Multi-site time-trend analysis of soil fertility management effects on crop production in sub-Saharan West Africa

Soil fertility constraints to crop production have been recognized widely as a major obstacle to food security and agro-ecosystem sustainability in sub-Saharan West Africa. As such, they have led to a multitude of research projects and policy debates on how best they should be overcome. Conclusions, based on long-term multi-site experiments, are lacking with respect to a regional assessment of phosphorus and nitrogen fertilizer effects, surface mulched crop residues, and legume rotations on total dry matter of cereals in this region. A mixed model time-trend analysis was used to investigate the effects of four nitrogen (0, 50, 90 or 150 kg/ha) and phosphorus (no fertilizer, 13 kg/ha single superphosphate, 39 kg/ha Tahouca rock phosphate, an additional annual placement of rock phosphate at 4 kg/ha, and as NPK) rates, annually applied crop residue dry matter at 500 and 2000 kg ha-1, and cereal-legume rotation versus continuous cereal cropping on the total dry matter of cereals and legumes. The multi-factorial experiment was conducted over four years (1995-98) at eight locations (Banizoumbou, Sadore, Kara Bedji, Goberi, Gaya, Fada-Kouare, Koukombo and Kaboli), with annual rainfall ranging from 510 to 1300 mm, in Niger, Burkina Faso, and Togo. With the exception of phosphorus, treatment effects on legume growth were marginal. At most locations, except for typical Sudanian sites with very low base saturation and high rainfall, phosphorus effects on cereal total dry matter were much lower with rock phosphate than with soluble phosphorus, unless the rock phosphate was combined with an annual seed-placement of 4 kg ha-1 phosphorus. Across all other treatments, nitrogen effects were negligible at 500 mm annual rainfall but at 900 mm, the highest nitrogen rate led to total dry matter increases of up to 77% and, at 1300 mm, to 183%. Mulch-induced increases in cereal total dry matter were larger with lower base saturation, reaching 45% on typical acid sandy Sahelian soils. Legume rotation effects tended to increase over time but were strongly species-dependen

The effects of cropping sequence, fertilization, and straw management on the yield stability of winter wheat (1986–2017) in the Broadbalk Wheat Experiment, Rothamsted, UK.

The development of resilient cropping systems with high yield stability is becoming increasingly important due to future climatic and agronomic challenges. Consequently, it is essential to be able to evaluate the effects of differing agronomic management practices, such as cropping sequences, and nutrient supply on the stability of crop yields. Long-term experiments are a valuable resource for investigating these effects, providing a sufficient number of years for accurate stability parameter estimation. The objective of the current study was to evaluate the effects of cropping sequence (#1: continuous vs rotational), fertilization (#2: mineral vs organic) and straw management in the case of continuous wheat (#3: removal vs incorporation) on the yield stability of winter wheat; yield risk (the probability of yield falling below a threshold yield level) and inter-annual yield variability were used as stability indicators of the effects. Long-term yield data from the Broadbalk Wheat Experiment (Rothamsted, United Kingdom) were analysed using a mixed model. Overall, the results showed that rotational cropping combined with supply of sufficient nutrients (N, P, and K) from mineral fertilizers, especially mineral N supply, ensured stable wheat yields whilst reducing the yield risk

Getting the Most Out of Sorghum Low-Input Field Trials in West Africa Using Spatial Adjustment

Breeding sorghum for low-input conditions is hindered by soil heterogeneity. Spatial adjustment using mixed models can help account for this variation and increase precision of low-input field trials. Large small-scale spatial variation (CV 39.4 %) for plant available phosphorus was mapped in an intensely sampled low-input field. Spatial adjustments were shown to account for residual yield differences because of this and other growth factors. To investigate the potential of such models to increase the efficiency of low- and high-input field trials, 17 experiments with 70 sorghum genotypes conducted in Mali, West Africa, were analysed for grain yield using different mixed models including models with autoregressive spatial correlation terms. Spatial models (AR1, AR2) improved broad sense heritability estimates for grain yield, averaging gains of 10 and 6 % points relative to randomized complete block (RCB) and lattice models, respectively. The heritability estimate gains were even higher under low phosphorus conditions and in two-replicate analyses. No specific model was best for all environments. A single spatial model, AR1 × AR1, captured most of the gains for heritability and relative efficiency provided by the best model identified for each environment using Akaike's Information Criterion. Spatial modelling resulted in important changes in genotype ranking for grain yield. Thus, the use of spatial models was shown to have potentially important consequences for aiding effective sorghum selection in West Africa, particularly under low-input conditions and for trials with fewer replications. Thus, using spatial models can improve the resource allocation of a breeding program. Furthermore, our results show that good experimental design with optimal placement and orientation of blocks is essential for efficient statistical analysis with or without spatial adjustment

Nonparametric Resampling Methods for Testing Multiplicative Terms in AMMI and GGE Models for Multienvironment Trials

The additive main effects and multiplicative interaction (AMMI) and genotype and genotype 'environment interaction (GGE) models have been extensively used for the analysis of genotype 'environment experiments in plant breeding and variety testing. Since their introduction, several tests have been proposed for testing the significance of the multiplicative terms, including a parametric bootstrap procedure. However, all of these tests are based on the assumptions of normality and homogeneity variance of the errors. In this paper, we propose tests based on nonparametric bootstrap and permutation methods. The proposed tests do not require any strong distributional assumptions. We also propose a test that can handle heterogeneity of variance between environments. The robustness of the proposed tests is compared with the robustness of other competing tests. The simulation study shows that the proposed tests always perform better than the parametric bootstrap method when the distributional assumptions of normality and homogeneity of variance are violated. The stratified permutation test can be recommended in case of heterogeneity of variance between environments

How rainfall variation influences reproductive patterns of African Savanna ungulates in an equatorial region where photoperiod variation is absent.

In high temperate latitudes, ungulates generally give birth within a narrow time window when conditions are optimal for offspring survival in spring or early summer, and use changing photoperiod to time conceptions so as to anticipate these conditions. However, in low tropical latitudes day length variation is minimal, and rainfall variation makes the seasonal cycle less predictable. Nevertheless, several ungulate species retain narrow birth peaks under such conditions, while others show births spread quite widely through the year. We investigated how within-year and between-year variation in rainfall influenced the reproductive timing of four ungulate species showing these contrasting patterns in the Masai Mara region of Kenya. All four species exhibited birth peaks during the putative optimal period in the early wet season. For hartebeest and impala, the birth peak was diffuse and offspring were born throughout the year. In contrast, topi and warthog showed a narrow seasonal concentration of births, with conceptions suppressed once monthly rainfall fell below a threshold level. High rainfall in the previous season and high early rains in the current year enhanced survival into the juvenile stage for all the species except impala. Our findings reveal how rainfall variation affecting grass growth and hence herbivore nutrition can govern the reproductive phenology of ungulates in tropical latitudes where day length variation is minimal. The underlying mechanism seems to be the suppression of conceptions once nutritional gains become insufficient. Through responding proximally to within-year variation in rainfall, tropical savanna ungulates are less likely to be affected adversely by the consequences of global warming for vegetation phenology than northern ungulates showing more rigid photoperiodic control over reproductive timing

Modellbasierte Analyse des Stoffumsatzes von Mageren Flachland-Mähwiesen in Baden-Württemberg im Critical-Loads-Konzept

Critical Loads für eutrophierenden Stickstoff werden anhand der Simple-Mass-Balance (SMB) Methode berechnet und dienen etwa in FFH-Verträglichkeitsprüfungen dem Schutz empfindlicher Ökosysteme (Anhang I FFH-Richtlinie). Die auf Basis der SMB ermittelten standortspezifischen Spannen für Critical Loads sind auf Grund von Unsicherheiten sowohl in den Eingangsgrößen als auch in den empirisch regelbasierten Methoden zur Berechnung der einzelnen Summanden in der SMB wenig vertrauenswürdig. Im Rahmen des von der Landesanstalt für Umwelt, Messungen und Naturschutz Baden-Württemberg (LUBW) koordinierten Forschungsprojektes „Analyse und Bewertung des Stickstoffhaushalts Baden-Württemberg (AG Critical Loads)“ soll deshalb die Schaffung einer Datenbasis für eine Weiterentwicklung der bisherigen Ansätze für den in Baden-Württemberg weit verbreiteten FFH-Lebensraumtyp 6510 „Magere Flachland-Mähwiesen“ erfolgen. Einen möglichen Weg hin zu belastbaren Abschätzverfahren für die Summanden der SMB-Formel stellen dynamische Simulationen der am N-Umsatz beteiligten Stoffflüsse mit Hilfe prozessbasierter Modelle dar. Ziel der vorgestellten Studie ist es, mit Hilfe des Modellpakets Expert-N standortspezifisch für ausgewählte Flachland-Mähwiesen die mehrjährigen Mittelwerte der Mineralisierung, Denitrifikation, Immobilisierung und Nitratauswaschung zu berechnen. Als experimentelle Datengrundlage für die Modellierung werden Feldmessungen zur Abschätzung des N-Umsatzes in Abhängigkeit von Standortbedingungen und Erhaltungszustand der Vegetation durchgeführt. Dazu wird auf 4 extensiv genutzten Grünlandflächen in FFH-Gebieten über 2 Jahre ein intensives Monitoring der Stickstoffflüsse im Boden sowie begleitende Messungen zur Bodenfeuchte, -temperatur und N-Deposition durchgeführt. Der Fokus liegt auf der in situ Quantifizierung der Bruttoraten des N-Umsatzes (Mineralisierung, Nitrifizierung) als wichtige Parameter für die Modellierung des N-Kreislaufs. Die aus der prozessbasierten Modellierung gewonnenen Mittelwerte werden mit den nach den derzeitigen SMB-Ansatz berechneten Ergebnissen verglichen und diskutiert. Die Ergebnisse der Studie werden so zur Entwicklung zuverlässigerer Berechnungsmethoden für Critical Loads in Baden-Württemberg beitragen. Auf dem Poster werden die methodischen Ansätze sowie erste Ergebnisse des Versuchs vorgestellt

High-throughput field phenotyping reveals genetic variation in photosynthetic traits in durum wheat under drought

Chlorophyll fluorescence (ChlF) is a powerful non-invasive technique for probing photosynthesis. Although proposed as a method for drought tolerance screening, ChlF has not yet been fully adopted in physiological breeding, mainly due to limitations in high-throughput field phenotyping capabilities. The light-induced fluorescence transient (LIFT) sensor has recently been shown to reliably provide active ChlF data for rapid and remote characterisation of plant photosynthetic performance. We used the LIFT sensor to quantify photosynthesis traits across time in a large panel of durum wheat genotypes subjected to a progressive drought in replicated field trials over two growing seasons. The photosynthetic performance was measured at the canopy level by means of the operating efficiency of Photosystem II ((Formula presented.)) and the kinetics of electron transport measured by reoxidation rates ((Formula presented.) and (Formula presented.)). Short- and long-term changes in ChlF traits were found in response to soil water availability and due to interactions with weather fluctuations. In mild drought, (Formula presented.) and (Formula presented.) were little affected, while (Formula presented.) was consistently accelerated in water-limited compared to well-watered plants, increasingly so with rising vapour pressure deficit. This high-throughput approach allowed assessment of the native genetic diversity in ChlF traits while considering the diurnal dynamics of photosynthesis

Selection Strategy for Sorghum Targeting Phosphorus-limited Environments in West Africa: Analysis of Multi-environment Experiments

Although sorghum [Sorghum bicolor (L.) Moench] in West Africa (WA) is generally cultivated with limited or no fertilization on soils of low phosphorus availability, no assessments of the genetic variation among WA sorghum varieties for adaptation to low soil P are known. We assessed grain yields of 70 diverse sorghum genotypes under −P (no P fertilization) and +P conditions at two locations in Mali over 5 yr. Genetic variation for grain yield under −P conditions and the feasibility and necessity of sorghum varietal testing for grain yield under −P conditions were evaluated. Delayed heading dates (0–9.8 d) and reductions of grain yield (2–59%) and plant height (13–107 cm) were observed in −P relative to the +P trials. High estimates of genetic variance and broad-sense heritabilities were found for grain yield across both −P (h2 = 0.93) and +P (h2 = 0.92) environments. The genetic correlation for grain yield performance between −P and +P conditions was high (rG = 0.89), suggesting that WA sorghum varieties generally possess good adaptation to low-P conditions. However, genotype × phosphorus crossover interaction was observed between some of the highest yielding genotypes from the −P and +P selected sets, with the variety IS 15401 showing specific adaptation to −P. Direct selection for grain yield in −P conditions was predicted to be 12% more efficient than indirect selection in +P conditions. Thus, selection under −P conditions should be useful for sorghum improvement in WA

Gene and QTL detection in a three-way barley cross under selection by a mixed model with kinship information using SNPs

Quantitative trait locus (QTL) detection is commonly performed by analysis of designed segregating populations derived from two inbred parental lines, where absence of selection, mutation and genetic drift is assumed. Even for designed populations, selection cannot always be avoided, with as consequence varying correlation between genotypes instead of uniform correlation. Akin to linkage disequilibrium mapping, ignoring this type of genetic relatedness will increase the rate of false-positives. In this paper, we advocate using mixed models including genetic relatedness, or ‘kinship’ information for QTL detection in populations where selection forces operated. We demonstrate our case with a three-way barley cross, designed to segregate for dwarfing, vernalization and spike morphology genes, in which selection occurred. The population of 161 inbred lines was screened with 1,536 single nucleotide polymorphisms (SNPs), and used for gene and QTL detection. The coefficient of coancestry matrix was estimated based on the SNPs and imposed to structure the distribution of random genotypic effects. The model incorporating kinship, coancestry, information was consistently superior to the one without kinship (according to the Akaike information criterion). We show, for three traits, that ignoring the coancestry information results in an unrealistically high number of marker–trait associations, without providing clear conclusions about QTL locations. We used a number of widely recognized dwarfing and vernalization genes known to segregate in the studied population as landmarks or references to assess the agreement of the mapping results with a priori candidate gene expectations. Additional QTLs to the major genes were detected for all traits as well