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While adoption rates for inorganic fertiliser are relatively high in Ethiopia, application rates are generally considered agronomically suboptimal. Using recent data on Ethiopian smallholder maize producers, we showed that maize response to nitrogen, and the profitability of fertiliser use depended on maize agronomy. The agronomic optimum ranged from 0 to 344 kg/ha with a mean value of 209 kg/ha. The actual nitrogen application rates were only about half the agronomic optimum, on average, and were less than the farm-specific economic optimum on 80% of maize fields. The average economic optimum level was 145 kg N/ha, but when we account for risk aversion, the resulting average optimum level is very close to the average observed usage level of 88 kg N/ha. Addressing risk aversion may help to induce greater levels of fertiliser investments at current prices and yield response rates. Our analysis also suggests that key pathways for increasing the economic returns to smallholder fertiliser investments include: complementing nitrogen inputs with phosphorus inputs and improved varieties, using lower levels of nitrogen under intercropping and manure inputs, enabling farmers to delay output sales beyond the immediate post-harvest period, and lowering the costs of accessing input and output markets. [ABSTRACT FROM AUTHOR]

LiGAPS-Beef (Livestock simulator for Generic analysis of Animal Production Systems – Beef cattle) is a generic, mechanistic model designed to quantify potential and feed-limited growth, which provides insight in the biophysical scope to increase beef production (i.e. yield gap). Furthermore, it enables identification of the bio-physical factors that define and limit growth, which provides insight in management strategies to mitigate yield gaps. The aim of this paper, third in a series of three, is to evaluate the performance of LiGAPS-Beef with independent experimental data. After model calibration, independent data were used from six experiments in Australia, one in Uruguay and one in the Netherlands. Experiments represented three cattle breeds, and a wide range of climates, feeding strategies and cattle growth rates. The mean difference between simulated and measured average daily gains (ADGs) was 137 g/day across all experiments, which equals 20.1% of the measured ADGs. The root mean square error was 170 g/day, which equals 25.0% of the measured ADGs. LiGAPS-Beef successfully simulated the factors that defined and limited growth during the experiments on a daily basis (genotype, heat stress, digestion capacity, energy deficiency and protein deficiency). The simulated factors complied well to the reported occurrence of heat stress, energy deficiency and protein deficiency at specific periods during the experiments. We conclude that the level of accuracy of LiGAPS-Beef is acceptable, and provides a good basis for acquiring insight in the potential and feed-limited production of cattle in different beef production systems across the world. Furthermore, its capacity to identify factors that define or limit growth and production provides scope to use the model for yield gap analysis. [ABSTRACT FROM AUTHOR]

The model LiGAPS-Beef (Livestock simulator for Generic analysis of Animal Production Systems – Beef cattle) has been developed to assess potential and feed-limited growth and production of beef cattle in different areas of the world and to identify the processes responsible for the yield gap. Sensitivity analysis and evaluation of model results with experimental data are important steps after model development. The first aim of this paper, therefore, is to identify which parameters affect the output of LiGAPS-Beef most by conducting sensitivity analyses. The second aim is to evaluate the accuracy of the thermoregulation sub-model and the feed intake and digestion sub-model with experimental data. Sensitivity analysis was conducted using a one-at-a-time approach. The upper critical temperature (UCT) simulated with the thermoregulation sub-model was most affected by the body core temperature and parameters affecting latent heat release from the skin. The lower critical temperature (LCT) and UCT were considerably affected by weather variables, especially ambient temperature and wind speed. Sensitivity analysis for the feed intake and digestion sub-model showed that the digested protein per kg feed intake was affected to a larger extent than the metabolisable energy (ME) content. Sensitivity analysis for LiGAPS-Beef was conducted for ¾ Brahman×¼ Shorthorn cattle in Australia and Hereford cattle in Uruguay. Body core temperature, conversion of digestible energy to ME, net energy requirements for maintenance, and several parameters associated with heat release affected feed efficiency at the herd level most. Sensitivity analyses have contributed, therefore, to insight which parameters are to be investigated in more detail when applying LiGAPS-Beef. Model evaluation was conducted by comparing model simulations with independent data from experiments. Measured heat production in experiments corresponded fairly well to the heat production simulated with the thermoregulation sub-model. Measured ME contents from two data sets corresponded well to the ME contents simulated with the feed intake and digestion sub-model. The relative mean absolute errors were 9.3% and 6.4% of the measured ME contents for the two data sets. In conclusion, model evaluation indicates the thermoregulation sub-model can deal with a wide range of weather conditions, and the feed intake and digestion sub-model with a variety of feeds, which corresponds to the aim of LiGAPS-Beef to simulate cattle in different beef production systems across the world. [ABSTRACT FROM AUTHOR]

The expected increase in the global demand for livestock products calls for insight in the scope to increase actual production levels across the world. This insight can be obtained by using theoretical concepts of production ecology. These concepts distinguish three production levels for livestock: potential (i.e. theoretical maximum) production, which is defined by genotype and climate only; feed-limited production, which is limited by feed quantity and quality; and actual production. The difference between the potential or limited production and the actual production is the yield gap. The objective of this paper, the first in a series of three, is to present a mechanistic, dynamic model simulating potential and feed-limited production for beef cattle, which can be used to assess yield gaps. A novelty of this model, named LiGAPS-Beef (Livestock simulator for Generic analysis of Animal Production Systems – Beef cattle), is the identification of the defining factors (genotype and climate) and limiting factors (feed quality and available feed quantity) for cattle growth by integrating sub-models on thermoregulation, feed intake and digestion, and energy and protein utilisation. Growth of beef cattle is simulated at the animal and herd level. The model is designed to be applicable to different beef production systems across the world. Main model inputs are breed-specific parameters, daily weather data, information about housing, and data on feed quality and quantity. Main model outputs are live weight gain, feed intake and feed efficiency (FE) at the animal and herd level. Here, the model is presented, and its use is illustrated for Charolais and Brahman × Shorthorn cattle in France and Australia. Potential and feed-limited production were assessed successfully, and we show that FE of herds is highest for breeds most adapted to the local climate conditions. LiGAPS-Beef also identified the factors that define and limit growth and production of cattle. Hence, we argue the model has scope to be used as a tool for the assessment and analysis of yield gaps in beef production systems. [ABSTRACT FROM AUTHOR]

Mineral phosphorus (P) used to fertilise crops is derived from phosphate rock, which is a finite resource. Preventing and recycling mineral P waste in the food system, therefore, are essential to sustain future food security and long-term availability of mineral P. The aim of our modelling exercise was to assess the potential of preventing and recycling P waste in a food system, in order to reduce the dependency on phosphate rock. To this end, we modelled a hypothetical food system designed to produce sufficient food for a fixed population with a minimum input requirement of mineral P. This model included representative crop and animal production systems, and was parameterised using data from the Netherlands. We assumed no import or export of feed and food. We furthermore assumed small P soil losses and no net P accumulation in soils, which is typical for northwest European conditions. We first assessed the minimum P requirement in a baseline situation, that is 42% of crop waste is recycled, and humans derived 60% of their dietary protein from animals (PA). Results showed that about 60% of the P waste in this food system resulted from wasting P in human excreta. We subsequently evaluated P input for alternative situations to assess the (combined) effect of: (1) preventing waste of crop and animal products, (2) fully recycling waste of crop products, (3) fully recycling waste of animal products and (4) fully recycling human excreta and industrial processing water. Recycling of human excreta showed most potential to reduce P waste from the food system, followed by prevention and finally recycling of agricultural waste. Fully recycling P could reduce mineral P input by 90%. Finally, for each situation, we studied the impact of consumption of PA in the human diet from 0% to 80%. The optimal amount of animal protein in the diet depended on whether P waste from animal products was prevented or fully recycled: if it was, then a small amount of animal protein in the human diet resulted in the most sustainable use of P; but if it was not, then the most sustainable use of P would result from a complete absence of animal protein in the human diet. Our results apply to our hypothetical situation. The principles included in our model however, also hold for food systems with, for example, different climatic and soil conditions, farming practices, representative types of crops and animals and population densities. [ABSTRACT FROM AUTHOR]

Abstract: Soil organic matter (SOM) is an important resource base for arable farming. For policies on SOM to be effective, insight is needed on why and under which conditions farmers are willing to increase SOM content. This study used the theory of planned behaviour to analyse what prevents or encourages Dutch farmers to increase the SOM content of their fields. In an online survey, 435 arable farmers were asked questions to understand their attitude (perceived benefits), subjective norm (social pressure) and perceived behavioural control (anticipated impediments and obstacles) related to management of SOM. Farmers’ answers were related to their intention to increase SOM content, use of organic materials and perceived increase in SOM content. Our results showed that Dutch farmers are well aware of the possible benefits of SOM content for crop productivity. Farmers’ attitude, subjective norm and perceived decrease in SOM content were significantly related to their intention to increase SOM content. In our farm survey, this intention was very strong: 90% of the farmers stated a high or very high intention to increase the SOM content of their fields. A higher intention to increase SOM content was correlated with the use of organic materials as expressed as total and effective C (P = 0.003 and P = 0.002, respectively), but this did not lead to a perceived increase in SOM content. From a farmer's point of view, this indicates that increasing SOM content is to a large degree beyond their direct influence. The Dutch Manure and Fertiliser Act, costs of organic inputs and the need to cultivate profitable crops (such as potatoes or sugar beet) were indicated as important impeding factors for increasing SOM content. [ABSTRACT FROM AUTHOR]