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Himanen, S. J., Ketoja, E., Hakala, K., Rötter, R. P., Salo, T., & Kahiluoto, H. (2013). Cultivar diversity has great potential to increase yield for feed barley. Agron. Sust. Developm., 33(3), 519–530.
Abstract: This study shows an average yield increase of 415–1,338 kg ha−1 per unit increase of the Shannon diversity index for feed barley cultivar use. There is a global quest to increase food production sustainably. Therefore, judicious farmer choices such as selection of crop cultivars are increasingly important. Cultivar diversity is limited and, as a consequence, corresponding crop yields are highly impacted by local weather variations and global climate change. Actually, there is little knowledge on the relationships between yields of regional crops and cultivar diversity, that is evenness and richness in cultivar use. Here, we hypothesized that higher cultivar diversity is related to higher regional yield. We also assumed that the diversity-yield relationship depends on weather during the growing season. Our data were based on farm yield surveys of feed and malting barley, Hordeum vulgare L.; spring wheat, Triticum aestivum L.; and spring turnip rape, Brassica rapa L. ssp. oleifera, from 1998 to 2009, representing about 4,500–5,500 farms annually. We modeled the relationships between regional yields and Shannon diversity indices in high-yielding (south-west) and low-yielding (central-east) regions of Finland using linear mixed models. Our results show that an increase of Shannon diversity index increases yield of feed barley. Feed barley had also the greatest cultivar diversity. In contrast, an average yield decrease of 1,052 kg ha−1 per unit increase in Shannon index was found for spring rape in 2006 and 2008. Our findings show that cultivar diversification has potential to raise mean regional yield of feed barley. Increasing cultivar diversity thus offers a novel, sustainability-favoring means to promote higher yields.
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Elliott, J., Müller, C., Deryng, D., Chryssanthacopoulos, J., Boote, K. J., Büchner, M., et al. (2015). The Global Gridded Crop Model Intercomparison: data and modeling protocols for Phase 1 (v1.0). Geosci. Model Dev., 8(2), 261–277.
Abstract: We present protocols and input data for Phase 1 of the Global Gridded Crop Model Intercomparison, a project of the Agricultural Model Intercomparison and Improvement Project (AgMIP). The project includes global simulations of yields, phenologies, and many land-surface fluxes using 12-15 modeling groups for many crops, climate forcing data sets, and scenarios over the historical period from 1948 to 2012. The primary outcomes of the project include (1) a detailed comparison of the major differences and similarities among global models commonly used for large-scale climate impact assessment, (2) an evaluation of model and ensemble hindcasting skill, (3) quantification of key uncertainties from climate input data, model choice, and other sources, and (4) a multi-model analysis of the agricultural impacts of large-scale climate extremes from the historical record.
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Lessire, F., Hornick, J. L., Minet, J., & Dufrasne, I. (2015). Rumination time, milk yield, milking frequency of grazing dairy cows milked by a mobile automatic system during mild heat stress. Advances in Animal Biosciences, 6(01), 12–14.
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Andreoli, V., Cassardo, C., Iacona, L. T., & Spanna, F. (2019). Description and Preliminary Simulations with the Italian Vineyard Integrated Numerical Model for Estimating Physiological Values (IVINE). Agronomy, 9(2).
Abstract: The numerical crop growth model Italian Vineyard Integrated Numerical model for Estimating physiological values (IVINE) was developed in order to evaluate environmental forcing effects on vine growth. The IVINE model simulates vine growth processes with parameterizations, allowing the understanding of plant conditions at a vineyard scale. It requires a set of meteorology data and soil water status as boundary conditions. The primary model outputs are main phenological stages, leaf development, yield, and sugar concentration. The model requires setting some variety information depending on the cultivar: At present, IVINE is optimized for Vitis vinifera L. Nebbiolo, a variety grown mostly in the Piedmont region (northwestern Italy). In order to evaluate the model accuracy, IVINE was validated using experimental observations gathered in Piedmontese vineyards, showing performances similar or slightly better than those of other widely used crop models. The results of a sensitivity analysis performed to highlight the effects of the variations of air temperature and soil water potential input variables on IVINE outputs showed that most phenological stages anticipated with increasing temperatures, while berry sugar content saturated at about 25.5 °Bx. Long-term (60 years, in the period 1950–2009) simulations performed over a Piedmontese subregion showed statistically significant variations of most IVINE output variables, with larger time trend slopes referring to the most recent 30-year period (1980–2009), thus confirming that ongoing climate change started influencing Piedmontese vineyards in 1980.
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Rusu, T. (2014). Energy efficiency and soil conservation in conventional, minimum tillage and no-tillage. International Soil and Water Conservation Research, 2(4), 42–49.
Abstract: The objective of this research was to determine the capacity of a soil tillage system in soil conservation, in productivity and in energy efficiency. The minimum tillage and no-tillage systems represent good alternatives to the conventional (plough) system of soil tillage, due to their conservation effects on soil and to the good production of crops (Maize, 96%-98% of conventional tillage for minimum tillage, and 99.8% of conventional tillage for no till; Soybeans, 103%-112% of conventional tillage for minimum tillage and 117% of conventional tillage for no till; Wheat, 93%-97% of conventional tillage for minimum tillage and 117% of conventional tillage for no till. The choice of the right soil tillage system for crops in rotation help reduce energy consumption, thus for maize: 97%-98% energy consumption of conventional tillage when using minimum tillage and 91% when using no-tillage; for soybeans: 98% energy consumption of conventional tillage when using minimum tillage and 93 when using no-tillage; for wheat: 97%-98% energy consumption of conventional tillage when using minimum tillage and 92% when using no-tillage. Energy efficiency is in relation to reductions in energy use, but also might include the efficiency and impact of the tillage system on the cultivated plant. For all crops in rotation, energy efficiency (energy produced from 1 MJ consumed) was the best in no-tillage — 10.44 MJ ha− 1 for maize, 6.49 MJ ha− 1 for soybean, and 5.66 MJ ha− 1 for wheat. An analysis of energy-efficiency in agricultural systems includes the energy consumed-energy produced-energy yield comparisons, but must be supplemented by soil energy efficiency, based on the conservative effect of the agricultural system. Only then will the agricultural system be sustainable, durable in agronomic, economic and ecological terms. The implementation of minimum and no-tillage soil systems has increased the organic matter content from 2% to 7.6% and water stable aggregate content from 5.6% to 9.6%, at 0–30 cm depth, as compared to the conventional system. Accumulated water supply was higher (with 12.4%-15%) for all minimum and no-tillage systems and increased bulk density values by 0.01%-0.03% (no significant difference) While the soil fertility and the wet aggregate stability have initially been low, the effect of conservation practices on the soil characteristics led to a positive impact on the water permeability in the soil. Availability of soil moisture during the crop growth period led to a better plant watering condition. Subsequent release of conserved soil water regulated the plant water condition and soil structure.
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