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Hundreds of millions of smallholders in emerging countries substantially overuse nitrogen (N) fertilizers, driving local environmental pollution and global climate change. Despite local demonstrationscale successes, widespread mobilization of smallholders to adopt precise N management practices remains a challenge, largely due to associated high costs and complicated sampling and calculations. Here, we propose a long-term steady-state N balance (SSNB) approach without these complications that is suitable for sustainable smallholder farming. The hypothesis underpinning the concept of SSNB is that an intensively cultivated soil–crop system with excessive N inputs and high N losses can be transformed into a steadystate system with minimal losses while maintaining high yields. Based on SSNB, we estimate the optimized N application range across 3,824 crop counties for the three staple crops in China. We evaluated SSNB first in ca. 18,000 researcher-managed on-farm trials followed by testing in on-farm trials with 13,760 smallholders who applied SSNB-optimized N rates under the guidance of local extension staff. Results showed that SSNB could significantly reduce N fertilizer use by 21 to 28%while maintaining or increasing yields by 6 to 7%, compared to current smallholder practices. The SSNB approach could become an effective tool contributing to the global N sustainability of smallholder agriculture.

Smallholder farming is the most prevalent form of agriculture in the world, supports many of the planet's most vulnerable populations, and coexists with some of its most diverse and threatened landscapes. However, there is little information about the location of small farms, making it difficult both to estimate their numbers and to implement effective agricultural, development, and land use policies. Here, we present a map of mean agricultural area, classified by the amount of land per farming household, at subnational resolutions across three key global regions using a novel integration of household microdata and agricultural landscape data. This approach provides a subnational estimate of the number, average size, and contribution of farms across much of the developing world. By our estimates, 918 subnational units in 83 countries in Latin America, sub-Saharan Africa, and South and East Asia average less than five hectares of agricultural land per farming household. These smallholder-dominated systems are home to more than 380 million farming households, make up roughly 30% of the agricultural land and produce more than 70% of the food calories produced in these regions, and are responsible for more than half of the food calories produced globally, as well as more than half of global production of several major food crops. Smallholder systems in these three regions direct a greater percentage of calories produced toward direct human consumption, with 70% of calories produced in these units consumed as food, compared to 55% globally. Our approach provides the ability to disaggregate farming populations from non-farming populations, providing a more accurate picture of farming households on the landscape than has previously been available. These data meet a critical need, as improved understanding of the prevalence and distribution of smallholder farming is essential for effective policy development for food security, poverty reduction, and conservation agendas.

Smallholder farmers play an important role in ensuring world food security. In addition to food security, small-scale farming also provides numerous other direct and indirect environmental, social, cultural, and economic benefits by improving crop diversification, job security, and self-sufficiency. However, small-scale agriculture faces several challenges which are further exacerbated by climate change, population increase, water scarcity, and soil degradation. Agriculture has seen a lot of technological advancements in the last few decades. However, access to these advancements has not always been economically viable for small or medium farm operations. This article aimed to review the major barriers to small-scale farming and to review the status and potential opportunities offered by advanced technologies that can benefit small-scale holders. Based on the review, we found that economics, marketing, climate change, lack of awareness, educational resources, infrastructure, information, and technology are the major challenges to small-scale farming. Technologies such as unmanned aerial vehicles (UAVs), the IoT (internet of things), irrigation automation, and the use of smartphones are already becoming mainstream in small-scale farming and other technologies like robotics, artificial intelligence (AI), yield monitoring, and food traceability have potential opportunities to solve the challenges that hamper the success of small-scale growers.

Poverty is prevalent in the small-farm sector of many developing countries. A large literature suggests that contract farming—a preharvest agreement between farmers and buyers—can facilitate smallholder market participation, improve household welfare, and promote rural development. These findings have influenced the development policy debate, but the external validity of the extant evidence is limited. Available studies typically focus on a single contract scheme or on a small geographical area in one country. We generate evidence that is generalizable beyond a particular contract scheme, crop, or country, using nationally representative survey data from 6 countries. We focus on the implications of contract farming for household income and labor demand, finding that contract farmers obtain higher incomes than their counterparts without contracts only in some countries. Contract farmers in most countries exhibit increased demand for hired labor, which suggests that contract farming stimulates employment, yet we do not find evidence of spillover effects at the community level. Our results challenge the notion that contract farming unambiguously improves welfare. We discuss why our results may diverge from previous findings and propose research designs that yield greater internal and external validity. Implications for policy and research are relevant beyond contract farming.

Young breeding programs in developing countries, like the Chibas sorghum breeding program in Haiti, face the challenge of increasing genetic gain with limited resources. Implementing genomic selection (GS) could increase genetic gain, but optimization of GS is needed to account for these programs’ unique challenges and advantages. Here, we used simulations to identify conditions under which genomic-assisted recurrent selection (GARS) would be more effective than phenotypic recurrent selection (PRS) in small new breeding programs. We compared genetic gain, cost per unit gain, genetic variance, and prediction accuracy of GARS (two or three cycles per year) vs. PRS (one cycle per year) assuming various breeding population sizes and trait genetic architectures. For oligogenic architecture, the maximum relative genetic gain advantage of GARS over PRS was 12–88%, which was observed only during the first few cycles. For the polygenic architecture, GARS provided maximum relative genetic gain advantage of 26–165%, and was always superior to PRS. Average prediction accuracy declines substantially after several cycles of selection, suggesting the prediction models should be updated regularly. Updating prediction models every year increased the genetic gain by up to 33–39% compared to no-update scenarios. For small populations and oligogenic traits, cost per unit gain was lower in PRS than GARS. However, with larger populations and polygenic traits cost per unit gain was up to 67% lower in GARS than PRS. Collectively, the simulations suggest that GARS could increase the genetic gain in small young breeding programs by accelerating the breeding cycles and enabling evaluation of larger populations.

Caseous lymphadenitis (CLA) is a bacterial infection caused by Corynebacterium pseudotuberculosis (C. pseudotuberculosis) that affects sheep and goats, leading to abscess formation in their lymph nodes. The present study aimed to isolate and identify C. pseudotuberculosis from CLA in smallholder sheep and goats, and determine the resistance patterns, virulence, and resistance genes of the isolates. Additionally, genotypic and phylogenetic analysis of the isolates was conducted using ERIC-PCR and DNA sequencing techniques. A cross-sectional study examined 220 animals (130 sheep and 90 goats) from 39 smallholder flocks for clinical signs of CLA. Fifty-four (24.54%) animals showed CLA-compatible lesions, confirmed by C. pseudotuberculosis isolation and PCR identification. Sheep had a lower infection rate of CLA (18.46%) compared with goats (33.3%). Antimicrobial susceptibility testing of 54 C. pseudotuberculosis isolates to 24 antimicrobial drugs revealed that they were 100% resistant to bacitracin and florfenicol, while none of the isolates were resistant to norfloxacin. A high resistance rate was observed for penicillin and erythromycin (92.6% each). Interestingly, 16.7% of C. pseudotuberculosis isolates recovered from sheep showed vancomycin resistance. Molecular characterization of C. pseudotuberculosis isolates revealed that PLD, PIP, and FagA virulence genes were present in all examined isolates. However, the FagB, FagC, and FagD genes were detected in 24 (100%), 20 (83%), and 18 (75%) of the sheep isolates, and 26 (87%), 26 (87%), and 18 (60%) of the goat isolates, respectively. The β-lactam resistance gene was present in all isolates. Furthermore, 83% of the sheep isolates carried the aminoglycoside (aph(3″)-lb), chloramphenicol (cat1), and bacitracin (bcrA) resistance genes. Among the isolates recovered from goats, 73% were found to contain macrolides (ermX), sulfonamide (sul1), and bacitracin (bcrA) resistance genes. It is worrisome that the glycopeptide (vanA) resistance gene was detected in 8% of the sheep isolates as a first report. ERIC-PCR genotyping of 10 multi-drug-resistant C. pseudotuberculosis isolates showed a high similarity index of 83.6% between isolates from sheep and goats. Nucleotide sequence analysis of partial 16S rRNA sequences of C. pseudotuberculosis revealed 98.83% similarity with biovar Ovis of globally available reference sequences on the Genbank database. Overall, our findings might indicate that C. pseudotuberculosis infection in smallholders in Egypt might be underestimated despite the significant financial impact on animal husbandry and potential health hazards it poses. Moreover, this study highlights the importance of implementing a sustainable control strategy and increasing knowledge and awareness among smallholder breeders to mitigate the economic impact of CLA.

Objective: Many studies have observed different characteristics among productive systems in the rural territories of Latin America. Therefore, understanding and characterizing them while they function plays an essential role in determining their relationship between development and environment. A study has been conducted in the Orellana province of NE Ecuador to determine their typology and then classify them according to the variables that describe their main traits or attributes using cluster analysis (CA). Materials and Methods: A survey was structured to investigate physical, productive, environmental, as well as socioeconomic character variables, which were subsequently applied to a random sample of the 5,963 agricultural productive units (APUs) through face-to-face contact with producers during an in situ visit to their farms. Result: The CA allowed us to identify three typologies of APUs in the Orellana Province. The first has been Type 1, which is denominated as the most conventional (40%), while Type 2 uses more efficient natural resources but represents an amount of only 9.4%. In contrast, type 3 (50.6%) depends on a significant part of local or national development programs. Conclusion: All groups indicated some peculiarities in common, as there were marked differences in the use and distribution of land as well as production methods among them. Consequently, this pioneering study allowed us to identify different production methods. Therefore, we encourage local and national governments to establish policies for natural resource conservation in such high-diversity zones.

Despite agriculture being a significant contributor to sub-Saharan Africa’s economy, its exploding population puts the region at the highest global risk for food insecurity. Agricultural productivity in the region must meet the growing domestic demand and the needs of global markets. However, the central actors, smallholder farmers, face chronic challenges marketing their produce in high-value markets. While local agricultural policies encourage smallholder farmers and give them education and access, subsistence mindsets are believed to hold them back. This study approaches this challenge from a different, farmer-centric view and proposes a new construct reflecting sustained and meaningful marketing activity—smallholder market participation. With survey data from 464 smallholder farmer-entrepreneurs in Zimbabwe, we reveal how market orientation, access to ancillary services, functional literacy, entrepreneurial abilities, and marketplace metacognition allowed them to beat the odds and grow in the market. We document financial and non-financial outcomes, such as increasing credibility in the marketplace. Our findings offer agribusiness marketers and policymakers more precise indicators of smallholder engagement with markets. The study contributes to marketing theory by highlighting the marketing caliber of an understudied actor, the smallholder farmer.

In South Asian and Sub-Saharan African nations, climate change offers numerous hurdles to growth and development. These regions are susceptible to climate change due to their vast population reliance on agriculture, high demand for natural resources, and comparatively limited strategies for coping. Reduced food grain yields, crop losses, feed scarcity, lack of potable water for livestock during the summer, forceful animal migrations, and severe losses in the poultry and fishery industries have all been documented, posing a threat to the lives of the rural poor. As global food security and agricultural productivity become increasingly vulnerable, the focus has shifted towards adopting climate-smart agricultural practices and techniques. The present study discussed the need to identify and prioritize regionally evolving climate-smart farming practices and the enabling environment required for CSA uptake. The popular CSA practices in South Asia and Sub-Saharan Africa are crop rotation, cultivation of drought/flood-tolerant crops, legume intercropping, changing planting dates, rainwater harvesting, agroforestry, micro-irrigation technologies, minimum tillage, and integrated crop-livestock farming. A solid institutional structure, policy environment, infrastructure, agricultural insurance, climate information services, and gender and social inclusion provide the required enabling environment to alleviate farmer issues, lower CSA adoption obstacles, and improve operational sustainability. Highlights of the study are: This study examines how climate-smart farming practices are evolving in South Asia and SubSaharan Africa. We used a systematic approach to categorize and characterize agricultural adaptation alternatives to climate change. Our specific goals are to gain knowledge of the CSA adoption-enabling environments and the climate-smart agriculture practices employed in South Asia and Sub-Saharan Africa

Vaccination against highly pathogenic avian influenza (HPAI) viruses, along with other measures, was successful in eradicating AI in very few countries where the competence of national veterinary services or the geography and bird density have contributed favorably to the outcome.  The main constraints to an effective AI vaccination are vaccine composition matching field strains, reliable cold chain and logistics to target all poultry smallholders, constraints related to the availability of sufficient financial and human resources.  When not conducted properly, vaccination can also contribute to the emergence of new field viral strains, through genetic drifts of HPAI viruses.   While new technologies have improved the possibility to produce high quality vaccines matching field strains, recurrent issues like post-vaccination field surveillance and vaccination coverage continue to limit the relevance of AI vaccination in smallholder settings. A “game-changer” vaccine targeting smallholders should be universal to protect against all field viral strains and reduce significantly, if not totally eliminate, the need for costly post-vaccination surveillance.  The ease of administration of this vaccine (eye drop or one single injection) would further contribute to its relevance in the field.  These characteristics are considered essential for the product profile of an AI vaccine that can contribute in a meaningful way to the livelihoods of poultry smallholders.