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Future crop breeding needs to consider future soils
Full text linkComment Section
Modern crop breeding and seed certification agencies ignore the known spatial heterogeneity of soils and develop cultivars to thrive in a ‘one-size-fits-all’ soil environment. Neglecting the evolving dynamics of soils substantially undermines the capacity of new genotypes to deliver optimal yield and stress resilience, and requires urgent consideration in future plant breeding programmes
Putting numbers to a metaphor: A Bayesian Belief Network with which to infer Soil Quality and Health
Full text linkSoil Quality or Soil Health are terms adopted by the scientific community as metaphors for the effects of differingland management practices on the properties and functions of soil. Because they are metaphors, consistent
quantitative definitions are lacking. We present here an approach based on expert elicitation in the field of soil
function and management that offers a universal way of putting numbers to the metaphor. Like humans, soils differ and so do the ways in which they are understood to become unhealthy. Long-term experiments such as the Broadbalk Wheat experiment at Rothamsted provide unparalled sources of data with which to investigate the state and changes of soil quality and health that have developed from known management over timescales of one hundred years or more. Similarly, large-scale datasets such as the National Soils Inventory and Countryside Survey provide rich resources to explore the geographical variability of soil quality and health in different places against a background of different observed management practices. We structure experts’ views of the extent to which soil delivers the functions expected of it within Bayesian Belief Networks anchored by measurable
properties of soil. With these networks, we infer the likely state of soil (i) on Broadbalk, (ii) at locations throughout England & Wales as well as inferring (iii) the most straightforward ways of improving soil quality and health at the locations in (ii). Our methodology has general applicability and could be deployed elsewhere or in other discipline
Carbon inventories: New opportunities and challenges for agriculture and forestry
No full textCarbon balance (carbon sequestration and greenhouse gas emissions) in natural and agroecosystems is a pivotal theme in important initiatives focused on reducing anthropogenic impacts on the environment (e.g., Paris Agreement, REDD+, initiative “4 per 1000″, Sustainable Development Goals). However, taking carbon balance of global progress towards achieving such initiatives requires consistently measuring aggregate national actions (Gidden et al., 2023). In this special issue (SI) entitled “Carbon inventories: new opportunities and challenges for agriculture and forestry”, we sought high quality manuscripts that encompass major scientific challenges and advances aiming to achieve feasible and accurate carbon inventories improvements in agriculture and forestry..
Differentially spliced mitochondrial CYP419A1 contributes to ethiprole resistance in Nilaparvata lugens
Full text linkThe brown planthopper Nilaparvata lugens is one of the most economically important pests of cultivated rice in Southeast Asia. Extensive use of insecticide treatments, such as imidacloprid, fipronil and ethiprole, has resulted in the emergence of multiple resistant strains of N. lugens. Previous investigation of the mechanisms of resistance to imidacloprid and ethiprole demonstrated that overexpression and qualitative changes in the cytochrome P450 gene CYP6ER1 lead to enhanced metabolic detoxification of these compounds. Here, we present the identification of a secondary mechanism enhancing ethiprole resistance mediated by differential splicing and overexpression of CYP419A1, a planthopper-specific, mitochondrial P450 gene. Although metabolic resistance to insecticides is usually mediated by overexpression of P450 genes belonging to either CYP 3 or 4 clades, we validate the protective effect of over-expression of CYP419A1, in vivo, using transgenic Drosophila melanogaster. Additionally, we report some unusual features of both the CYP419A1 gene locus and protein, which include, altered splicing associated with resistance, a non-canonical heme-binding motif and an extreme 5’ end extension of the open reading frame. These results provide insight into the molecular mechanisms underpinning resistance to insecticides and have applied implications for the control of a highly damaging crop pest
Building a Near-infrared (NIR) Soil Spectral Dataset and Predictive Machine Learning Models using a Handheld NIR Spectrophotometer
Full text linkThis near-infrared spectral dataset consists of 2,106 diverse mineral soil samples scanned, on average, on six different units of the same low-cost commercially available handheld
spectrophotometer. Most soil samples were selected from the USDA NRCS National Soil Survey Center-Kellogg Soil Survey Laboratory (NSSC-KSSL) soil archives to represent the diversity of mineral soils (0-30 cm) found in the United States, while 90 samples were selected from Ghana, Kenya, and
Nigeria to represent available African soils in the same archive. All scanning was performed on dried and sieved (<2 mm) soil samples. Machine learning predictive models were developed for soil organic carbon (SOC), pH, bulk density (BD), carbonate (CaCO3), exchangeable potassium (Ex. K),
sand, silt, and clay content from their spectra in the R programming language using most of this dataset (1,976 US soils) and are included in this data release. Two model types, Cubist and partial least squares regression (PLSR) were developed using two strategies: (1) using an average of the spectral scans across devices for each sample and, (2) using the replicate spectral scans across devices for each sample. We present the internal performance of these models here. The dry spectra and Cubist models for these soil properties are available for download from 10.5281/zenodo.7586621. An example of detailed code used to produce these models is hosted at the Open Soil Spectral Library, a free service of the Soil Spectroscopy for the Global Good Network (soilspectroscopy.org), enabling broad use of these data for multiple soil monitoring applications
Achieving net-zero agriculture in Africa: perspective on policies, challenges, and opportunities
Full text linkAfrica, with 55 Member States and over 1 billion people, is projected to nearly double its population to 2.5 billion by 2050, presenting both opportunities and challenges for sustainable development. Agriculture employs 65% of the labour force and contributes 32% to gross domestic product. The aim of this perspective is to highlight the challenges and opportunities of achieving net-zero agriculture in Africa while proffering appropriate recommendations. The primary issues are how extreme weather events affect food security and how to cut emissions from livestock farming as well as rice cultivation and fertilizer usage alongside evaluating current policies that support climate-smart agricultural practices. Africa needs to investigate how its expanding young population along with research and innovation can advance the move towards net-zero agricultural practices. Challenges of insufficient data availability together with ineffective policy enforcement, financial barriers, and limited awareness, decreasing precipitation levels coupled with regional conflicts and population migration hinder progress in achieving net-zero agriculture on the continent. However, Africa possesses substantial opportunities through its extensive arable land combined with its youthful workforce and renewable energy capabilities. Africa needs to obtain climate funds and strengthen regional partnerships while enhancing climate information services and creating inclusive and gender-responsive policies to address these issues. Investing in innovative technologies alongside renewable energy sources and crops resistant to climate change stands as an essential strategy. The implementation of early warning systems along with the development of alternative livelihoods will enhance efforts towards sustainable management of climate-induced migration. Africa will develop a climate-resilient agricultural system by confronting existing challenges while capitalizing on emerging opportunities
Field plants strategically regulate water uptake from different soil depths by spatiotemporally adjusting their radial root hydraulic conductivity
No full textPlants modify their root hydraulics to maintain water status and strategically use soil water, but how they achieve this in the field remains elusive.
We developed a method to measure and calculate daily water uptake, water potential and radial hydraulic permeability of roots at different depths in wheat and permanent grass fields.
During drying processes, both plant systems decreased the radial hydraulic permeability of their shallow roots to reduce water uptake from the topsoil, while increasing the radial hydraulic permeability of their deep roots to boost water uptake from the subsoil. Conversely, after the topsoil was rewetted, both plant systems instantly increased the radial hydraulic permeability of their shallow roots to enhance water uptake from the topsoil whereas decreasing the radial hydraulic permeability of their deep roots to reduce water extraction from the subsoil.
We found water uptake of deep roots was influenced by topsoil water more than by subsoil water, and thus the topsoil water serves not only as a resource but also as a cue coordinating optimal use of soil water in different depths. These findings have important implications for improving our understanding of the mechanisms plants use to cope with periodic water stress and screening drought-tolerant varieties
Fitting and comparing water retention curves for soils under contrasting experimental treatment: Examples from conservation agriculture trials in southern Africa
No full textConservation Agriculture (CA) is proposed as a ‘climate-smart’ intervention for resilient crop production in dryland areas affected by climate change. Evidence is needed for how these practices affect fundamental properties of the soil. The soil water retention curve (SWRC) is a physical attribute of the soil which provides information on its porous structure and physical quality. It is also critical for modelling processes in the soil such as water movement, water availability for plants and infiltration into the soil during rainfall events. In this paper we estimate parameters of the van Genuchten model of the SWRC from experiments on CA interventions in southern Africa, using a linear mixed modelling framework. The method we use, stochastic approximation maximization, allows for maximum likelihood estimation of the parameters without use of linearizing approximation. We show how sequential fitting of model parameters, with marginal false discovery rate control, allows us to make robust inferences about differences in the SWRC between soils under contrasting experimental management. We also show how the method allows us to draw samples from distribution of SWRC parameters, reflecting the uncertainty which arises from variation within the management treatments. Indices of soil physical quality may be computed from the parameter estimates to compare treatments, and by computing them from the samples, the uncertainty in these indices can also be assessed. We use the estimated model parameters to simulate infiltration of water into the soils under different management during a rainfall event. Again, by using the samples from the joint distributions of the parameters the effects of uncertainty in these parameters as propagated through the model can be computed. We applied these methods to soils collected from experimental plots under CA and conventional tillage (CV) at sites in Zimbabwe, Zambia and Malawi. We observed differences in the SWRC for the CA and CV plots at the Zambian site where a physically vulnerable soil showed greater macroporosity under CA than CV. In contrast, a sandy and organic-poor soil at the site in Zimbabwe showed somewhat greater macroporosity under cultivation rather than CA management. There was no detectable treatment effect of the management system on the SWRC for the soils at the site in Malawi
Evaluating the effects of montmorillonite amendments on quinoa growth, water flow, and solute transport in sandy loam and loam soils
No full textClay nanoparticles (NPs) are recognized as natural soil amendments. However, the effects of different types of clay NPs and their application rates on the physical, chemical, and biological characteristics of soils, solute transport, and plant photosynthesis parameters have not been thoroughly investigated. This study focused on amending two soil textures—sandy loam and loam—by adding 3% nano clay. The original and amended soils were packed into soil columns to conduct cultivation experiments with quinoa (Chenopodium quinoa Willd) plants and displacement solute transport experiments. The goal of column experiments was to explore the impact of the nano clay amendment on the photosynthetic properties of quinoa plants and solute transport in soils. The results indicated that adding NPs to loam soil improved photosynthesis and stomatal conductance. Additionally, the introduction of nano clays reduced sub-stomatal CO2 levels in the amended soils compared to the control soils. In sandy loam soil, both with and without cultivation, the addition of nano clay enhanced saturated hydraulic conductivity, dispersivity, and maximum chloride concentration when compared to the control. However, it also resulted in a decrease in immobile water content and a reduction in peak travel time. In loam soil, the application of nano clay—regardless of cultivation method—increased dispersivity and immobile water contents while reducing maximum chloride concentration. It simultaneously decreased hydraulic conductivity compared to control conditions and also increased it in some instances. This research demonstrates that the nano clay amendment significantly alters soil's physical and chemical properties, affecting solute transport and the photosynthetic parameters of the quinoa cultiva
Flame-Retardant Properties of a Styrene-Vinyl Tetrazole Copolymer Additive in an LDPE/EVA Blend
No full textIn this work, we report the effect of combining styrene-vinyl tetrazole copolymer (StVTz) and ammonium polyphosphate (APP) on the thermal degradation, mechanical properties, flame retardancy, and char formation of low-density polyethylene with ethyl vinyl acetate (LDPE/EVA) composites. The tetrazole heterocycle exhibits high thermal stability (>200 °C), and during its thermal decomposition, it releases non-toxic nitrogen gas. Its degradation generates reactive species capable of cross-linking the polymer chains, thereby promoting the formation of a protective char layer. To evaluate the influence of composition on the intumescent flame-retardant (IFR) properties of LDPE/EVA blends, different concentrations of APP and StVTz additives were incorporated. The composites were prepared in an internal mixer (Brabender Intelli-Torque Plasti-Corder). Test specimens were obtained by compression molding and subsequently cut into appropriate shapes for each analysis. Thermal stability was studied by thermogravimetric analysis (TGA) and differential scanning calorimetry (DSC). Mechanical properties were evaluated by tensile testing. Morphology of cone calorimetry (CC) residues was examined using SEM. Flammability properties, studied using CC, revealed a 70% reduction in the peak heat release rate (pHRR) and a 48% reduction in the total heat release (THR) compared to the neat LDPE/EVA blend. These results indicate that StVTz and APP act synergistically to improve the flame-retardant properties of LDPE/EVA