Iowa Crop Progress & Condition, October 31, 2016

Report produced by the The Department of Agriculture and Land Stewardship, Climatology Bureau. Weather report released by the USDA National Agricultural Statistical Service. The report is released weekly from April through October. Formally titled: Iowa Crop and Weather Report

Influence of mucuna fallow crop on selected soil properties, weed suppression and taro yields in Taveuni, Fiji

Two field experiments were carried out in Taveuni, Fiji to study the effects of mucuna (Mucuna pruriens) and grass fallow systems at 6 and 12 month durations on changes in soil properties (Experiment 1) and taro yields (Experiment 2). Biomass accumulation of mucuna fallow crop was significantly higher (P<0.05) than grass fallow crop at both 6 and 12 month durations. The longer fallow duration resulted in higher (P<0.05) total soil organic carbon, total soil nitrogen and earthworm numbers regardless of fallow type. Weed suppression in taro grown under mucuna was significantly greater (P<0.05) than under natural grass fallow. Taro grown under mucuna fallow significantly outyielded taro grown under grass fallow (11.8 vs. 8.8 t ha-1). Also, the gross margin of taro grown under mucuna fallow was 52% higher than that of taro grown under grass fallow. © ISHS.

Statistical forecasting of the Australian macadamia crop

Three types of forecasts of the total Australian production of macadamia nuts (t nut-in-shell) have been produced early each year since 2001. The first is a long-term forecast, based on the expected production from the tree census data held by the Australian Macadamia Society, suitably scaled up for missing data and assumed new plantings each year. These long-term forecasts range out to 10 years in the future, and form a basis for industry and market planning. Secondly, a statistical adjustment (termed the climate-adjusted forecast) is made annually for the coming crop. As the name suggests, climatic influences are the dominant factors in this adjustment process, however, other terms such as bienniality of bearing, prices and orchard aging are also incorporated. Thirdly, industry personnel are surveyed early each year, with their estimates integrated into a growers and pest-scouts forecast. Initially conducted on a 'whole-country' basis, these models are now constructed separately for the six main production regions of Australia, with these being combined for national totals. Ensembles or suites of step-forward regression models using biologically-relevant variables have been the major statistical method adopted, however, developing methodologies such as nearest-neighbour techniques, general additive models and random forests are continually being evaluated in parallel. The overall error rates average 14% for the climate forecasts, and 12% for the growers' forecasts. These compare with 7.8% for USDA almond forecasts (based on extensive early-crop sampling) and 6.8% for coconut forecasts in Sri Lanka. However, our somewhatdisappointing results were mainly due to a series of poor crops attributed to human reasons, which have now been factored into the models. Notably, the 2012 and 2013 forecasts averaged 7.8 and 4.9% errors, respectively. Future models should also show continuing improvement, as more data-years become available.

A review of weed management in wheat using crop competition

Wheat occupies a principal place in the diet of humans globally, contributing more to our daily calorie and protein intake than any other crop. For this reason, preventing weed induced yield losses in wheat has high significance for world food sustainability. Herbicides and tillage play an important role in weed control, but their use has often unacceptable consequences for humans and the wider environment. Additionally, the range of herbicides effective on key weeds is dwindling due to the evolution of herbicide resistance. Elevating crop competitiveness against weeds, through a combination of wheat breeding and innovative planting design (planting density, row spacing and orientation), has strong potential to reduce weed-induced yield losses in wheat. The last decade of research has provided a solid foundation for the breeding of weed suppressive wheat cultivars, and continued research in this area should be a focus for the future. In the interim, there is cause for optimism that weeds can be effectively suppressed using existing wheat varieties, through careful cultivar selection and choice of planting design. Further research is required to define the nature of relationships between cultivar traits and competitive planting strategies, across diverse weed flora in multiple countries, sites and seasons. Investment in such innovation promises to produce benefits, not only in terms of sustained wheat yields, but also in terms of human and ecosystem health, through ameliorating chemical and sediment contamination, soil degradation, and CO2 pollution.

Sorghum Crop Modeling and Its Utility in Agronomy and Breeding

Crop models are simplified mathematical representations of the interacting biological and environmental components of the dynamic soil–plant–environment system. Sorghum crop modeling has evolved in parallel with crop modeling capability in general, since its origins in the 1960s and 1970s. Here we briefly review the trajectory in sorghum crop modeling leading to the development of advanced models. We then (i) overview the structure and function of the sorghum model in the Agricultural Production System sIMulator (APSIM) to exemplify advanced modeling concepts that suit both agronomic and breeding applications, (ii) review an example of use of sorghum modeling in supporting agronomic management decisions, (iii) review an example of the use of sorghum modeling in plant breeding, and (iv) consider implications for future roles of sorghum crop modeling. Modeling and simulation provide an avenue to explore consequences of crop management decision options in situations confronted with risks associated with seasonal climate uncertainties. Here we consider the possibility of manipulating planting configuration and density in sorghum as a means to manipulate the productivity–risk trade-off. A simulation analysis of decision options is presented and avenues for its use with decision-makers discussed. Modeling and simulation also provide opportunities to improve breeding efficiency by either dissecting complex traits to more amenable targets for genetics and breeding, or by trait evaluation via phenotypic prediction in target production regions to help prioritize effort and assess breeding strategies. Here we consider studies on the stay-green trait in sorghum, which confers yield advantage in water-limited situations, to exemplify both aspects. The possible future roles of sorghum modeling in agronomy and breeding are discussed as are opportunities related to their synergistic interaction. The potential to add significant value to the revolution in plant breeding associated with genomic technologies is identified as the new modeling frontier.

EFFECT OF SORGHUM SEED TREATMENT IN BURKINA FASO VARIES WITH BASELINE CROP PERFORMANCE AND GEOGRAPHICAL LOCATION

Sorghum [ Sorghum bicolor (L.) Moench] is a major subsistence crop throughout the region of Sahel. With the exception of seeds and labour, no agricultural inputs are in general used in sorghum production since the grain is of a relatively low commercial value and the risk of losing the crop to drought, flooding, etc. is substantial. A meta-analysis of 118 field experiments was carried out to identify conditions in which two protective seed treatments could support a yield increase of sorghum in Burkina Faso. The two treatments were: i) treatment with the pesticide Calthio C (thiram and chlorpyrifos) and ii) treatment with an aqueous extract from the plant Eclipta alba . Both treatments were found to produce a yield increase (Medians: Calthio C +199 kg ha-1, P<2x10-9; E. alba +90.5 kg ha-1 P<4x10-4). A strong relative effect of Calthio C on yield (+36%) was found for field experiments with a low baseline yield. A strong relative effect of E. alba extract on yield (+22%) was found for experiments with a low baseline of emergence. ANOVA of the 118 field tests showed that baseline crop performance (yield and emergence) and the effect of seed treatments were strongly linked to geographical location (twelve different villages included). Roots from sorghum in the village showing the strongest effect of both seed treatments (>40% yield increase) were found to carry a comparatively high load of the infectious ascomycetes: Fusarium equiseti , Macrophomina phaseolina and Curvularia lunata .

Federal Crop Insurance Program Expands in 2016 and 2017 to Cover More Organic Crops

Organic agriculture represents one of the fastest growing segments of U.S. agriculture (USDA-RMA). With this in mind, the USDA’s Risk Management Agency (RMA) continues to expand crop insurance options for organic growers. In 2016 and 2017, organic producers in Maryland will see additional crops with organic crop insurance options. Increasing crop insurance options will allow this segment of producers new opportunities to manage their risks.

Crop Insurance For Maryland Field Crops And Livestock

Multi-peril crop insurance is a valuable risk management tool which allows you to insure against losses on your farm due to adverse weather conditions, price fluctuations, and unavoidable pests and diseases. It shifts unavoidable production risks to an insurance company for the payment of a fixed amount of premium per acre. This publication assists readers in understanding the basics of the federal crop insurance program.

NITROUS OXIDE EMISSIONS IN COVER CROP-BASED CORN PRODUCTION SYSTEMS

Nitrous oxide (N2O) is a potent greenhouse gas; the majority of N2O emissions are the result of agricultural management, particularly the application of N fertilizers to soils. The relationship of N2O emissions to varying sources of N (manures, mineral fertilizers, and cover crops) has not been well-evaluated. Here we discussed a novel methodology for estimating precipitation-induced pulses of N2O using flux measurements; results indicated that short-term intensive time-series sampling methods can adequately describe the magnitude of these pulses. We also evaluated the annual N2O emissions from corn-cover crop (Zea mays; cereal rye [Secale cereale], hairy vetch [Vicia villosa], or biculture) production systems when fertilized with multiple rates of subsurface banded poultry litter, as compared with tillage incorporation or mineral fertilizer. N2O emissions increased exponentially with total N rate; tillage decreased emissions following cover crops with legume components, while the effect of mineral fertilizer was mixed across cover crops.

Optimization of microwave-assisted extraction of hydrophilic and lipophilic antioxidants from a surplus tomato crop by response surface methodology

Tomato is the second most important vegetable crop worldwide and a rich source of industrially interesting antioxidants. Hence, the microwave-assisted extraction of hydrophilic (H) and lipophilic (L) antioxidants from a surplus tomato crop was optimized using response surface methodology. The relevant independent variables were temperature (T), extraction time (t), ethanol concentration (Et) and solid/liquid ratio (S/L). The concentration-time response methods of crocin and β-carotene bleaching were applied, since they are suitable in vitro assays to evaluate the antioxidant activity of H and L matrices, respectively. The optimum operating conditions that maximized the extraction were as follows: t, 2.25 min; T, 149.2 ºC; Et, 99.1 %; and S/L, 45.0 g/L for H antioxidants; and t, 15.4 min; T, 60.0 ºC; Et, 33.0 %; and S/L, 15.0 g/L for L antioxidants. This industrial approach indicated that surplus tomatoes possess a high content of antioxidants, offering an alternative source for obtaining natural value-added compounds. Additionally, by testing the relationship between the polarity of the extraction solvent and the antioxidant activity of the extracts in H and L media (polarity-activity relationship), useful information for the study of complex natural extracts containing components with variable degrees of polarity was obtained.

CLIMATE CHANGE ADAPTATION IN VULNERABLE CROP AND LIVESTOCK PRODUCTION SYSTEMS IN MGETA, TANZANIA

Increased occurrence of drought and dry spells during the growing season have resulted in increased interest in protection of tropical water catchment areas. In Mgeta, a water catchment area in the Uluguru Mountains in Tanzania, water used for vegetable and fruit production is provided through canals from the Uluguru South Forest Reserve. The clearing of forest land for cultivation in the steep slopes in the area is causing severe land degradation, which is threatening the water catchment area, livelihoods, and food security of the local communities, as well as the major population centers in the lowlands. In this paper, the economic performance of a traditional cropping-livestock system with East African (EA)-goats and pigs and extensive vegetable production is compared with a more sustainable and environmentally friendly crop-dairy goat production system. A linear programming (LP) crop-livestock model, maximizing farm income considering the environmental constraints in the area was applied for studying the economic performance of dairy goats in the production system. The model was worked out for the rainy and dry seasons and the analysis was conducted for a basic scenario representing the current situation, based on the variability in the 30 years period from 1982-2012, and in a scenario of both lower crop yields and increased crop variability due to climate change. Data obtained from a sample of 60 farmers that were interviewed using a questionnaire was used to develop and parameterize the model. The study found that in the steep slopes of the area, a crop-dairy goat system with extensive use of grass and multipurpose trees (MPTs) would do better than the traditional vegetable gardening with the EA goat production system. The crop-dairy goat system was superior both in the basic and in a climate change scenario since the yield variation of the grass and MPTs system was less affected compared to vegetable crops due to more tree cover and the use of perennial grasses. However, the goat milk production in the area was constrained by inadequate feeding and lack of an appropriate breeding program. Hence, farmers should enhance goat milk production by supplementing with more concentrate feed and by implementing goat-breeding principles. Moreover, policy measures to promote such a development are briefly discussed.

Bacterial communities of the specialty crop phyllosphere: response to biological soil amendment use, rainfall, and insect visitation

Microorganisms in the plant rhizosphere, the zone under the influence of roots, and phyllosphere, the aboveground plant habitat, exert a strong influence on plant growth, health, and protection. Tomatoes and cucumbers are important players in produce safety, and the microbial life on their surfaces may contribute to their fitness as hosts for foodborne pathogens such as Salmonella enterica and Listeria monocytogenes. External factors such as agricultural inputs and environmental conditions likely also play a major role. However, the relative contributions of the various factors at play concerning the plant surface microbiome remain obscure, although this knowledge could be applied to crop protection from plant and human pathogens. Recent advances in genomic technology have made investigations into the diversity and structure of microbial communities possible in many systems and at multiple scales. Using Illumina sequencing to profile particular regions of the 16S rRNA gene, this study investigates the influences of climate and crop management practices on the field-grown tomato and cucumber microbiome. The first research chapter (Chapter 3) involved application of 4 different soil amendments to a tomato field and profiling of harvest-time phyllosphere and rhizosphere microbial communities. Factors such as water activity, soil texture, and field location influenced microbial community structure more than soil amendment use, indicating that field conditions may exert more influence on the tomato microbiome than certain agricultural inputs. In Chapter 4, the impact of rain on tomato and cucumber-associated microbial community structures was evaluated. Shifts in bacterial community composition and structure were recorded immediately following rain events, an effect which was partially reversed after 4 days and was strongest on cucumber fruit surfaces. Chapter 5 focused on the contribution of insect visitors to the tomato microbiota, finding that insects introduced diverse bacterial taxa to the blossom and green tomato fruit microbiome. This study advances our understanding of the factors that influence the microbiomes of tomato and cucumber. Farms are complex environments, and untangling the interactions between farming practices, the environment, and microbial diversity will help us develop a comprehensive understanding of how microbial life, including foodborne pathogens, may be influenced by agricultural conditions.