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Integration of perennial forages in annual cropping systems can expand ecosystem service benefits to agricultural landscapes. Such benefits are frequently derived from changes to soil properties. Unfortunately, there is limited guidance for agricultural producers regarding the length of time needed to accrue soil condition improvements under perennial forages, particularly for semiarid regions. The objective of this study was to quantify soil responses to perennial grasses, legumes, and grass–legume mixtures over a 5-yr year period in a semiarid region. Select soil physical and chemical properties were measured within five perennial forage treatments and under annual cropping over a 5-yr period on a Parshall fine sandy loam near Mandan, ND. Treatment effects on soil properties were limited to the surface 10 cm. Differences in soil properties between spring wheat (Triticum aestivum L.) and perennial forages were most frequent following the fourth stand year. Compared with spring wheat, perennial forages mitigated soil acidification (by 0.26–0.65 pH units), reduced soil bulk density (by 0.04–0.08 Mg m–3), and increased particulate organic matter (POM) (by 0.41 g C kg–1) and water-stable aggregates (by 3.8%). Among perennial forages, intermediate wheatgrass (Thinopyrum intermedium L.) and intermediate wheatgrass–field pea (Pisum sativum L) mixture followed by alfalfa (Medicago spp.) reduced soil bulk density (by 0.06–0.11 Mg m–3) and increased POM (by 0.24–0.92 g C kg–1) compared with alfalfa following 4- and 5-yr perennial forage stands. While these outcomes suggest perennial forages can improve the near-surface soil condition, accrual of improvements may be slow and subtle in semiarid regions. [ABSTRACT FROM AUTHOR]

Perennial grass systems are being evaluated as a bioenergy feedstock in the northern Great Plains. Inter-annual and inter-seasonal precipitation variation in this region will require efficient water use to maintain sufficient yield production to support a mature bioenergy industry. Objectives were to evaluate the impact of a May-June (early season) and a July-August (late season) drought on the water use efficiency (WUE), amount of water used, and biomass production in monocultures of switchgrass ( Panicum virgatum L.), western wheatgrass ( Pascopyrum smithii (Rydb.) Á. Löve), and a western wheatgrass-alfalfa ( Medicago sativa L.) mixture using an automated rainout shelter. WUE was strongly driven by biomass accumulation and ranged from 5.6 to 7.4 g biomass mm water for switchgrass to 1.06 to 2.07 g biomass mm water used with western wheatgrass. Timing of water stress affected WUE more in western wheatgrass and the western wheatgrass-alfalfa mixture than switchgrass. Water deficit for the western wheatgrass-alfalfa mixture was 23 % lower than western wheatgrass ( P = 0.0045) and 31 % lower than switchgrass ( P < 0.0001) under the May-June stress water treatment, while switchgrass had a 37 and 38 % greater water deficit than did western wheatgrass or western wheatgrass-alfalfa mixture, respectively ( P < 0.001) under the July-August water stress treatment. Water depletion was always greatest in the upper 30 cm. Switchgrass had greater WUE but resulted in greater soil water depletion at the end of the growing season compared to western wheatgrass and a western wheatgrass-alfalfa mixture which may be a concern under multi-year drought conditions. [ABSTRACT FROM AUTHOR]

Economic analysis of forage production and handling aids in making an educated decision related to growing or buying forage, setting forage prices, and purchasing additional equipment. Manual calculation of economics is highly complex, tedious, and time-consuming. Therefore, a multi-device web-based tool, called the "forage economics calculator web tool" (FECWT) was developed using HTML, CSS, and JavaScript. The tool's interface was designed for a user-friendly experience with easy access to commands set in an easy-to-follow layout. The FECWT uses 29 input variables to generate results "dynamically" for 37 output variables, based either on the supplied default data or with user-provided inputs (imperial or metric units). The tool emphasizes the cost of the bale collection activity performed using tractor or tractor pulling an "automatic bale picker" (ABP), while the cost of other activities (planting, fertilizer & chemical application, harvesting, and baling) are provided as direct inputs. The economic analysis outputs include net return, break-even ratio, payback period, and return on investment. Features of FECWT include the sensitivity of profit to changes in input values, and downloadable reports and charts for record-keeping. Two case studies using farmers' actual field data inputs demonstrated the FECWT's effectiveness, with its generated results corroborating well with farmers' records. The tool allows for "what-if" scenario analysis related to equipment purchase, effect of forage crop, net-return, and low-inputs scenario for different field areas suggests that an ABP purchase for field areas greater than ≥ 65 ha (≥ 160 ac) could be profitable; alfalfa and corn were the most profitable forage and grain-forage crops, where the grain revenue stream of grain-forage crops easily covers the costs and makes a profit; and a low-inputs scenario (no fertilizers, chemicals, and/or seeds) for forages (alfalfa and grass) decreased the net returns on average by 8.1 times at 50% forage yield potential suggesting the use of all inputs and increased field areas (≥ 65 ha) make a better profit in this low-inputs scenario. Potential users of this web tool include farmers, hay producers, custom hay operators, educators, agricultural extension and financial personnel, and others interested in the economics of handling bales. [Display omitted] • Web tool calculator developed uses 29 inputs to generate 37 forage economics outputs. • Economics of bale collection using tractor and automatic bale picker is emphasized. • Tool's features include inputs sensitivity and downloadable report and chart. • Tool allows what-if scenario analysis for many practical field situations. • Actual field data case studies reported satisfactory performance of the tool. [ABSTRACT FROM AUTHOR]