FIELD—A summary simulation model of the soil–crop system to analyse long-term resource interactions and use efficiencies at farm scale

Resources for crop production are often scarce in smallholder farming systems in the tropics, particularly in sub-Saharan Africa (SSA). Decisions on the allocation of such resources are often made at farm rather than at field plot scale. To handle the uncertainty caused by both lack of data and imperfect knowledge inherent to these agricultural systems, we developed a dynamic summary model of the soil–crop system that captures essential interactions determining the short- and long-term crop productivity, while keeping a degree of simplicity that allows its parameterisation, use and dissemination in the tropics. Generic, summary functions describing crop productivity may suffice for addressing questions concerning trade-offs on resource allocation at farm scale. Such functions can be derived from empirical (historical) data or, when they involve potential or water-limited crop yields, can be generated using process-based, detailed crop simulation models. This paper describes the approach to simulating crop productivity implemented in the model FIELD (Field-scale Interactions, use Efficiencies and Long-Term soil fertility Development), based on the availability of light, water, nitrogen, phosphorus and potassium, and the interactions between these factors. We describe how these interactions are simulated and use examples from case studies in African farming systems to illustrate the use of detailed crop models to generate summary functions and the ability of FIELD to capture long-term trends in soil C and crop yields, crop responses to applied nutrients across heterogeneous smallholder farms and the implications of overlooking the effects of intra-seasonal rainfall variability in the model. An example is presented that evaluates the sensitivity of the model to resource allocation decisions when operating (linked to livestock and household models) at farm scale. Further, we discuss the assessment of model performance, going beyond the calculation of simple statistics to compare simulated and observed results to include broader criteria such as model applicability. In data-scarce environments such as SSA, uncertainty in parameter values constrains the performance of detailed process-based models, often forcing model users to ‘guess’ (or set to default values) parameters that are seldom measured in practice. The choice of model depends on its suitability and appropriateness to analyse the relevant scale for the question addressed. Simpler yet dynamic models of the various subsystems (crop, soil, livestock, manure) may prove more robust than detailed, process-based models when analysing farm scale questions on system design and resource allocation in SSA.     

Nutrient use efficiencies and crop responses to N, P and manure applications in Zimbabwean soils: Exploring management strategies across soil fertility gradients

The spatial variability in crop yields commonly observed in smallholder farms of sub-Saharan Africa is often caused by gradients of declining soil fertility with increasing distance from the homestead. This heterogeneity means that recommendations based on regional soil surveys are of limited value. The variability in soil qualities within farms must be considered when designing management strategies, and their feasibility analysed by integrating results at the farm livelihood scale. For this purpose, we have developed the model FARMSIM, a dynamic bio-economic model for analysis and exploration of trade-offs in resource and labour allocation in heterogeneous smallholder farms. Focusing on farm-scale strategies, the approach to simulation of soil and crop processes in FARMSIM (the sub-model FIELD) is designed to be simple, but to keep the necessary degree of complexity to capture heterogeneity in resource use efficiencies. To test our approach, the sub-model FIELD was calibrated against chronosequences of woodland clearance in three agroecological zones of Zimbabwe (with soil textures of 3, 10, 35% clay), and used to simulate: (i) the creation of soil fertility gradients, and (ii) different strategies of N, P and manure applications to maize and soyabean rotations in homefields and outfields of smallholder farms on clayey and sandy soils. The results of the simulation of management strategies were tested against on-farm experimental data from Murewa, Zimbabwe. The model produced satisfactory predictions (r²: 0.6–0.9) of long-term changes in soil organic C, of crop responses to N and P and of nutrient use efficiencies across a wide range of yields and different field types. This demonstrated the broad applicability of the model despite the sparse data required for initialisation. However, the model results were less accurate in predicting crop responses to N and P applications in the outfields on sandy soils. Experimental evidence indicated yield limitation by Ca and Zn deficiencies in highly depleted outfields on sandy soils, which were not included mechanistically in the current version of FIELD. Repeated applications of 16 t ha⁻¹ year⁻¹ of manure allowed larger responses to applied N and P after 3 years of experimentation; such a corrective effect of manure was simulated to be due to improved N and P recovery efficiencies in the model. In combination with the experimental data, the simulation results suggested that soil fertility gradients affect nutrient use efficiencies, operating mostly on the efficiencies of nutrient capture rather than conversion. A typology of fields according to the type of management interventions needed is introduced, based on a generic application of FIELD with this parameterisation.     

Validation of the QTL on SSC4 for meat and carcass quality traits in a commercial crossbred pig population

Porcine chromosome 4 harbours many quantitative trait loci (QTL) affecting meat quality, fatness and carcass composition traits, detected in resource pig populations previously. However, prior to selection in commercial breeds, QTL identified in an intercross between divergent breeds require confirmation, so that they can be segregated. Consequently, the objective of this study was to validate several QTL on porcine chromosome 4 responsible for meat and carcass quality traits. The experimental population consisted of 14 crossbred paternal half-sib families. The region of investigation was the q arm of SSC4 flanked by the markers S0073 and S0813. Regression analysis resulted in the validation of three QTL within the interval: Minolta a * loin, back fat thickness and the weight of trimmed ham. The results were additionally confirmed by factor analysis. Candidate genes were proposed for meat colour, which was the most evident QTL validated in this study.     

Haemonchus spp. in sheep farmed under resource-poor conditions in South Africa--effect on haematocrit,conjunctival mucous membrane colour and body condition

A longitudinal study was conducted on the differential faecal egg counts, haematocrits and body condition scores of sheep belonging to resource-poor farmers at Rust de Winter, Gauteng province, and Kraaipan, North West Province, South Africa. The animals were scored for level of anaemia using the FAMACHA method, an assay for the clinical evaluation of anaemia caused by Haemonchus spp. Periods of higher Haemonchus egg counts occurred from October to March for sheep at Rust de Winter and from September/October to February or April for sheep at Kraaipan. Lower haematocrit values were registered during these periods as was a higher incidence of anaemic conjunctival mucous membrane colour scores compared to the period April to September. No clear relationship between the faecal egg counts and the body condition scores was evident. Although wider application of the FAMACHA system in sheep raised by resource-poor farmers should be investigated, the present study indicates that this method may certainly prove to be a valuable worm control strategy for such livestock owners.     

Effects of air temperature, air movement and artificial rain on the heat production of brushtail possums (Trichosurus vulpecula): an exploratory study

Two groups of six mature brushtail possums (Trichosurus vulpeculu) were housed in two respiration chambers, and their heat production, whole body conductance and lower critical temperatures were measured under a variety of simulated weather patterns. The possums were subjected to ambient temperatures of 30, 20 and 3 degrees C. At 20 and 3 degrees C, the animals were exposed to near still air and light winds (wind speed 0.8 and 6.7 km/h), both with, and without, simulated rain every 8 hours. The lower critical temperature in near still air lies between 7 and 10 degrees C. This temperature increases by about 2, 6 and 8 degrees C respectively for a wind velocity of 6.7 km/h, simulated rain and a combination of the two factors. Weather in New Zealand, especially in the cooler part of the year, will often produce conditions below the lower critical temperature of the thermoneutral zone of possums. This will necessitate significant increases in metabolic rate and hence food consumption or mobilisation of body fat reserves, which if not sustainable will result in the death of possums. Field studies have shown that this is often the case in the wild. It is proposed that this stress may be sufficient to decrease the resistance (especially cell-mediated immunity) of some possums and allow acceleration of the disease process in those infected with Mycobacterium bovis.     

Genetic parameters for carcass composition and pork quality estimated in a commercial production chain

Breeding goals in pigs are subject to change and are directed much more toward retail carcass yield and meat quality because of the high economic value of these traits. The objective of this study was to estimate genetic parameters of growth, carcass, and meat quality traits. Carcass components included ham and loin weights as primal cuts, which were further dissected into boneless subprimal cuts. Meat quality traits included pH, drip loss, purge, firmness, and color and marbling of both ham and loin. Phenotypic measurements were collected on a commercial crossbred pig population (n = 1,855). Genetic parameters were estimated using REML procedures applied to a bivariate animal model. Heritability estimates for carcass traits varied from 0.29 to 0.51, with 0.39 and 0.51 for the boneless subprimals of ham and loin, respectively. Heritability estimates for meat quality traits ranged from 0.08 to 0.28, with low estimates for the water holding capacity traits and higher values for the color traits: Minolta b*(0.14), L* (0.15), a* (0.24), and Japanese color scale (0.25). Heritability estimates differed for marbling of ham (0.14) and loin (0.31). Neither backfat nor ADG was correlated with loin depth (r(g) = 0.0), and their mutual genetic correlation was 0.27. Loin primal was moderately correlated with ham primal (r(g) = 0.31) and more strongly correlated with boneless ham (r(g) = 0.58). Backfat was negatively correlated with (sub)primal cut values. Average daily gain was unfavorably correlated with subprimals and with most meat quality characteristics measured. Genetic correlations among the color measurements and water-holding capacity traits were high (average r(g) = 0.70), except for Minolta a* (average r(g) = 0.17). The estimated genetic parameters indicate that meat quality and valuable cut yields can be improved by genetic selection. The estimated genetic parameters make it possible to predict the response to selection on performance, carcass, and meat quality traits and to design an effective breeding strategy fitting pricing systems based on retail carcass and quality characteristics.     

Stabilization of dissolved organic matter by aluminium: a toxic effect or stabilization through precipitation?

Carbon mineralization in acidic forest soils can be retarded by large concentrations of aluminium (Al). However, it is still unclear whether Al reduces C mineralization by direct toxicity to microorganisms or by decreased bioavailability of organic matter (OM) because dissolved organic matter (DOM) is precipitated by Al. We conducted an incubation experiment (6 weeks) with two DOM solutions (40 mg C litre^?1) derived from two acidic forests and possessing large differences in composition. Aluminium was added to the solutions in realistic ranges for acidic soils (1.6–24 mg Al litre^?1) at pHs of 3.8 and 4.5, to achieve differences in Al speciation. We determined different Al species, including the potentially toxic Al³⁺, by Diffusive Gradients in Thin Films (DGT) to evaluate toxic effects on microorganisms. Precipitation of OM increased with larger amounts of added Al and higher pH, and we measured a larger fraction of dissolved ‘free’ Al at pH 3.8 than at pH 4.5. Organic matter degradation decreased significantly with Al addition, and we found more organic matter degraded at pH 3.8 than at pH 4.5 for the respective Al additions. Consequently, the observed reduction in OM degradation (i.e. stabilization) cannot be explained by toxic effects of ‘free’ Al. However, C stabilization correlated significantly with C precipitation. The pH did not influence C stabilization directly, but determined the amount of C being precipitated. Phosphorus was removed along with OM by precipitation, which possibly also affected C stabilization. We conclude that C stabilization upon Al addition did not result from toxic effects, but was caused by reduced bioavailability of OM after its precipitation. The reduction in OM degradation by 65% is of great relevance for the overall C stabilization in acidic forest soils. Increasing pH and decreasing Al concentrations upon recovery from acidic deposition should therefore not result in decreased stabilization of precipitated OM.     

Closing the cassava yield gap: An analysis from smallholder farms in East Africa

Cassava yields in Africa are small and it remains unclear which factors most limit yields. Using a series of farm surveys and on-farm and on-station trials in Uganda and western Kenya, we evaluated the importance of abiotic, biotic and associated crop management constraints for cassava production in a range of socio-economic settings as found in smallholder farms in the region. Average yields under farmer management were 8.6 t ha⁻¹, but these were more than doubled to 20.8 t ha⁻¹ by using improved crop establishment, improved genotypes and 100–22–83 kg ha⁻¹ of single-nutrient N–P–K fertilizers. A farm survey revealed large yield differences between farms. Less endowed farmers harvested less cassava per unit area than better endowed farmers (difference of 5.9 and 9.7 t ha⁻¹ in Kenya and Uganda, respectively); differences were associated with less access to labour, poorer soils, and premature harvesting by less endowed farmers. Analysis of 99 on-farm and 6 on-station trials showed that constraints for cassava production varied strongly between sites and years. Poor soil fertility, early water stress and sub-optimal weed management limited cassava production by 6.7, 5.4 and 5.0 t ha⁻¹, respectively, when improved crop establishment and genotypes were used. Pests and diseases were relatively unimportant, while weed management was particularly important in farmer fields during a dry year in Kenya (yield gap of 11.6 t ha⁻¹). The use of complementary analytical tools such as multiple regression and boundary line analysis revealed that many fields were affected by multiple and interacting production constraints. These should be addressed simultaneously if significant productivity improvements are to be achieved. This will be more difficult for less endowed than for better endowed farm households, since the former lack social and financial capital to improve management.     

Resource flows,crops and soil fertility management in smallholder farming systems in semi‐arid Zimbabwe

Poor soil fertility and erratic rains are major constraints to crop production in semi‐arid environments. In the smallholder farming systems of sub‐Saharan Africa, these constraints are manifested in frequent crop failures and endemic food insecurity. We characterized a semi‐arid smallholder farming system in south‐western Zimbabwe to assess crop production, nutrient use and factors that constrain productivity. The farming system was studied using resource flow mapping, farmer interviews and calculations of crop production over three cropping seasons (2002/2003, 2003/2004 and 2004/2005) to capture variability between years. Farmers were categorized into three groups: better resourced, medium resourced and poorly resourced. Better resourced farmers produced adequate grain for basic household consumption, except in the drought year (2002/2003). Poorly resourced farmers had large grain deficits, whereas the medium resourced class had smaller deficits. Better resourced and medium resourced farmers produced adequate amounts of staple cereal in two of the seasons, while poorly resourced farmers produced inadequate amounts of food in all three seasons. All farmers produced less than 300 kg/ha of legumes per season. Lack of seed was cited as the main reason for poor legume production. Better resourced farmers used animal manure (2000–5000 kg per season) and some fertilizer on their cereal crops, while the medium resourced group used less manure (1000 kg or less) and no fertilizer. The use of manure varied strongly across the years. Poorly resourced farmers used no nutrient inputs on any of their crops. All groups had negative nitrogen balances during the three cropping seasons, although the values varied strongly between seasons. Investigation of the potential strategies for developing sustainable production systems are required to address the problems of food security in the semi‐arid parts of the country and the region.