control and corn yield can be maintained by use of a 38 cm (15 in.) herbicide band and a single sweep cultivation.

Testing Leaf Multispectral Reflectance Data as Input into Random Forest to Differentiate Velvetleaf from Soybean

Velvetleaf (Abutilon theophrasti Medic.) infestations negatively impact row crop production throughout the United States and Canada’s eastern provinces. To implement management strategies to control velvetleaf, managers need tools for differentiating it from crop plants. 5 Band, 7 Band, 8 Band, and 16 Band multispectral datasets simulating LANDSAT 3 plus a blue band, LANDSAT 8, WorldView 2, and WorldView 3 spectral bands, respectively were tested as input into the random forest algorithm for velvetleaf soybean [Glycine max L. (Merr.)] discrimination. During two separate greenhouse experiments in 2014, leaf reflectance measurements were obtained at the vegetative growth stage of velvetleaf plants and two soybean varieties. The reflectance measurements were collected with a plant contact probe attached to a hyperspectral spectroradiometer. Leaf hyperspectral reflectance measurements were convolved to the four multispectral datasets with computer software. Overall, user’s, and producer’s accuracies and kappa coefficient were employed to determine classification accuracies. Using the multispectral datasets as input, the random forest algorithm differentiated velvetleaf from the soybean varieties with accuracies ranging from 86.7% to 100%. 7 Band, 16 Band, 8 Band, and 5 Band datasets ranked or tied for the highest accuracies seventeen, sixteen, twelve, and one time, respectively. Kappa coefficients indicated an almost perfect agreement (i.e., kappa value, 0.81 - 1.0) to substantial agreement (i.e., kappa value, 0.61 - 0.80) between reference data and model predicted classes. This study was the first to demonstrate the application of the random forest machine learner and leaf multispectral reflectance data as tools to distinguish velvetleaf from soybean and to identify multispectral band combinations providing the best accuracies. Findings support further application of the random forest machine learner along with remotely-sensed multispectral data as tools for velvetleaf soybean discrimination with future implications for site-specific management of velvetleaf.

Response of Two Inexpensive Commercially Produced Soil Moisture Sensors to Changes in Water Content and Soil Texture

The use of low-cost (<200 USD) soil moisture sensors in crop production systems has the potential to give inference on plant water status and therein drive irrigation events. However, commercially available sensors in this price range vary in sensing methodologies and limited information on sensor to sensor relationship is available. The objective of this research was to test the response of the Watermark 200SS and Decagon 10HS sensors to changes in water content of three dissimilar soils representing common soils in Arkansas row-crop production in nine plastic, 19 L containers under variable environmental conditions. Both sensors were influenced by changes in soil temperature but the magnitudes of the temperature responses were small relative to the moisture responses. Furthermore, the 10HS sensor did not indicate a significant impact of soil texture on estimated volumetric water contents (VWCs). The small sphere of influence on the tested soil moisture parameters coupled with the substantial evaporative demands and temperatures under which this experiment was conducted resulted in suspected non-uniform drying and wetting of the tested containers. Subsequently, non-linear relationships were noted between 10HS estimated VWCs and actual container VWCs and the 200SS predicted lower water potentials than calculated by converting container VWC to soil water potential. The failure of the sensors to accurately predict container VWC highlights the importance of understanding the relatively small quantity of soil on which these sensors rely as well as the potential variability in soil moisture within a very limited volume. The authors caution users of sensors that soil variability may be one of the most important considerations in sensor deployment.

Opportunities for Energy Crop Production Based on Subfield Scale Distribution of Profitability

Incorporation of dedicated herbaceous energy crops into row crop landscapes is a promising means to supply an expanding biofuel industry while benefiting soil and water quality and increasing biodiversity. Despite these positive traits, energy crops remain largely unaccepted due to concerns over their practicality and cost of implementation. This paper presents a case study for Hardin County, Iowa, to demonstrate how subfield decision making can be used to target candidate areas for conversion to energy crop production. Estimates of variability in row crop production at a subfield level are used to model the economic performance of corn (Zea mays L.) grain and the environmental impacts of corn stover collection using the Landscape Environmental Analysis Framework (LEAF). The strategy used in the case study integrates switchgrass (Panicum virgatum L.) into subfield landscape positions where corn grain is modeled to return a net economic loss. Results show that switchgrass integration has the potential to increase sustainable biomass production from 48% to 99% (depending on the rigor of conservation practices applied to corn stover collection), while also improving field level profitability of corn. Candidate land area is highly sensitive to grain price (0.18 to 0.26 $·kg−1) and dependent on the acceptable subfield net loss for corn production (ranging from 0 to −1000 $·ha−1) and the ability of switchgrass production to meet or exceed this return. This work presents the case that switchgrass may be economically incorporated into row crop landscapes when management decisions are applied at a subfield scale within field areas modeled to have a negative net profit with current management practices.

Pelletized Biochar as a Carrier for AM Fungi in the On-Farm System of Inoculum Production in Compost and Vermiculite Mixtures

ABSTRACT.On farm production of arbuscular mycorrhizal (AM) fungi is suitable for vegetable and horticultural crop production because the inocula may be efficiently mixed into horticultural potting media for plant production in the greenhouse. These inocula are not amenable for use in row crop production because they are not in a form suitable for mechanical application. Experiments were conducted in which light expanded clay aggregates (LECA) and pelletized biochar were used in the media for the on-farm production of AM fungus inoculum utilizing compost and vermiculite with Paspalum notatum Flugge as the nurse host plant. Subsequent colonization assays using P. notatum failed to detect any infectivity of LECA granules, indicating that the AM fungi did not infest the granules. However, as little as 0.1 g fresh wt of biochar was sufficient to produce colonization of test plants. Biochar pellets recovered from the on-farm system used to propagate Rhizophagus intraradices exhibited 24 propagules g−1 fresh wt. These results indicate the promise of pelletized biochar as a carrier for AM fungi in inoculum production systems.

Total and labile pools of soil organic carbon in cultivated and undisturbed soils in northern India

Labile fractions of soil organic matter (SOM) have been used as indicators for land use induced changes in soil quality. Differences in soil C pools under row crop production and uncultivated soils may provide information about soil C sequestration. The impact of agroforestry consisting of poplar with wheat, rice–wheat, maize–wheat and sugarcane agro-ecosystems on total organic carbon (TOC) and labile pools, viz. water-extractable (WEOC), hot water-soluble (HWC), KMnO4-oxidizable, microbial biomass and mineralizable C; and organic C fractions of different oxidizability was studied at 22-sites for each land use. Cultivation resulted in decrease in TOC (21–36%) and dehydrogenase activity (by 2.8–3.4mgkg−1soilh−1) compared to uncultivated soils. Labile C pools, except WEOC, were correlated (P<0.05), though the amount extracted by different methods varied considerably suggesting that each method enumerated different fractions of TOC. Agroforestry and sugarcane systems were characterized by very labile C compared with uncultivated soils and the soils under rice–wheat and maize–wheat systems. Conversely, uncultivated soils and the soils under maize–wheat and rice–wheat held greater proportion of organic C in recalcitrant fractions. Results suggest that soil organic C (SOC) pools in agroforestry and sugarcane systems could be decomposed under land use alterations. However, no single soil C pool alone was suitable as a sensitive indicator for land use induced changes in SOM. A composite of soil indicators encompassing labile C, KMnO4-oxidizable C, non-labile and recalcitrant C, mineralizable C, basal soil respiration, and dehydrogenase activity could distinguish different land use systems.

Co-robotic intra-row weed control system

The automation of intra-row weed control in row crop production systems is very challenging. This work describes the development and in-field assessment of an automatic intra-row, hoe-based weeding co-robot system with real-time pneumatic hoe actuation based on an accurate odometry sensing technique. The US National Science Foundation has identified a need for robots (called co-robots) that serve as co-workers and work beside, or cooperatively with, people. These co-robots have a symbiotic relationship with a human partner, where, as a team, they combine their relative strengths to jointly perform a task. Such co-robots should be relatively inexpensive and easy to use. In this work, mechanical weed control was achieved by a co-robot actuator that automatically positioned a pair of miniature hoes into the intra-row zone between crop plants. The design was tested in a precision transplanted row crop and may also be suitable for direct seeded row crops. Co-robot cost was minimised by limiting the system to a single, simple odometry sensor. Co-robot hoe actuation was controlled using pre-programmed knowledge of the crop planting pattern and real-time odometry data as the control input for hoe positioning. Low-frequency drift in the odometry control points relative to the actual plant locations was corrected occasionally as needed in real-time by a human partner monitoring system performance. The co-robot was evaluated in an experimental trial conducted on the UC Davis campus farm. Assessment was based upon the follow-up hand hoeing required after automated intra-row weeding in comparison to the labour required to manually hoe a control plot. The mean person hours required for hand hoeing weeds in the control were 0.241 h for the 100 m2 plot, while only 0.102 h 100 m−2 were required in follow-up labour to complete the weed removal in the plots weeded by the co-robot. This represents a 57.5% reduction in hand labour requirements for intra-row weed control and indicates that the co-robot could help reduce traditional hand hoeing labour requirements with mechanised weed control in intra-row areas between the crop plants.