Modeling responses of dryland spring triticale,proso millet and foxtail millet to initial soil water in the High Plains

Dryland farming strategies in the High Plains must make efficient use of limited and variable precipitation and stored water in the soil profile for stable and sustainable farm productivity. Current research efforts focus on replacing summer fallow in the region with more profitable and environmentally sustainable spring and summer crops. In the absence of reliable precipitation forecasts for the crop growing season, farmers rely mainly upon knowledge of plant available water (PAW) in the soil profile at planting for making crop choice decisions. To develop a decision support strategy for crop selection based on initial PAW, experiments were conducted with spring triticale (XTiticosecale Wittmack), proso millet (Panicum miliaceum L.), and foxtail millet (Setaria italica L. Beauv.) under artificially controlled Low, Medium, and High initial PAW levels during 2004 and 2005 at Akron, Colorado, and Sidney, Nebraska. The objectives of this study were to adapt an existing cropping systems model for the simulation of triticale and millet and to evaluate simulations from the adapted model by comparing results with field data collected under varying initial PAW conditions. The Root Zone Water Quality Model with DSSAT v4.0 crop growth modules (RZWQM2) was used. Specifically, the Cropping System Model (CSM)–CERES–Wheat module was adapted for simulating triticale, and CSM–CERES–Sorghum (v4.0) module was adapted for simulating proso millet and foxtail millet. Soil water, leaf area index, grain yield, and biomass data for the highest PAW treatment from one crop season for each of the three crops were used to adapt and calibrate the crop modules. The models were then evaluated with data from the remaining PAW treatments. The proso millet module was further tested with four years of data from a crop rotation experiment at Akron from 2003 to 2006. Simulation results indicated that the adapted and calibrated crop modules have the potential to simulate these new crops under a range of varying water availability conditions. Consequently, these models can aid in the development of decision support tools for the season-to-season management of these summer fallow replacement crops under dryland conditions in semi-arid environments.     

Measuring water stress in a wheat crop on a spatial scale using airborne thermal and multispectral imagery

A modified stress index is proposed that accounts for both chronic and acute water stress. Current trapezoid methods that use vegetation cover and temperature indices do not necessarily measure chronic conditions. The modified method describes the chronic stress as the ratio of actual crop cover to its potential expressed such that zero stress occurs when actual cover equals or exceeds the potential as determined by a simulation model. The advantage of such a definition is that in areas where full groundcover is rarely achieved, such as semi-arid regions, a more realistic and conservative stress condition will be observed. Airborne thermal and multispectral images were acquired at four growth stages of a wheat crop from a site in Victoria, Australia with experimental plots having rain-fed and irrigated regimes over two seasons (2005 and 2006). The theoretical basis of vector determination was adopted for trapezoidal extent per season. The relationship between such chronic stress and acute stress is explored and show that in any 2 years large differences between these stresses exist.     

Multivariate global sensitivity analysis for dynamic crop models

Dynamic crop models are frequently used in ecology, agronomy and environmental sciences for simulating crop and environmental variables at a discrete time step. They often include a large number of parameters whose values are uncertain, and it is often impossible to estimate all these parameters accurately. A common practice consists in selecting a subset of parameters by global sensitivity analysis, estimating the selected parameters from data, and setting the others to some nominal values. For a discrete-time model, global sensitivity analyses can be applied sequentially at each simulation date. In the case of dynamic crop models, simulations are usually computed at a daily time step and the sequential implementation of global sensitivity analysis at each simulation date can result in several hundreds of sensitivity indices, with one index per parameter per simulation date. It is not easy to identify the most important parameters based on such a large number of values. In this paper, an alternative method called multivariate global sensitivity analysis was investigated. More precisely, the purposes of this paper are (i) to compare the sensitivity indices and associated parameter rankings computed by the sequential and the multivariate global sensitivity analyses, (ii) to assess the value of multivariate sensitivity analysis for selecting the model parameters to estimate from data. Sequential and multivariate sensitivity analyses were compared by using two dynamic models: a model simulating wheat biomass named WWDM and a model simulating N₂O gaseous emission in crop fields named CERES-EGC. N₂O measurements collected in several experimental plots were used to evaluate how parameter selection based on multivariate sensitivity analysis can improve the CERES-EGC predictions.The results showed that sequential and multivariate sensitivity analyses provide modellers with different types of information for models which exhibit a high variability of sensitivity index values over time. Conversely, when the parameter influence is quite constant over time, the two methods give more similar results. The results also showed that the estimation of the parameters with the highest sensitivity indices led to a strong reduction of the prediction errors of the model CERES-EGC.     

An empirical statistical model for predicting the yield of herbage from legume-grass swards within organic crop rotations based on cumulative water balances

Multi-species legume-grass swards play a key role in organic farming systems as a source of forage and of symbiotically fixed nitrogen (N). Forage and N balances, based on site-specific data on dry matter (DM) yields of herbage, are useful planning tools in describing forage and N supply at the field and farm level. In practice, measurements of DM yield are often imprecise or missing, and thus a weather- and site-specific assessment of DM yield is required. An empirical model to predict DM yield from legume-grass swards was developed based on weather and soil data commonly available at field and regional scales. The main underlying hypothesis was that water use, calculated from cumulative water balances, can be used as a predictor of DM yield. The model was calibrated with data from a multi-year field experiment in Müncheberg, north-east Germany and was tested with data from other countries of Europe. In the calibration data set, highly significant linear relationships were found between water use and DM yield for DM yield of single harvests and for annual DM yield. The only additional variable significantly improving the prediction of DM yield was cut number. For the validation data set the DM yield for single cuts and annual yields was predicted with a similar accuracy as found with other models requiring the use of more information. The models described offer a straightforward weather- and site-specific means of predicting DM yield with a satisfactory level of precision, especially for annual DM yields, and thus can help to reduce planning failures concerning forage and N supply in organic farming systems in Europe.     

宁夏春小麦对气候变化情景的响应模拟

应用DSSAT35作物模型中的CERES-Wheat模型,在Baseline年(1961-1990)及构建的2011-2100年A2(CO2约1%的高排放)和B2(CO2约0.5%的低排放)气候情景下,对宁夏春小麦品种永良4号在宁夏25 km×25 km黄河灌区的59个格点进行模拟试验,模拟对比了100年的潜在产量、生育期、蒸散量、灌溉累积量的变化.结果表明,在Baseline(基准年)气候情景下,59个格点的平均潜在产量为6 234 kg/ha,A2、B2情景下模拟潜在产量与Baseline相比均为减产趋势,A2情景下减产率比B2情景下的大;开花期到生理成熟期的生育期天数为24～25 d,A2、B2情景下开花期和生理成熟期分别比Baseline明显提前;与Baseline比较,生育期内总蒸散量增加幅度不大;A2、B2情景下,整个季节内平均灌水量比Baseline仅少1～6 mm.     

Conservation agriculture and smallholder farming in Africa: The heretics’ view

Conservation agriculture is claimed to be a panacea for the problems of poor agricultural productivity and soil degradation in sub-Saharan Africa (SSA). It is actively promoted by international research and development organisations, with such strong advocacy that critical debate is stifled. Claims for the potential of CA in Africa are based on widespread adoption in the Americas, where the effects of tillage were replaced by heavy dependence on herbicides and fertilizers. CA is said to increase yields, to reduce labour requirements, improve soil fertility and reduce erosion. Yet empirical evidence is not clear and consistent on many of these points nor is it always clear which of the principles of CA contribute to the desired effects. Although cases can be found where such claims are supported there are equally convincing scientific reports that contradict these claims. Concerns include decreased yields often observed with CA, increased labour requirements when herbicides are not used, an important gender shift of the labour burden to women and a lack of mulch due to poor productivity and due to the priority given to feeding of livestock with crop residues. Despite the publicity claiming widespread adoption of CA, the available evidence suggests virtually no uptake of CA in most SSA countries, with only small groups of adopters in South Africa, Ghana and Zambia. We conclude that there is an urgent need for critical assessment under which ecological and socio-economic conditions CA is best suited for smallholder farming in SSA. Critical constraints to adoption appear to be competing uses for crop residues, increased labour demand for weeding, and lack of access to, and use of external inputs.     

Grain yield increase in cereal variety mixtures: A meta-analysis of field trials

Plant ecology theory predicts that growing seed mixtures of varieties (variety mixtures) may increase grain yields compared to the average of component varieties in pure stands. Published results from field trials of cereal variety mixtures demonstrate, however, both positive and negative effects on grain yield. To investigate the prevalence and preconditions for positive mixing effects, reported grain yields of variety mixtures and pure variety stands were obtained from previously published variety trials, converted into relative mixing effects and combined using meta-analysis. Furthermore, available information on varieties, mixtures and growing conditions was used as independent variables in a series of meta-regressions. Twenty-six published studies, examining a total of 246 instances of variety mixtures of wheat (Triticum aestivum L.) and barley (Hordeum vulgare L.), were identified as meeting the criteria for inclusion in the meta-analysis; on the other hand, nearly 200 studies were discarded. The accepted studies reported results on both winter and spring types of each crop species. Relative mixing effects ranged from −30% to 100% with an overall meta-estimate of at least 2.7% (p < 0.001), reconfirming the potential of overall grain yield increase when growing varieties in mixtures. The mixing effect varied between crop types, with largest and significant effects for winter wheat and spring barley. The meta-regression demonstrated that mixing effect increased significantly with (1) diversity in reported grain yields, (2) diversity in disease resistance, and (3) diversity in weed suppressiveness, all among component varieties. Relative mixing effect was also found to increase significantly with the effective number of component varieties. The effects of the latter two differed significantly between crop types. All analyzed models had large unexplained variation between mixing effects, indicating that the variables retrievable from the published studies explained only a minority of the differences among mixtures and trials.     

Variation in Granule Bound Starch Synthase I (GBSSI) loci amongst Australian wild cereal relatives (Poaceae)

A complex cascade of enzymes is responsible for the development of starch granules in grain endosperm. Granule Bound Starch Synthase I (GBSSI), encoded by the Waxy gene, is a key enzyme of starch synthesis and determines the accumulation of amylose in the starch granules. The complete genomic GBSSI sequence was ascertained for eight Australian cereal wild relatives (CWR) to determine diversity within the gene. A phylogeny derived from the coding sequence of the entire Waxy gene was compared to established phylogenetic relationships. Starch granule morphology observed in conjunction with this phylogeny suggests that small polygonal starch granules arranged as compound granules are the ancestral state, evolving subsequently to bimodal starch granules and to larger simple granules. Genomic sequence length varied within the species from 2800 to 3572 bp. Most variation occurred within the intron sequences, the largest insertion showing strong homology to a retrotransposon. One wild species was determined to have a deletion in the 3′-end of exon 1 resulting in a putatively non-functional allele. Alignment of the amino acid sequence showed strong homology throughout the central fragments of the gene but broad variation in the transit peptides. All putative functional alleles maintained the reported active sites for glycogen synthesis, though with variations in other highly conserved areas of the gene. These variations within the wild relatives of cultivated cereals may provide novel sources of genetic diversity for future cereal improvement programs.     

Amaranth (Amaranthus hypochondriacus) as an alternative crop for sustainable food production: Phenolic acids and flavonoids with potential impact on its nutraceutical quality

The demand for food is increasing, not only to meet food security for growing populations, but also to provide more nutritious food, rich in good quality proteins and nutraceutical compounds. The amaranth (Amaranthus hypochondriacus) plant, in addition to its high nutritive and nutraceutical characteristics, has excellent agronomic features. The objective of the present study was to analyze some physical and proximal-nutritional properties of amaranth seeds obtained from different varieties grown in arid zones and characterize their phenolic acids and flavonoids. Two commercial (Tulyehualco and Nutrisol) and two new (DGETA and Gabriela) varieties of A. hypochondriacus were grown at the Mexican Highlands zone. Tulyehualco and DGETA varieties had higher seed yield of 1475 and 1422 kg ha⁻¹, respectively, comparable to corn and soybean production in agricultural areas. Gabriela had the highest protein content of 17.3%, but all varieties had an adequate balance of essential amino acids. Polyphenols as rutin (4.0–10.2 μg g⁻¹ flour) and nicotiflorin (7.2–4.8 μg g⁻¹ flour) were detected. Amaranth can be cultivated in arid zones where commercial crops cannot be grown; the seeds besides their well known nutritive characteristics could be a source of phenolic compounds of high antioxidant properties.     

The current and future potential distribution of Cytisus scoparius: a weed of pastoral systems, natural ecosystems and plantation forestry

Cytisus scoparius is a serious weed of pastoral systems, natural ecosystems and plantation forestry, which has become invasive in a number of countries. CLIMEX™ was used to infer the climatic requirements of C. scoparius from its native range, as well as its current range as an exotic in the United States and New Zealand. The parameterised model was used to examine the invasive potential of C. scoparius under current and future climatic conditions, assuming a range of climate-change scenarios. The modelled global potential distribution of C. scoparius compared favourably with the known distributions, in both the fitted and validation dataset, encompassing almost all temperate and Mediterranean regions. The predicted distribution also included most sub-tropical regions and extended into continental areas in North America and Europe and savanna regions in Africa. Under current climate, the projected potential distribution exceeded the known distribution. Places most at risk from range expansion include China, Australia, Argentina and North America, as C. scoparius is already present, but has not yet colonised all areas with apparently high climatic suitability. Climate change is likely to lead to a poleward shift in the range of C. scoparius and a contraction of areas of suitable climate for the species in southern Europe, central Africa, Australia, China, Brazil and the southern United States. With climate change, currently uncolonised areas within northern Scandinavia, southern Canada and western regions of the Russian Federation are projected to become climatically suitable.