The recent interest in multi-functional agricultural landscapes has not been matched with formal assessment of the roles that trees play across the spectrum of ecosystem services (ESs) provided in Sub-Saharan Africa (SSA). A structured literature review (1995-2014) assessed 350 journal articles about provision of one or more ESs by trees on farms and in agricultural landscapes in SSA. This revealed information on 15 ESs from studies in 23 countries covering arid (1% of studies), semi-arid (49%), sub-humid (26%) and humid (24%) agro-ecological zones. The majority of the studies reported provisioning (39%) and supporting (35%) followed by regulating (26%) ESs while studies on cultural services were scarce. Beneficial impacts of trees were dominating (58%), in particular in semi-arid zones where they were associated with enhancing water and nutrient cycling. A decline in some ESs was reported in 15% of the studies, while 28% found no effect of trees. Although the effects of trees were mainly positive, a decline in crop production was noted as a key trade-off against the provisions of ESs, such as modification of microclimate. This highlights the need to manage trade-offs among impacts of trees on ES provision to reduce competition and increase complementarity between trees and crops.
Data from about 4000 Sahiwal cows from eight large herds in Pakistan were used to study the influence of genetic and environmental factors on some milk production traits. First-lactation mean values were 1363 kg, 1395 kg and 252 days for milk yield up to 305 days after calving, total lactation yield and lactation length, respectively. Second and third lactation yields were proportionately 0-12 and 0-18 higher, respectively, at 305 days. The effect of herdyear at calving was by far the most important source of variation for all traits. Heritabilities estimated in uni-and trivariate analyses, using restricted maximum likelihood (REML) with an expectation maximization algorithm for an animal model, ranged from 0-14 to 0-17 for first-lactation traits. The estimates were generally lower for second lactation and higher for third lactation traits. Genetic correlation between lactations for the same trait were close to unity, whilst the phenotypic were considerably lower. Repeatabilities for milk yield traits were 0-42 and for lactation length 0-31. Genetic and phenotypic correlations between first-lactation 305-day milk yield and lactation length were 0-83 and 0-71, respectively. Genetic trends for all traits were close to zero but a substantial deterioration in performance, caused by negative environmental factors, was observed. Although the heritabilities were low, the prospects for genetic improvement are good, as indicated by a rather large additive genetic variation. A multivariate animal model, including the first three lactations of 305-day milk yield, was recommended for the most accurate prediction of breeding values for milk production.
We investigated differences between forage species with regard to micronutrients that are essential to sustain livestock health. Five grasses (timothy, perennial ryegrass, meadow fescue, tall fescue and cocksfoot), three legumes (red clover, white clover and birdsfoot trefoil) and four forbs (ribwort plantain, salad burnet, caraway and chicory) were grown on one micronutrient-poor/low pH soil and one micronutrient-rich/high pH soil (outdoor pot experiment). In addition, six grasses (timothy, perennial ryegrass, meadow fescue, tall fescue, Festulolium hybrid and cocksfoot) and one legume (red clover) were field-grown on the micronutrient-poor soil. Of the twelve pot-grown species, herbage of chicory, red clover and white clover generally had the highest micronutrient concentrations (maximum Co, Cu, Fe and Zn concentrations were 0Á23, 9Á8, 233 and 109 mg kg À1 DM, respectively), except for Mo, which was highest in the clovers (10Á6 mg kg À1 DM), and Mn, which was highest in cocksfoot (375 mg kg À1 DM). Soil type had the strongest effect on plant Mo and Mn concentrations. We also investigated differences in micronutrients between varieties, but they were generally few and negligible. The results indicate that choice of forage species is of major importance for micronutrient concentrations in herbage and that soil type exerts a major effect through pH. Forage of chicory, red clover and white clover generally met the requirements of high-yielding dairy cows with regard to most micronu-trients; therefore, diversification of seed mixtures so as to include these species could increase micronutrient concentrations in forage.
Yield estimates and yield gap analysis are important for identifying poor agricultural productivity. Remote sensing holds great promise for measuring yield and thus determining yield gaps. Farming systems in sub-Saharan Africa (SSA) are commonly characterized by small field size, intercropping, different crop species with similar phenologies, and sometimes high cloud frequency during the growing season, all of which pose real challenges to remote sensing. Here, an unmanned aerial vehicle (UAV) system based on a quadcopter equipped with two consumer-grade cameras was used for the delineation and classification of maize plants on smallholder farms in Ghana. Object-oriented image classification methods were applied to the imagery, combined with measures of image texture and intensity, hue, and saturation (IHS), in order to achieve delineation. It was found that the inclusion of a near-infrared (NIR) channel and red-green-blue (RGB) spectra, in combination with texture or IHS, increased the classification accuracy for both single and mosaic images to above 94%. Thus, the system proved suitable for delineating and classifying maize using RGB and NIR imagery and calculating the vegetation fraction, an important parameter in producing yield estimates for heterogeneous smallholder farming systems.
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