The performances of two remote sensing drought indices were evaluated at selected agricultural sites in different agro-climatic zones in Iran to detect the severity of drought phenomena related to temporal variation and different climatic conditions. The indices used were the perpendicular drought index (PDI) and the modified perpendicular drought index (MPDI), which are derived from moderate resolution imaging spectroradiometer (MODIS) satellite images (MOD13A3 V005). The correlations between these perpendicular indices and two other remote sensing indices in ten different agro-climatic zones of Iran from February 2000 to December 2005 were analysed. The additional indices evaluated were the enhanced vegetation index (EVI) and the vegetation condition index (VCI) along with five water balance parameters, including climatic water balance (CL), crop water balance (CR), monthly reference crop evapotranspiration (ET0), crop evapotranspiration (ETc) and required irrigation water (I). Winter wheat was selected as the reference crop because it is grown in the majority of climatic conditions in Iran.

The results show that in several climatic regions, there is a statistically significant correlation between PDI and MPDI and the water balance parameters, indicating an acceptable performance in detecting crop drought stress conditions. In all zones except at the sites located in northwest and northeast of Iran, VCI and EVI are less correlated with the applied water balance indicators compared to PDI and MPDI. In a temporal analysis, PDI and MPDI showed a greater ability to detect CR conditions than VCI and EVI in the most drought-sensitive winter wheat-growing stages. Since Iran is characterized by arid or semi-arid climatic conditions and winter wheat is a major agricultural crop, a combination of both PDI and MPDI could be used as simple remote sensing-based tool to map drought conditions for crops in Iran and in other developing countries with similar climatic conditions.

Information on the performance of the Rothamsted organic carbon turnover model (RothC model) in predicting changes in soil organic carbon (SOC) in short-term experiments is scarce. In Mexico, it was found that these experiments covered not more than 20 years. The purpose of the present study was to evaluate short-term SOC prediction performance of the RothC model in the following systems: (1) farming with residues added (A+R), (2) farming with no added residues (A−R), (3) pure forest stands (F), (4) grasslands (GR) and (5) rangeland (RL). Work was done in five experimental sites: Atécuaro, Michoacán; Santiago Tlalpan, Tlaxcala; El Batán, State of Mexico; Sierra Norte, Oaxaca; and Linares, Nuevo León. Carbon (C) inputs to the soil were plant residues and organic fertilizers, which need to be known to operate the RothC model. The adjustment coefficients for site modelling had R2 values of 0·77–0·95 and model efficiency (EF) was −0·60 to 0·93. When RothC performance was evaluated by a system, R2 values were 0·06–0·92 and EF was −0·24 to 0·90. The low R2 and EF values in rangelands were attributed to the fact that these systems are complex because of heterogeneous vegetation, soil and climate. In general, the evaluation of the RothC model indicates that it can be useful in simulating SOC changes in temperate and warm climate sites and in farming, forest and grassland systems in Mexico.

Global changes including increases in temperature, atmospheric greenhouse gases, soil degradation and competition for land and water resources, will have multiple impacts on rice production systems in Africa. These changes will affect weed communities, and management approaches must be adapted to take this into account. Higher temperatures and limited water availability will generally advantage C4 over C3 plants (e.g. rice). Conversely, elevated carbon dioxide (CO2) levels will improve the competitiveness of rice relative to C4 weeds, which comprise many of the problem weeds of rice. Increased atmospheric CO2 levels may also improve tolerance of rice against parasitic weeds, while prevalence of parasitic species may be amplified by soil degradation and more frequent droughts or floods. Elevated CO2 levels tend to promote growth below-ground relative to above-ground, particularly in perennial (C3) species. This may render mechanical control of weeds within a cropping season less effective or even counterproductive. Increased CO2 levels, rainfall and temperature may also reduce the effectiveness of chemical control, while the implementation of adaptation technologies, such as water-saving irrigation regimes, will have negative consequences for rice–weed competition. Rain-fed production systems are prevalent throughout Africa and these are likely to be most vulnerable to direct effects of climate change (e.g. higher temperatures and changes in rainfall patterns). Effective weed management strategies in these environments could encompass off-season tillage, the use of well-adapted cultivars (i.e. those with drought and heat tolerance, high weed competitiveness and parasitic weed resistance or tolerance) and rotations, intercropping or short, off-season fallows with weed-suppressive legumes including those that suppress parasitic weeds. In irrigated, non-flooded rice systems, weeds are expected to become more serious. Specifically, perennial rhizomatous C3 weeds and species adapted to hydromorphic conditions are expected to increase in prevalence. By implementing an integrated weed management strategy primarily targeted at weed prevention, dependency on flood water, herbicides and mechanical control can be lessened. Off-season deep tillage, stale seed bed techniques, use of clean seeds and irrigation water, competitive cultivars, timely transplanting at optimum spacing and judicious fertilizer timings are suitable candidate components for such a strategy. Integrated, novel approaches must be developed to assist farmers in coping with the challenges of weed control in the future.

The present paper provides a geographically scaled analysis of adaptation to climate change using adoption of agricultural systems observed across Africa. Using c. 9000 farm surveys, spatial logit models were applied to explain observed agricultural system choices by climate variables after accounting for soils, geography and other household characteristics. The results reveal that strong neighbourhood effects exist and a spatial re-sampling and bootstrapping approach can remove them. The crops-only system is adopted most frequently in the lowland humid forest, lowland sub-humid, mid-elevation sub-humid Agro-Ecological Zones (AEZs) and in the highlands in the east and in southern Africa. Integrated farming is favoured in the lowland dry savannah, moist savannah and semi-arid zones in West Africa and eastern coastal zones. A livestock-only system is favoured most in the mid/high-elevation moist savannahs located in southern Africa. Under a hot and dry Canadian Climate Centre (CCC) scenario, the crops-only system should move out from the currently favoured regions of humid zones in the lowlands towards the mid-/high elevations. It declines by more than 5% in the lowland savannahs. Integrated farming should increase across all the AEZs by as much as 5%, but less so in the deserts or in the humid forest zones in the mid-/high elevations. A livestock-only system should increase by 2–5% in the lowland semi-arid, dry savannah and moist savannah zones in the lowlands. Adaptation measures should be carefully scaled, up or down, considering geographic and ecological differentials as well as household characteristics, as proposed in the present study.

Characterization of plant varieties is traditionally based on phenotypic observation. However, some varieties have very similar morphological characteristics, which make it difficult to distinguish between them. The present study employed 15 microsatellite markers distributed across all linkage groups (LG) of the chickpea genetic map to characterize 32 commercial chickpea cultivars and determine the usefulness of these markers for cultivar identification. These markers showed a high level of polymorphism; a total of 154 different alleles were detected, with a mean of 10·3 alleles per locus. The polymorphic information content (PIC) value ranged from 0·455 to 0·897. All the markers, with the exception of TA130, TA135 and TA144, were considered to be informative (PIC>0·7), indicating their potential usefulness for cultivar identification. A subset of markers (TA186, TA200, TA106, TA113, TA117 and TA30) was sufficient to identify all the cultivars studied. In order to confirm their discriminatory power, 16 unreleased chickpea cultivars (V1–V16) were screened and all of them presented different patterns. Therefore, these microsatellites can be regarded as a reference set for chickpea cultivar identification and their profiles can be used as a DNA fingerprint for each registered cultivar, avoiding redundancy of identical cultivars as well as to protect breeders' rights.

The application of organic composts to soil may affect the availability of micronutrients and their concentration in plants. The present field research study compared soil micronutrient extractability after 5 years of organic fertilization v. conventional inorganic fertilization. Iron (Fe), copper (Cu), manganese (Mn) and zinc (Zn) were extracted from soil using diethylene triamine pentaacetic acid (DTPA) and the data obtained were compared with the concentration of these micronutrients in the edible portion of the crop. The study was carried out on a loam soil classified as a Xerofluvent. The soil was fertilized with composted plant residues or with conventional inorganic fertilizer and all treatments were replicated four times in a randomized complete block design. In all cases a crop rotational system was applied. The use of organic fertilization resulted in a higher extractability for all the elements studied; however, the micronutrient content in the edible part of the crops was variable depending on the plant species and element. Crop yields depended on the type of crop rather than the type of soil fertilization. The present study showed that the use of plant compost and the elimination of synthetic fertilizers result in an increase of Fe, Cu, Mn and Zn extractability compared to soil treated with inorganic fertilization, which should provide long-term fertility benefits.

Accurate field data on the paddock area affected by cow urine depositions are critical to the estimation and modelling of nitrogen (N) losses and N management in grazed pasture systems. A new technique using survey-grade global positioning system (GPS) technology was developed to precisely measure the paddock spatial area coverage, diversity and distribution of dairy cattle urine patches in grazed paddocks over time. A 4-year study was conducted on the Lincoln University Dairy Farm (LUDF), Canterbury, New Zealand, from 2003 to 2007. Twelve field plots, each 100 m2 in area, were established on typical grazing areas of the farm. All urine and dung deposits within the plots were visually identified, the pasture response area (radius) measured and position marked with survey-grade GPS. The plots were grazed as part of the normal grazing rotation of the farm and urine and dung deposits measured at 12-week intervals. The data were collated using spatial (GIS) software and an assessment of annual urine patch coverage and spatial distribution was made. Grazing intensities ranged from 17 645 to 30 295 cow grazing h/ha/yr. Mean annual areas of urine patches ranged from 0·34 to 0·40 m2 (4-year mean 0·37±0·009 m2), with small but significant variation between years and seasons. Mean annual urine patch numbers were 6240±124 patches/ha/yr. The mean proportional area coverage for a single sampling event or season was 0·058 and the mean proportional annual urine patch coverage was 0·232±0·0071. There was a strong linear relationship between annual cow grazing h/ha and urine patch numbers/ha (R2=0·69) and also annual urine patch area coverage (R2=0·77). Within the stocking densities observed in this study, an annual increase of 10 000 cow grazing h/ha increased urine patch numbers by 1800 urine patches/ha/yr and annual urine patch area coverage by 0·07. This study presents new quantitative data on urine patch size, numbers and the spatial coverage of patches on a temporal basis.

Simplified cultivation technologies for rice have become increasingly attractive in recent years in China because of their social, economical and environmental benefits. To date, several simplified cultivation technologies, such as conventional tillage and seedling throwing (CTST), conventional tillage and direct seeding (CTDS), no-tillage and seedling throwing (NTST), no-tillage and direct seeding (NTDS) and no-tillage and transplanting (NTTP), have been developed in China. Most studies have shown that rice grown under each of these simplified cultivation technologies can produce a grain yield equal to or higher than traditional cultivation (conventional tillage and transplanting). Studies that have described the influences of agronomic practices on yield formation of rice under simplified cultivation have demonstrated that optimizing agronomy practices would increase the efficiencies of simplified cultivation systems. Further research is needed to optimize the management strategies for CTST, CTDS and NTST rice which have developed quickly in recent years, to strengthen basic research for those simplified cultivation technologies that are rarely used at present (such as NTTP and NTDS), to select and breed cultivars suitable for simplified cultivation and to compare the practicability and effectiveness of different simplified cultivation technologies in different rice production regions.

Cotton is the dominant crop in the northern Xinjiang oasis of China; it accounts for 0·78 of the total planting area and represents a major contribution to economic development. The objective of the present study is to determine how cotton plantation age affected chemical and microbiological properties of the soil. The time substitution method was used on plantation farmlands, reclaimed from uncultivated land 0, 5, 10, 15 and 20 years ago. A total of 250 soil samples, at depths of 0–200, 200–400, 400–600, 600–800 and 800–1000 mm, were collected from cotton fields in 10 farms of each age category. There were significant differences in soil organic carbon (SOC), total soil nitrogen (TSN), soil available nitrogen (SAN), soil microbial biomass carbon (SMBC) and soil microbial biomass nitrogen (SMBN). There were also differences in the activities of cellulase, invertase and urease between soil layers and plantation ages, and these were most evident in the 200–400 mm layer. The cumulative rates of SOC and SMBC in the 0–1000 mm soil layer at the 5-, 10-, 15- and 20-year sites were 0·89, 0·99, 1·01 and 0·92 mg/kg/yr and 16, 16, 16 and 15 mg/kg/yr, respectively, compared to that at the control site (0 year). The cumulative amounts of SOC and SMBC increased gradually and then decreased, reaching a maximum at plantation ages of 13·1 years and 11·1 years, respectively. This suggests that incorporation of post-harvest cotton residues could be used as an effective measure to improve SOC in farmland of Xinjiang Oasis, and may be recommended for adoption in cotton growing in semi-arid oasis agriculture.

The UK dairy sector has undergone considerable structural change in recent years, with a decrease in the number of producers accompanied by an increased average herd size and increased concentrate use and milk yields. One of the key drivers to producers remaining in the industry is the profitability of their herds. The current paper adopts a holistic approach to decomposing the variation in dairy profitability through an analysis of net margin data explained by physical input–output measures, milk price variation, labour utilization and managerial behaviours and characteristics. Data are drawn from the Farm Business Survey (FBS) for England in 2007/08 for 228 dairy enterprises. Average yields are 7100 litres/cow/yr, from a herd size of 110 cows that use 0·56 forage ha/cow/yr and 43·2 labour h/cow/yr. An average milk price of 22·57 pence per litre (ppl) produced milk output of £1602/cow/yr, which after accounting for calf sales, herd replacements and quota leasing costs, gave an average dairy output of £1516/cow/yr. After total costs of £1464/cow/yr this left an economic return of £52/cow/yr (0·73 ppl) net margin profit. There is wide variation in performance, with the most profitable (as measured by net margin per cow) quartile of producers achieving 2000 litres/cow/yr more than the least profitable quartile, returning a net margin of £335/cow/yr compared to a loss of £361/cow/yr for the least profitable. The most profitable producers operate larger, higher yielding herds and achieve a greater milk price for their output. In addition, a significantly greater number of the most profitable producers undertake financial benchmarking within their businesses and operate specialist dairy farms. When examining the full data set, the most profitable enterprises included significantly greater numbers of organic producers. The most profitable tend to have a greater reliance on independent technical advice, but this finding is not statistically significant. Decomposing the variation in net margin performance between the most and least profitable groups, an approximate ratio of 65:23:12 is observed for higher yields: lower costs: higher milk price. This result indicates that yield differentials are the key performance driver in dairy profitability. Lower costs per cow are dominated by the significantly lower cost of farmer and spouse labour per cow of the most profitable group, flowing directly from the upper quartile expending 37·7 labour h/cow/yr in comparison with 58·8 h/cow/yr for the lower quartile. The upper quartile's greater milk price is argued to be achieved through contract negotiations and higher milk quality, and this accounts for 0·12 of the variation in net margin performance. The average economic return to the sample of dairy enterprises in this survey year was less than £6000/farm/yr. However, the most profitable quartile returned an average economic return of approximately £50 000 per farm/yr. Structural change in the UK dairy sector is likely to continue with the least profitable and typically smaller dairy enterprises being replaced by a smaller number of expanding dairy production units.

Ten Polwarth×Texel lambs (26±2·1 kg live weight (LW)), housed in metabolism cages and offered ryegrass (Lolium multiflorum) ad libitum, were used in a 5×5 Latin Square experiment to evaluate the effect of supplement type on digestion processes and on amino acid and energy supplies. Five of the 10 lambs were fitted with a rumen catheter and duodenal cannulae. Treatments included no supplement (control); 7 g/kg LW daily of cassava meal (Manihot esculenta, high-starch low-nitrogen (HS-LN)), cassava meal plus corn gluten meal (2:1, high-starch high-undegradable N (HS-UN)), cassava meal plus calcium caseinate (2·8:1, high-starch high-degradable N (HS-DN)) or corn gluten feed (low-starch high-degradable N (LS-DN)). Total intake of dry matter (DM), organic matter (OM) and N, as well as digestible OM intake were increased with HS-UN, HS-DN and LS-DN (P⩽0·050). Forage DM intake was reduced by HS-LN (P=0·030). Apparent digestibility of DM and OM was increased by HS-LN and HS-DN (P⩽0·038). Digestibility of neutral detergent fibre (NDF) and OM true digestibility were similar for all treatments. Supplementation with HS-LN decreased duodenal flux of total N, amino acid N, ammonia N and feed residual N (P⩽0·023). None of the supplements affected rumen microbial protein entering the small intestine, whereas the efficiency of rumen microbial protein synthesis (EMPS) was reduced by HS-LN and HS-DN (P⩽0·036). Ruminal degradability of dietary N (RDN) was increased by HS-LN, HS-DN and LS-DN (P⩽0·050). In conclusion, supplementing lambs fed ryegrass with degradable or undegradable high-protein concentrate increased the amino acid supply without affecting the supply of digestible energy, regardless of either the starch content or the degree of ruminal degradability of the protein source. These results indicate that supplementation of ryegrass-based diets should include both starch and protein sources.

The coding region of the alpaca Agouti signalling protein (ASIP) gene was sequenced. It was determined to be 402 nucleotides long and code for a protein that is 133 amino acids long. Eight mutations were identified in a sample of 15 alpaca, five in the coding region and three in the introns flanking the exons. In silico analysis showed that three of the five mutations in the coding sequence, c.325_381del57, c.292C>T and c.353G>A are probable loss-of-function mutations. The three mutations were strongly associated with black fibre colour, with 0·90 of black alpacas in the current study having two copies of one or another of the mutations. However, not all black animals displayed the putative ‘aa’ genotype, and almost half of the non-black animals did display that genotype. Contributing factors such as regulatory region mutations, interactions of ASIP with melanocortin-1 receptor (MC1R) and α-melanocyte stimulating hormone (α-MSH), the effect of dilution genes and subjective phenotype assignment are discussed. These mutations will allow alpaca breeders to select for or against black, but they do not explain all black phenotypes in this species.