Meta-analysis of crop responses to conservation agriculture in sub-Saharan Africa

Conservation agriculture involves reduced or no-tillage, permanent soil cover and crop rotations to enhance soil fertility and crop yields. Conservation agriculture practices are increasingly promoted on smallholder farms in sub-Saharan Africa as a means to overcome continuing poor-profitability and soil degradation. In recent years a growing number of studies have been carried out in sub-Saharan Africa comparing conservation agriculture practices to conventional tillage-based practices. These studies have been conducted under a range of conditions (climate, soil, management, cropping system) gaining variable results on crop yield responses. The aim of this study is to compare and combine the results from different conservation agriculture experiments using meta-analysis in the hope of identifying patterns among study results, sources of disagreement among those results, or interesting relationships that may come to light in the context of the different studies

Crop type identification and spatial mapping using Sentinel-2 satellite data with focus on field-level information

Accurate monitoring of croplands helps in making decisions (for insurance claims, crop management and contingency plans) at the macro-level, especially in drylands where variability in cropping is very high owing to erratic weather conditions. Dryland cereals and grain legumes are key to ensuring the food and nutritional security of a large number of vulnerable populations living in the drylands. Reliable information on area cultivated to such crops forms part of the national accounting of food production and supply in many Asian countries, many of which are employing remote sensing tools to improve the accuracy of assessments of cultivated areas. This paper assesses the capabilities and limitations of mapping cultivated areas in the Rabi (winter) season and corresponding cropping patterns in three districts characterized by small-plot agriculture. The study used Sentinel-2 Normalized Difference Vegetation Index (NDVI) 15-day time-series at 10m resolution by employing a Spectral Matching Technique (SMT) approach. The use of SMT is based on the well-studied relationship between temporal NDVI signatures and crop phenology. The rabi season in India, dominated by non-rainy days, is best suited for the application of this method, as persistent cloud cover will hamper the availability of images necessary to generate clearly differentiating temporal signatures. Our study showed that the temporal signatures of wheat, chickpea and mustard are easily distinguishable, enabling an overall accuracy of 84%, with wheat and mustard achieving 86% and 94% accuracies, respectively. The most significant misclassifications were in irrigated areas for mustard and wheat, in small-plot mustard fields covered by trees and in fragmented chickpea areas. A comparison of district-wise national crop statistics and those obtained from this study revealed a correlation of 96%

Understanding the response of sorghum cultivars to nitrogen applications in the semi-arid Nigeria using the agricultural production systems simulator

The Agricultural Production Systems simulator (APSIM) model was calibrated and evaluated using two improved sorghum varieties conducted in an experiment designed in a randomized complete block, 2014–2016 at two research stations in Nigeria. The results show that the model replicated the observed yield accounting for yield differences and variations in phenological development between the two sorghum cultivars. For early-maturing cultivar (ICSV-400), the model indicated by low accuracy with root means square error (RMSE) for biomass and grain yields of 20.3% and 23.7%. Meanwhile, Improved-Deko (medium-maturing) cultivar shows the model was calibrated with low RMSE (11.1% for biomass and 13.9% for grain). Also, the model captured yield response to varying Nitrogen (N) fertilizer applications in the three agroecological zones simulated. The N-fertilizer increased simulated grain yield by 26–52% for ICSV-400 and 19–50% for Improved-Deko compared to unfertilized treatment in Sudano-Sahelian zone. The insignificant yield differences between N-fertilizer rates of 60 and 100 kgha−1 suggests 60 kgNha−1 as the optimal rate for Sudano-Sahelian zone. Similarly, grain yield increased by 23–57% for ICSV-400 and 19–59% for Improved Deko compared to unfertilized N-treatment while the optimal mean grain yield was simulated at 80 kgNha−1 in the Sudan savanna zone. In the northern Guinea savanna, mean simulated grain yield increased by 8–20% for ICSV-400 and 12–23% for Improved-Deko when N-fertilizer was applied compared to unfertilized treatment. Optimum grain yield was obtained at 40 kgha−1. Our study suggests a review of blanket recommended fertilizer rates across semi-arid environments for sorghum to maximize productivity and eliminate fertilizer losses, means of adaptation strategies to climate variability

Cross-kingdom signalling regulates spore germination in the moss <i>Physcomitrella patens</i>

Plants live in close association with microorganisms that can have beneficial or detrimental effects. The activity of bacteria in association with flowering plants has been extensively analysed. Bacteria use quorum-sensing as a way of monitoring their population density and interacting with their environment. A key group of quorum sensing molecules in Gram-negative bacteria are the N-acylhomoserine lactones (AHLs), which are known to affect the growth and development of both flowering plants, including crops, and marine algae. Thus, AHLs have potentially important roles in agriculture and aquaculture. Nothing is known about the effects of AHLs on the earliest-diverging land plants, thus the evolution of AHL-mediated bacterial-plant/algal interactions is unknown. In this paper, we show that AHLs can affect spore germination in a representative of the earliest plants on land, the Bryophyte moss Physcomitrella patens. Furthermore, we demonstrate that sporophytes of some wild isolates of Physcomitrella patens are associated with AHL-producing bacteria

Estimating organic surface horizon depth for peat and peaty soils across a Scottish upland catchment using linear mixed models with topographic and geological covariates

In order to evaluate and protect ecosystem services provided by peat and peaty soils, accurate estimations for the depth of the surface organic horizon are required. This study uses linear mixed models (LMMs) to test how topographic (elevation, slope, aspect) and superficial geology parameters can contribute to improved depth estimates across a Scottish upland catchment. Mean (n = 5) depth data from 283 sites (representing full covariate ranges) were used to calibrate LMMs, which were tested against a validation dataset. Models were estimated using maximum likelihood, and the Akaike Information Criterion was used to test whether the iterative addition of covariates to a model with constant fixed effects was beneficial. Elevation, slope and certain geology classes were all identified as useful covariates. Upon addition of the random effects (i.e. spatial modelling of residuals), the RMSE for the model with constant‐only fixed effects reduced by 24%. Addition of random effects to a model with topographic covariates (fixed effects = constant, slope, elevation) reduced the RMSE by 13%, whereas the addition of random effects to a model with topographic and geological covariates (fixed effects = constant, slope, elevation, certain geology classes) reduced the RMSE by only 3%. Therefore, much of the spatial pattern in depth was explained by the fixed effects in the latter model. The study contributes to a growing research base demonstrating that widely available topographic (and also here geological) datasets, which have national coverage, can be included in spatial models to improve organic horizon depth estimations

Differentiated function and localisation of SPO11-1 and PRD3 on the chromosome axis during meiotic DSB formation in Arabidopsis thaliana

During meiosis, DNA double-strand breaks (DSBs) occur throughout the genome, a subset of which are repaired to form reciprocal crossovers between chromosomes. Crossovers are essential to ensure balanced chromosome segregation and to create new combinations of genetic variation. Meiotic DSBs are formed by a topoisomerase-VI-like complex, containing catalytic (e.g. SPO11) proteins and auxiliary (e.g. PRD3) proteins. Meiotic DSBs are formed in chromatin loops tethered to a linear chromosome axis, but the interrelationship between DSB-promoting factors and the axis is not fully understood. Here, we study the localisation of SPO11-1 and PRD3 during meiosis, and investigate their respective functions in relation to the chromosome axis. Using immunocytogenetics, we observed that the localisation of SPO11-1 overlaps relatively weakly with the chromosome axis and RAD51, a marker of meiotic DSBs, and that SPO11-1 recruitment to chromatin is genetically independent of the axis. In contrast, PRD3 localisation correlates more strongly with RAD51 and the chromosome axis. This indicates that PRD3 likely forms a functional link between SPO11-1 and the chromosome axis to promote meiotic DSB formation. We also uncovered a new function of SPO11-1 in the nucleation of the synaptonemal complex protein ZYP1. We demonstrate that chromosome co-alignment associated with ZYP1 deposition can occur in the absence of DSBs, and is dependent on SPO11-1, but not PRD3. Lastly, we show that the progression of meiosis is influenced by the presence of aberrant chromosomal connections, but not by the absence of DSBs or synapsis. Altogether, our study provides mechanistic insights into the control of meiotic DSB formation and reveals diverse functional interactions between SPO11-1, PRD3 and the chromosome axis

A watershed approach to managing rainfed agriculture in the semiarid region of southern Mali: integrated research on water and land use

Soil and water conservation (SWC) practices like that of erosion control and soil fertility measures were commonly practiced in the semiarid region of southern Mali since the 1980s. The SWC practices were mainly meant to increase water availability in the subsurface, reduce farm water runoff and gully formation and improve nutrient content of the soil, thereby increasing crop yield. Despite such efforts to promote at scale SWC practices, the landscape of southern Mali is still affected by high rates of runoff and soil erosion and low crop yield in farmers’ fields. Data are lacking on previous beneficial SWC practices that could be adapted for wider application. In this paper, a watershed approach to managing rainfed agriculture is presented to show potential benefits of SWC practices at field and watershed scales. The approach included (1) community participation in establishing and monitoring new sets of hydro-meteorological monitoring stations and field experiments; (2) studying the dynamics and consumptive water uses of different land uses over time; and (3) evaluating the biophysical and economic advantages of SWC practices implemented in the watershed. Results showed that over a period of 34 years (1980–2014) cropping area and consumptive water uses of crops (sorghum and cotton) increased at the expenses of natural vegetation. However, the yield of these crops remained low, indicating that soil fertility management and soil moisture were insufficient. In such cases, implementation of more SWC practices can help provide the additional soil moisture required

Evaluation of the onset and length of growing season to define planting date - ‘a case study for Mali (West Africa)’

The agroecological zones (AEZ) of Mali fall within the semi-arid climate, the ability to determine efficiently or predict accurately the onset of growing season (OGS), and length of growing season (LGS) cannot be over-emphasized due to highly variable rainfall pattern and the dependence of smallholder farmers practising on rainfed farming agriculture. In this study, we determined the most suitable method for predicting the onset date of rainfall across AEZ that fitted with the planting windows of major cereal crops (maize, millet, and sorghum). Using long-term daily rainfall records from 22 meteorological stations spread across AEZ of Mali, four (4) known methods were applied to determine the onset dates of the rain. The mean onset dates were statistically compared with the farmer’s planting window for the selected weather stations to determine the suitable dates of OGS and LGS. The hypothesis considered a time lag minimum of 7 days between the mean onset date and traditional farmer sowing dates for the crops. Then, the preferred method was used to estimate OGS based on early, normal and late dates respectively across the stations. Also, the estimated LGS according to each zone was evaluated using probability distribution chart with duration to maturity for varieties of the same crops. The results showed that Def_4 was found appropriate for Sahelian and Sudano-Sahelian zones; Def_3 satisfied the criteria and exhibited superior capacity into farmer’s average planting date over Sudanian and Guinea Savannah zones. These results have an important application in cropping systems in order to prevent crop failure and ensure a better choice of crop variety according to LGS under climate variability and change being experienced across Mali

Quantifying Farm Household Resilience and the Implications of Livelihood Heterogeneity in the Semi-Arid Tropics of India

The vast majority of farmers in the drylands are resource-poor smallholders, whose livelihoods depend heavily on their farming systems. Therefore, increasing the resilience of these smallholders is vital for their prosperity. This study quantified household resilience and identified livelihoods and their influence on resilience in the semiarid tropics of India by analysing 684 households. A resilience capacity index was devised based on the composition of household food and non-food expenditure, cash savings, and food and feed reserves. The index ranged from 8.4 reflecting highly resilient households with access to irrigation characteristics, to -3.7 for households with highly limited resilience and low household assets. The livelihoods were identified through multivariate analysis on selected socioeconomic and biophysical variables; households were heterogeneous in their livelihoods. Irrigated livestock and rainfed marginal types had the highest and lowest resilience capacity index with the mean score of 0.69 and −1.07, respectively. Finally, we quantified the influence of livelihood strategies on household resilience. Household resilience was strengthened by the possession of livestock, crop diversification and access to irrigation. Low resilience is predominantly caused by low household assets. The resilience capacity index and derived livelihood strategies helps to understand the complexity of household resilience, and will aid in targeting technology interventions for development

Calibration and Validation of APSIM-Sorghum (Sorghum Bicolor (L.) Moench) for Simulating Growth and Yield in Contrasting Environments in Nigeria

In Semi-arid Nigeria, sorghum production is regarded as a major cereal for food grain and fodder, predominantly grown under rainfed conditions. With demand for sorghum outweighing its current production. there is a need to exploer a wide range of sorghums adopted to contrasting production environments