The emergence of microbiological inputs and the challenging laboratorisation of agriculture: lessons from Brazil and Mexico

In this article, we analyse the tensions associated with the emergence of microorganism-based agricultural inputs in two Latin American countries, Brazil and Mexico. More specifically, we examine the ways in which these technologies, which are based on the use of living organisms, leave public microbiology research laboratories and are further developed by manufacturers or farmers. To this end, we draw on the concept of the ‘laboratorisation’ of society, part of the actor-network theory. We show that the emergence of these technologies is currently facing a number of challenges, due to the risks associated with their biological nature and the difficulty involved in establishing production processes as reliable as those used in reference laboratories. Whether produced by companies or on farms, the quality and safety of the practices and of these products are the subject of debate, as well as the focus of scientific, economic and political scrutiny. These microbiological inputs are evidence for the transformation of the relationship between science, industry, users and politics that is taking place around the emergence of alternatives to synthetic chemical inputs in agriculture, and more broadly, about the use of microbiological resources in agriculture.369–38

Optimization of sparse phenotyping strategy in multi-environmental trials in maize

The phenotyping needs to be optimized and aims to achieve desired precision at low costs because selection decisions are mainly based on multi-environmental trials. Optimization of sparse phenotyping is possible in plant breeding by applying relationship measurements and genomic prediction. Our research utilized genomic data and relationship measurements between the training (full testing genotypes) and testing sets (sparse testing genotypes) to optimize the allocation of genotypes to subsets in sparse testing. Different sparse phenotyping designs were mimicked based on the percentage (%) of lines in the full set, the number of partially tested lines, the number of tested environments, and balanced and unbalanced methods for allocating the lines among the environments. The eight relationship measurements were utilized to calculate the relatedness between full and sparse set genotypes. The results demonstrate that balanced and allocating 50% of lines to the full set designs have shown a higher Pearson correlation in terms of accuracy measurements than assigning the 30% of lines to the full set and balanced sparse methods. By reducing untested environments per sparse set, results enhance the accuracy of measurements. The relationship measurements exhibit a low significant Pearson correlation ranging from 0.20 to 0.31 using the accuracy measurements in sparse phenotyping experiments. The positive Pearson correlation shows that the maximization of the accuracy measurements can be helpful to the optimization of the line allocation on sparse phenotyping designs

Chapter 34. What do we know about the future of wheat?

Wheat has been and will remain a major component of diets globally. It accounts for an average of 18 percent of total energy intake and 19 percent of total protein intake globally. It is the primary staple food for 1.5 billion resource-constrained people in the Global South. Wheat represents 29 percent of the global cereals area and 14 percent of the global cropland area. It is an important crop in most agricultural areas of the world except the humid tropics and is less prominent in sub-Saharan Africa. Compared to rice and maize, it is more drought- and cold-tolerant. Wheat will continue to be an important source of protein in 2050, even under changing diets. In meat-based diets, wheat is often part of animal feed. In plant-based diets, wheat is a source of protein. Climate change offers both challenges and opportunities for wheat. Areas previously unsuitable for wheat production may have a comparative advantage under climate change. Similarly, some traditional wheat-growing areas may become less suitable for wheat production under climate change, especially due to heat stress. While Jägermeyr et al. (2021) indicate it can be beneficial for many existing wheat-growing areas, the impacts, for example, of increased frequency and intensity of heat waves, warmer night temperatures, and other weather anomalies are likely to counteract some of the benefits. Some of the poorer regions of the world are historically considered to be wheat-deficit areas and will increasingly depend on imports. This is a key factor in Africa, where there is less wheat production and wheat consumption is increasing with rising incomes.201-20

A weather-forecast driven early warning system for wheat blast disease: User-centered design, validation, and scaling in Bangladesh and Brazil

We describe the user-centered design (UCD) of a numerical weather-forecast-driven early warning system (EWS) as a climate service for managing wheat blast, a fungal disease capable of causing complete crop yield losses that is strongly dependent on weather conditions. Our mixed-methods process was guided by stakeholder input on the design, testing, and refinement of the EWS from agricultural extension organizations, meteorological departments, and farmers’ groups in Bangladesh and Brazil, where concerns about blast disease risks are high. The UCD process led to a wheat blast disease prediction model, server systems, and user-facing enhancements, including an open-source dashboard (https://beattheblastews.net/) that displays historical, real-time, and forecasted weather data, along with geographically explicit disease predictions, to support informed decision-making on wheat blast management. We describe the back- and front-end design of the dashboard, which supports disease risk forecasting, hindcasting, and the dissemination of early warning advisories co-designed with user organizations. We validated the EWS through comparisons with field observations in both countries. Model results generally agreed with disease incidence records, and model hindcasting confirmed alignment with disease outbreak patterns in Bangladesh and Brazil. Collaboration between agricultural research, meteorological and extension organizations in developing and supplying weather forecasts, disease management advisories, and early warning systems—along with presenting hindcast validation results to stakeholders—led to the formal endorsement of the EWS in both countries. This process also enabled the registration and training of over 14,500 extension officers, lead farmers, and farmers' cooperative members who now receive advisories via email, SMS, agro-meteorological bulletins, smartphone applications, WhatsApp and social media messages. These tools support them in interpreting and sharing wheat blast early warnings with farmers to improve disease preparadness and management actions in both countries

Sparse testcrossing for early-stage genomic prediction of GCA to increase genetic gain in maize hybrid breeding programs

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QTL mapping for leaf rust resistance in a recombinant inbred line population from the cross of wheat cultivars Zhongmai 578/Jimai 22

Leaf rust is a highly destructive disease that poses a significant threat to both the yield and quality of wheat. Identification of genetic loci can aid in enhancing leaf rust resistance in wheat breeding. In the present study, 262 recombinant inbred lines derived from a cross between Zhongmai 578 and Jimai 22 were used to map leaf rust resistance loci using the Wheat 50K single-nucleotide polymorphism (SNP) array across four environments. Four quantitative trait loci (QTL) on chromosomes 2B (2), 5B, and 7B were identified through composite interval mapping, designated QLr.caas-2B.1, QLr.caas-2B.2, QLr.caas-5B, and QLr.caas-7B, respectively, explaining 3.7%-19.6% of the phenotypic variances. The resistance alleles at QLr.caas-2B.1, QLr.caas-5B, and QLr.caas-7B originated from Zhongmai 578, while that at QLr.caas-2B.2 came from Jimai 22. Both QLr.caas-2B.2 and QLr.caas-5B overlapped with loci previously reported, whereas QLr.caas-2B.1 and QLr.caas-7B are likely to be new loci. Two kompetitive allele-specific PCR (KASP) markers, KASP-QLr.caas-2B.2 and KASP-QLr.caas-5B, were proven to be significantly associated with leaf rust resistance in a diverse panel of 119 wheat varieties mainly from China. Four candidate genes encoding a lectin-receptor kinase protein, F-box family protein, ankyrin repeat domain protein, and putative ABC transporter, respectively, were identified in genetic regions of the four QTL. These findings provide valuable QTL and breeding available KASP markers, facilitating the improvement of leaf rust resistance in wheat through marker-assisted breeding

Development of climate smart mechanization and irrigation lending product

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Tailored framework for sustainable intensification of marginal and small farms using farm typology to strengthen farm income

Farm typology studies assist in understanding how different farming components interact with each other and with the surroundings. These are often a prerequisite before devising adaptations to numerous agri-related challenges and in the development of sustainable agriculture policies. This holds importance for countries where the majority of the workforce is engaged in the agri-sector. The deliberated study investigates the determining factors that characterize the small and marginal farms spread across 16 states of India through typology to understand the limitations and challenges to formulate an alternative framework for leveraging their livelihood through enhanced income. The study clusters the surveyed farms under 06 farm types following a multivariate statistical approach. Further, it recommends alternate farming system models developed at research stations for different agro-climatic zones and the attributes of the respective farm type for the contemplated agroclimate zones. The study further scopes for the increment in annual farm income following the adoption of the recommended models. The results underscore the potential impacts of recommended models on the farmer's livelihoods

Mango under climate change scenarios: Evaluating temperaturebased suitability across elevation gradients of Nepal

Mango (Mangifera indica L.) has been grown predominantly in southern plains of Nepal. Climate change is expected to affect vegetation including its impact on mango phenology. To investigate how future climate affect mango suitability in Nepal, thresholds of bioclimatic variables such as Bio5 and Bio6 were set based on available literatures and related climate projections of 30 years’ time interval, were sourced from CHELSA platform. This constitutes the near current (1981-2010) as baseline for this study, and near future (2011-2040), mid-century (2041-2070) and end century (2071-2100) timeframes for three Shared Socioeconomic Pathways and climate forcing scenarios (SSP1- 2.6, SSP3-7.0 and SSP5-8.5). Utilizing geospatial layers of the bioclimatic variables, currently available land cover map and digital elevation model (DEM), the change in suitable area and elevation for mango were mapped for Nepal. The results suggest that elevated temperature across different climate projection scenarios will increase additional mango suitable area up to 35.9 percent during end century from near current and extend suitability to higher elevation, ranging from additional 89.02 m in SSP1-2.6 of near future to 502.67 m in SSP5-8.5 of end century. The increment in suitability will further differ across elevation ranges and provinces, Karnali witnessing the highest rate of change in suitable area in all scenarios. The upward extension of suitability in the changed climatic conditions for Nepal’s has implications in future fruit zoning and climate adaptation planning. This also demands further research on integration of this tropical fruit in the existing farming systems where mango cultivation was not in practice.16 page

Transfer of cytoplasmic male sterility to the female parents of heat- and drought-resilient maize (Zea mays L.) hybrids

Maize is the second most important staple food crop in the world after wheat. For maize hybrid seed production, a prominent step is detasseling in the female parent, which is laborious, time consuming, and increases the hybrid seed cost by 15 to 20 percent. Hence, to overcome this problem, exploitation of male sterility in maize crops gains special significance. In this direction, the research was conducted to transfer cytoplasmic male sterility (CMS-C) from a CMS donor (VL192114) into the female parents (CAL1514 and ZL153493) of heat- and drought-resilient maize hybrids (RCRMH-2 and RCRMH-3) by a marker-assisted backcross scheme. The present research used Diversity Array Technology (DArTag) and Kompetitive Allele Specific PCR (KASP)-based single-nucleotide polymorphic markers for background selection in backcross populations. Genome recovery percentage ranged from 64.25 to 72.70, 78.94 to 87.69 and 82.28 to 90.77 percent in the BC1F1, BC2F1 and BC3F1 population, respectively, in the CAL1514 population, while it was 63.47 to 73.55, 78.16 to 88.76 and 83.96 to 91.81 percent in the BC1F1, BC2F1 and BC3F1 population, respectively, in the ZL153493 population. When the near-isogenic CMS lines of both populations are compared for agro-morphological traits with their recurrent parents, the agronomic qualities of recurrent parents, as well as the attributes of distinctness, uniformity and stability, are shown. Therefore, male sterility-transferred, female lines of RCRMH-2 and RCRMH-3 maize hybrids can be used directly to produce maize hybrid seed without the need of the detasseling process