Small Farm Size Research Articles

Prevalence of bean scab caused by Elsinoë phaseoli and challenges associated with bean cultivation in Kenya.

This study investigated the prevalence of scab caused by Elsinoë phaseoli causing yield losses on beans in Kenya. The research focused on common practices and challenges faced by subsistence farmers with the aim of providing insights into scab prevalence, impact, and potential management challenges. A structured questionnaire was employed in a survey conducted in 2022 and 2023, covering major bean-growing regions using a three-stage sampling design. Data from 128 bean farmers included information on farm size, seed sources, cropping systems, awareness of challenges, and pest/disease management practices. Scab prevalence was determined by scouting for symptoms, with a total of 84 farms surveyed in 2021. The incidence of bean scab was confirmed in all surveyed clusters, indicating its widespread occurrence across various agro-ecological zones. Farmers exhibited common practices such as preference for uniform bean seeds (61%), use of uncertified seeds (83%), intercropping (80%), and limited crop rotation. Challenges included disease and pest infestations, with limited diversity in management options. Confirmation of the presence of bean scab in diverse agro-ecological zones emphasizes its importance and the need for further research on its impact and epidemiology. Challenges with crop rotation were evident due to small farm sizes and subsistence-focused farming. The study recommends further research for a comprehensive understanding of the link between increased scab importance and current bean farming practices such as short rotation periods and the use of susceptible varieties. Training programs are also vital to improve farmers' knowledge on safe agro-chemical use, ensuring sustainable constraint management in common bean cultivation in Kenya.

Drought Adaptation Strategies Among Smallholder Cereal Farmers In Makueni County, Kenya

Increasing frequency and severity of drought increase vulnerability of smallholder cereal farmers globally. Arid and Semi-Arid Lands cover 80% of Kenya and location around the equator are major factors in drought development in the country. Frequent droughts result in fluctuations in cereal yields hence food insecurity in Makueni County. This study evaluated community-based and indigenous knowledge drought adaptations practiced by smallholder cereal farmers in Makueni County, Kenya. This study adopted explanatory sequential mixed methods research design. Household surveys (N=225) and key informant interviews (N=16) were used. Descriptive techniques were used in data analysis. The study found that frequent droughts in Makueni County resulted in adoption of small farm sizes for production of maize, sorghum and finger millet. Majority of the farmers produced between 1 and 10 bags of cereals. Majority (50.2%) of the smallholder cereal farmers who adopted community-based adaptations and indigenous knowledge-based drought adaptations strategies recorded an in increase in cereal yields in Makueni County. Early planting (66.7%), timely weeding (61.4%), manure application (57.0%), improving land tillage (56.1%), seed spacing (55.3%) and planting droughtresilient seeds (44.7%) led to the high annual cereal yields ranging between 1 and 10 bags in Makueni County. The drought adaptation strategies are commendable for upscaling in agro-ecological zones with similar climatic conditions in order to improve food production in the country. Information and data generated by this study is expected to result in improvement in drought adaptation policy formulation and adaptive capacity of smallholder cereal farmers hence, improvement in food production and security.

Economic Assessment of Small-Scale Mountain Dairy Farms by Using Accounting Data: Evidence from an Italian Case Study

Dairy mountain farms are economically disadvantaged due to small farm sizes and high production costs. This situation was exacerbated firstly by the opening of the market linked to the abolition of milk quotas; secondly by the rising prices due to the energy crisis due to covid 19 and the war in Ukraine. However, these farms are important for the preservation of traditional landscapes, the economy of these areas and the offered ecosystem services, especially when they are managed extensively. The objective of this research is to understand if mountain dairy farms are economically sustainable and competitive through the analysis of a case study. The economic analysis takes into account the production cost of milk, profitability, and some economic indicators using accounting data. The results show that the farm profitability is decreasing, and the costs are unsustainable. As a consequence, more efficient policy support is needed to overcome this crisis.

Economics and Constraints of Organic Turmeric at Kakching District of Manipur

Background: As the locale of the present study has high potential for production of organic turmeric, so to take the relevant measures for best exploit the resources and to create more income and employment to the rural people. Methods: The present study is based on 200 turmeric growers drawn by adopting a multistage purposive stratified simple random sampling technique from Kakching district; based on the primary data, collected through personal interview method with the help of pre-tested and well structured questionnaire exclusively designed pertaining for the agricultural year 2020-2022. Result: The majority (93.00 per cent) of the respondents belonged to semi-medium land holding with an area of 2.01 to 3.00 ha, total gross return was highest (₹ 1,61,768.44/-) for medium farm size group and benefit-cost ratio was highest (2.64 : 1) for small farm size group. The major production constraint was lack of proper inputs, lack of training, lack of irrigation facility, lack of quality planting material etc.

Spatiotemporal modeling of household's food insecurity levels in Ethiopia

The state of moderate and severe food insecurity in Ethiopia has not been significantly reduced for a long time due to cultural, natural, and manmade shocks, which cover most part of the country with considerable magnitude and have adverse effects on the health and economy. This temporal evolution of the wider geographic distribution of the food insecurity levels has not been investigated for the feeding culture and shocks effect in Ethiopia, though previous studies have indicated significant geographic distribution and related factors. In addition, the longtime zone-specific comprehensive drivers were not assessed. Therefore, this study focused on investigating the feeding culture-adjusted food insecurity levels (FCSL) and their evolutional sustainability across zones by identifying the factors causing each level of household's food insecurity tailored to a specific zone.In this study, Ethiopian socio-economic longitudinal data from years 2012, 2014, and 2016 with a sample size of 3835 households were analyzed. An ordinal spatiotemporal model with different interactions under empirical Bayes estimation was adopted, and the type III interaction with Markov random field was selected to reveal the evolution of FCSL sustainability across zones and find-out the causing factors of households to each level of food insecurity tailored to zone-level by analyzing the effects of diverse factors and shocks. The result reveals that a greater portion (52.07 %) of households’ population is moderately and chronically food insecure. Basically, households living in neighboring zones have significantly similar food insecurity levels, and slight improvements were observed over time. This transition over time within neighboring zones, revealed that chronic food insecurity in neighboring zones has transited to moderate food insecurity, particularly in most of the northern and southwestern areas of Ethiopia. However, the interaction term showed that the change in food insecurity levels for households living in neighboring zones is similar at one time point, but the evolution is not sustainable. Therefore, working on major zone-specific factors, such as enhancing zone-level urbanization through improving market and road linkage to rural areas, education, employment, non-agricultural businesses, and promoting integrated farming by conserving soil with consideration of additional confounding factors, will bring change and can sustainably eradicate moderate and chronic food insecurity in zone households through controlling dependency ratios, shocks, and small land size farming. This study brings resilient, manageable, and zone-specific mitigation for households living in food-insecure and vulnerable zones.

A Comparative Analysis of Household Food Insecurity Status among Rice Farmers in Savanna and the Rainforest Agro-ecological Zones in Southwest States, Nigeria

The study presents findings on comparative analysis of household food insecurity status among rice farmers in the Savanna and the Rainforest agro-ecological zones in Southwest States, Nigeria. Primary data were used and obtained through the administration of a well structured questionnaire. A multistage random sampling was used to select 577 rice farmers in the study area. Data were analyzed using descriptive statistics, household food insecurity access (HFIA) scale, household food insecurity access prevalence (HFIAP) scale, likert scale and linear regression model. The results revealed that majority of the rice farmer’s fall within 31-50 years of age bracket, with household size of 5-8 persons, married, with farming experiences and have small farm size. The findings from average household food insecurity access scale scores in the Savanna and the Rainforest agro-ecological zones were 4.0 (mildly food insecure) and 5.2 (moderately food insecure) respectively. The results of HFIAP indicator revealed that about 39.1% and 33.5% of respondents were classified as food secure, 8% and 13.9% were mildly food insecure, 15.1% and 22.2% were moderately food insecure and 37.8% and 30.4% were severely food insecure in the Savanna and the Rainforest agro-ecological zones respectively. The major coping strategies adopted by the respondents against food insecurity include reduce the quantity of food consumed and eating but not satisfied. The linear regression model revealed that age, sex, years in school, farm size, household size, farming experience, rice farming experience and tenure system significantly affect household’s food insecurity status. To transport from food insecure to food secure, age, sex, years in school, farm size, household size, farming experience, rice farming experience and tenure system alleviation policies are imperative.

Thai farmers’ perceptions on climate change: Evidence on durian farms in Surat Thani province

Rising temperatures, unpredictable rainfall patterns, and an increase in extreme weather events pose significant threats to agricultural productivity and food security. These conditions provide the glimpse of the future and smallholder farmers, who often lack access to resources and support, are particularly vulnerable. Among the crops cultivated in Thailand, durian stands out as a uniquely cherished commodity, predominantly cultivated by these vulnerable farmers and despite the significance of this crop, there remains a notable oversight in understanding the specific challenges and vulnerabilities faced by durian growers in the face of changing climatic conditions. The objective of this study was to investigate the perception of climate change and the adaptive capacity among durian farmers in Southern Thailand. A survey involving 80 durian farmers from Surat Thani province was conducted, and the data were analyzed using descriptive statistics and a binary logistic regression model. Findings found that 91.2 % of respondents acknowledged the impact of climate change, with 53.1 % opting to implement adaptation strategies. Factors such as lower education levels, limited farming experience, small farm sizes, and greater reliance on family labor significantly influenced the adoption of these strategies. Farmers achieving higher yields tended to adopt information and communication technologies (ICT), while smart farming technology (SFT) was more common among younger farmers and those with larger farms. This study indicates factors influencing adoption and a potential gap between awareness and action among durian farmers, highlighting the need for targeted interventions and support mechanisms to encourage and facilitate the implementation of adaptation measures.

Biosecurity practices in the dairy farms of southern Brazil.

Biosecurity refers to a set of practices that prevents and/or controls the introduction, spread, and elimination of harmful biological agents in a production system. In this study, we aimed to survey the biosecurity practices and determine their correlation with the size of production systems. A biosecurity assessment form was provided to 69 farms in the Campos Gerais region of Paraná, Brazil. The questionnaire was divided into two sections: general and bovine viral diarrhea virus- and bovine herpesvirus type-1-specific sections. The general section covered topics on traffic control, quarantine and animal isolation, hygiene practices, carcass disposal, and disease monitoring/control. The specific section consisted of questions on the reproductive and respiratory factors, use of antimicrobials, and vaccination schedule. The 69 farms were also classified into small (≤ 61), medium (62-201), and large (≥ 202) size farms based on the number of lactating cows. Moreover, multiple correspondence analysis (MCA) was performed between the biosecurity measures and farm size. The main risk factors and variability were related to the traffic control of people, animals, and vehicles/equipment, animal quarantine/isolation, and hygiene practices. MCA revealed that the small farms exhibited a lack of biosecurity measures, including those related to traffic control, animal quarantine, and hygiene. In medium-size farms, contact between bovine animals of different ages and difficulty in animal isolation in the quarantine system were among the main risk factors. In contrast, isolation of sick animals was easy, but the need to frequently purchase cattle was an important risk factor in large farms. These results highlight the relationship between biosecurity measures and farm size, providing valuable insights for the development of better biosecurity plans for production systems.

Resource-use-efficiency and Constraints Faced by the King Chilli Growers in Peren District of Nagaland

Background: The cultivating of King chilli has been practicing since long in Peren district of Nagaland; and registered under Geographical Indication Tag in the year 2006. So, the present study aimed to access the inputs used with maximum level of resource-use-efficiency tocontributethe output and highlight the major constraints faced by the King chilli growers. Methods: The present research investigation were carried out during the agricultural year 2020-21 with a total of 120 King chili growers; selected by following a multi-stage simple random quota sampling technique to access the impact. Result: The King chilli growers of marginal and small both farm size groups were found to be highly statistically significant at 1 per cent level; by ceteris paribus, the selected inputs were categorized viz; underutilized and over utilized with the available resources and further main constraints faced by the respondents were highlighted.

Analysis of Chainsaw Emissions during Chestnut Wood Operations and Their Health Implications

In Italy, the use of chainsaws for field operations such as Felling (FE), Delimbing (DE), and Bucking (BU) is widespread due to the topography, the medium–small size of farms, and the predominant presence of broad-leaved forests managed through coppicing. However, this has led to an increase in injuries and illnesses due to exposure to physical factors (e.g., noise, dust, and vibrations) and chemical agents (e.g., various volatile compounds). Occupational health and safety legislation in Italy has undergone several phases, including the approval of U.T. 81/2008. The present study aims to evaluate the noise generated by chainsaws and the concentration of pollutants (CO, VOC, and C6H6) present in chainsaw exhaust gases during interventions in a chestnut coppice in relation to the limits set by current legislation. The analysis of the noise generated by chainsaws during chestnut cutting operations showed that it exceeded the legal noise limits during all chainsaw activities, with peak levels of about 110 dB. The detected noise could cause important critical issues in relation to the health and safety of specialized operators. Furthermore, the correlation between the specific work (FE, DE, and BU) and the ratio between maximum and average values of CO and VOC emissions was evaluated. Notably, comparable levels of maximum VOC emissions were observed during the FE and BU phases. However, the average emission values during these phases exhibited significant differences, suggesting higher VOC production when the engine was running but not actively engaged in cutting. The highest emissions were recorded during the FE phase (CO = 135 ppm, VOC = 17.28 ppm, and C6H6 = 2.13 ppm).

Growth, yield and oil quality of adult pedestrian olive orchards grown at four different planting systems.

This study evaluated growth, yield and olive oil quality of mature pedestrian olive orchards. Trees of three Sicilian cultivars Calatina, Nocellara del Belice and Abunara were planted at four combinations of planting densities and training forms. Trees at 2 × 5m were trained to central leader (CLx2), those at 3 × 5m to free palmette (FPx3), those at 4 x 5 to globe vase (GVx4), and those at 5 x 5 to poly-conic vase (PVx5). 'Calatina' had the smallest trees in terms of trunk size in all growing systems, while canopy size of trees at higher densities was similar for all three cultivars. 'Calatina' was also the most growth efficient (m3 of canopy per cm2 of TCSA) and produced the least amount of pruning wood in the hedgerow systems (CLx2 and FPx3). Fruit yield per tree tended to be higher in more vigorous cultivars (Abunara and Nocellara) grown to 3D systems (GVx4 and PVx5), while 'Calatina' was the most yield efficient (kg of fruit per cm2 of TCSA) especially in the hedgerow growing systems. Fruit and oil yield per ha and average production value tended to be highest in CLx2 trees and lowest in GVx4 trees, with 'Calatina' showing the sharpest changes and 'Nocellara' the smallest changes among growing systems. According to the Jaen index, CLx2 tended to induce earlier fruit maturation, followed by PVx5, GVx4, and FPx3. The growing system did not affect oil fatty acid composition, while 'Calatina' had the highest amount of mono-unsaturated fatty acids and the lowest amount of saturated fatty acids. 'Abunara' oils exhibited the highest amount of total phenols in CLx2, while 'Calatina' and 'Nocellara' oils exhibited the highest amount in FPx3 and PVx5. Both, trans-2-hexenal ("cut grass" sensory note) and hexenyl acetate ("floral" sensory note) tended to be lowest in oils from trees grown at CLx2 and highest in those from trees grown at GVx4, showing a somewhat inverse relationship with fruit ripening degree. The outcome of the present study on mature pedestrian orchards shows that proper combinations of cultivars, planting densities, and training forms (canopy shape) may result in efficient intensive systems for growing olive in areas where super-high density systems cannot be profitable due to agronomic and environmental limitations (water shortage, steep sloping sites, small farm size, etc.). Pedestrian growing systems can also be used to exploit olive biodiversity by allowing the use of available local genotypes. For this reason, they may represent an effective and sustainable solution against unexpected climate changes and associated emerging diseases.

Measuring the Impact of Strategic Decisions on the Sustainability of Short Food Supply Chains – A Simulation-Based Approach

Short Food Supply Chains have logistics costs almost four times higher than the average of the agri-food sector [8]. And yet, the environmental impact of small-size farms involved in such initiatives is believed to be much better, with less input and less soil depletion. With the agricultural sector responsible for 26% of CO2 emissions, economically viable and environmentally friendly initiatives in this sector can have huge impacts in terms of climate change mitigation. This paper proposes a simulation-based approach, applied on an existing short food supply chain. The performance of the system is measured and analyzed in three dimensions: economic, environmental, and social, with qualitative discussions on their correlations. The framework of indicators proposed is based on a literature review of usual KPIs for Food Supply Chains. We adapted the set of indicators in order to evaluate the performance of the actual organization, and simulate the impact of three optimization possibilities, chosen based on local opportunities. Our results enable us to facilitate decision-making for the organization, by visualizing the impact of each strategic decision on sustainability. The outcomes of this research provide input for further studies investigating the logistical organization in SFSCs, helping these initiatives become a viable and sustainable alternative to conventional food systems. For this paper, we limited the study to past available data regarding demand and supply, and we also limited the scope of the supply chain to the producers, customers, and association.

An open-source machine-learning application for predicting pixel-to-pixel NDVI regression from RGB calibrated images

The Normalized Difference Vegetation Index (NDVI) is the most common index to measure vegetation in agriculture and create classified prescription maps used for several purposes. It is obtained as the ratio between information from the visible and near infrared spectral bands. The calculation of NDVI often uses very expensive hyperspectral and multispectral optical sensors. This study aims to develop an efficient model to extract NDVI data from RGB images. During the work were acquired images, of different plant species at different vegetation status, through a snapshot hyperspectral camera (Specim IQ) featuring natively superimposed RGB sensor whose images were calibrated a posteriori (sRGB). NDVI was predicted from sRGB images using a Shallow-regressive neural network that performs a pixel-pixel regression. The model has been then tested on around 1000 drone images acquired by a 6x Sentera sensor to test the efficiency of the applied model. The model has been used to estimate the numerical value of NDVI and the classes produced by a clustering method (k-means). The results of this work showed that the calibrated images had a very high correlation with the NDVI in validation (r = 0.91), maintaining good performances (r = 0.71) when applied to a set of data acquired with a different non-co-registered sensor. Therefore, for the first time this work has shown that the health of vegetation through the NDVI could be calculated using unexpensive RGB device adopting a pixel-pixel regression AI approach. The approach shows its importance especially for small-sized farms where profit would not allow for the budget to access multispectral cameras and heavy carriers (i.e., UAV).

The Women Farmer Stress Inventory: Examining women farmer stress in the United States Corn Belt.

While women identifying as primary farmers have increased in the United States, there has not been research focused on the antecedents of stress and quality of life among women farmers in particular. This study set out to construct a Women Farmer Stress Inventory (WFSI), test its dimensionality, and assess its criterion-related validity by looking at its relationship with subjective wellbeing as measured by the Satisfaction with Life Scale (SWLS). We then examined sociodemographic and farm-level correlates to assess their relationship with stress. We utilized responses from a random sample of 592 Iowan women farmers who responded to a mailout survey that included the WFSI. We conducted exploratory factor analysis to identify the factorial structure of the WFSI, and used linear regression to evaluate how sociodemographic and farm-level characteristics were related to each factor. The analysis revealed 5 unique factors that reflected different aspects of women farmer stress: time pressures and workload, environmental concern, external stressors from governments and market, interpersonal relationships, and rural amenities. All factors except rural amenities had high levels of internal consistency (Cronbach's alpha >0.80) and were validated using the external criteria of SWLS measures. Young age, being married, and engagement in off-farm work, and smaller farm size were associated with greater levels of stress across most domains. The WFSI is a promising tool that shows high internal consistency and is validated with life satisfaction. Our study also finds certain sociodemographic and farm characteristics associated with different stress domains, which could inform both future research and community-based interventions.

Examination of Structural Characteristics and Biosecurity of Sheep Farms in Niğde Province

The aim was to examine the structural features and biosecurity practices of sheep farms operating in Niğde province. For this purpose, 75 farms operating in the region were classified according to size (number of animals) and production system (extensive and intensive) and, they were compared in terms of typology and biosafety. In this context, a face-to-face survey was conducted with the owners or authorized persons of the small, medium and large size farms and the data collected from the farms about technical, sanitation-hygiene and health protection were comparatively presented. According to the findings obtained from the study, manure and wastes produced in 24% of farms were seen randomly throwing into the environment, and the differences observed between farms depending on the farm size were found significant (P<0.05). These farms can become a potential source of environmental and odor pollution. In addition, it was determined that disinfection was not applied to a large extent (97.30%) as a preventive measure at farm and shelter entrances (P>0.05). At the end of the study, it has been concluded that the typology and biosafety practices could be an important support for future strategic programs against disease and other factors which affects the production of the Niğde region.

Developing flexible models for genetic evaluations in smallholder crossbred dairy farms

The productivity of smallholder dairy farms is very low in developing countries. Important genetic gains could be realized using genomic selection, but genetic evaluations need to be tailored for lack of pedigree information and very small farm sizes. To accommodate this situation, we propose a flexible Bayesian model for the genetic evaluation of milk yield, which allows us to simultaneously account for nongenetic random effects for farms and varying SNP variance (BayesR model). First, we used simulations based on real genotype data from Indian crossbred dairy cattle to demonstrate that the proposed model can separate the true genetic and nongenetic parameters even for small farm sizes (2 cows on average) although with high standard errors in scenarios with low heritability. The accuracy of genomic genetic evaluation increased until farm size was approximately 5. We then applied the model to real data from 4,655 crossbred cows with 106,109 monthly test day milk records and 689,750 autosomal SNPs. We estimated a heritability of 0.16 (0.04) for milk yield and using cross-validation, a genomic estimated breeding value (GEBV) accuracy of 0.45 and bias (regression of phenotype on GEBV) of 1.04 (0.26). Estimated genetic parameters were very similar using BayesR, BayesC, and genomic BLUP approaches. Candidate genes near the top variants, IMMP2L and ARHGEF2, have been previously associated with milk protein composition, mastitis resistance, and milk cholesterol content. The estimated heritability and GEBV accuracy for milk yield are much lower than those from intensive or pasture-based systems in many countries. Further increases in the number of phenotyped and genotyped animals in farms with at least 2 cows (preferably 3-5, to allow for dropout of cows) are needed to improve the estimation of genetic effects in these smallholder dairy farms.

Influences of large-scale farming on carbon emissions from cropping: Evidence from China

Reducing agricultural carbon emissions is important to enable carbon emission peaking by 2030 in China. However, China's transformation towards large-scale farming brings uncertainties to carbon emission reduction. This study quantifies the carbon emissions from cropping based on life cycle assessment and estimates the effects of farm size on carbon emissions using a fixed effects model. Furthermore, the variations of the carbon emissions from cropping driven by the changes in farm size in future years are projected through scenario analysis. Results demonstrate an inverted U-shaped change in total carbon emission from cropping as farm size increases, which is dominated by the changes in the carbon emission from fertilizer. Projections illustrate that large-scale farming transformation will postpone the peak year of total carbon emission from cropping until 2048 if the change in farm size follows a historical trend, although it is conducive to reducing total carbon emission in the long run. The findings indicate that environmental regulations to reduce fertilizer usages should be strengthened for carbon emission abatement in the early stage of large-scale farming transformation, which are also informative to other developing countries with small farm size.

An Economic Analysis of Production of Pearl Millet in Jaipur District of Rajasthan, India

The present study entitled ‘An Economic Analysis of Production of Pearl Millet in Jaipur District of Rajasthan’ was carried out in 2022–2023 with a sample of 120 participants. The findings showed that Medium-sized farms had the highest percentage of respondents with a graduate degree, followed by Small(62.31%) and Marginal(42.75%) farms, and that Medium-sized(54.23%) farms had the highest percentage of illiterate people. In marginal size farms, the average area per hectare holding was 0.66 ha, in small size farms, it was 1.59 ha, and in medium size farms, it was 4.32 ha. The total cost of Pearl millet cultivation for marginal, small, and medium-sized farms was (Rs. 36010/ha),(Rs.35007/ha), and (Rs. 34223/ha), respectively. Medium-sized and small-sized farms saw excellent gross earnings per hectare (Rs51750/ha). The net returns per hectare obtained by small size farms were high (Rs. 50625/ha) as compared to marginal size farms (Rs. 49500/ha) and medium size farms (Rs. 13490/ha and Rs. 17525/ha), respectively. Compared to small and medium size farms (1:1.44 and 1:1.51), marginal size farms had the highest input-output ratio per hectare, and the marketable surplus for farmers in these three sizes was (6.73%, 21.73%, and 35.33%), correspondingly.

Review of the Current State and Potential Benefits of Using Herbicides by Smallholder Farmers in Sub-Saharan Africa

Poor weed control automatically results in yield losses, and the review has provided a range of 30-100% depending on the crop, weed species, and stage of the crop. The timing and efficacy of the methods matter. Across the region, farmers use different methods broadly grouped into preventive, cultural, and curative methods. Herbicide application, a form of curative method, is seen as an effective means of weed control, which is cheap, time, and labor-saving technology for adoption. Also, the technology helps in soil carbon sequestration. Hence, it could be used to improve crop productivity and profitability of already of the farming systems in the region. The current adoption of herbicides is very low across SSA, ranging from 0.1-55%. The low adoptions in SSA could be associated with low education levels, poor knowledge, and experience with technology, cultural beliefs, high poverty levels, small farm size, and weak government and intercountry policies and extension services.

Soybean crop intensification for sustainable aboveground-underground plant–soil interactions

The major challenge of growing soybean, other than unfavorable weather and small farm size, is the non-availability of quality inputs at the right time. Furthermore, in soybean growing regions, crop productivity and soil environment have deteriorated due to the use of traditional varieties and conventional methods of production. Soybean crop intensification or system of crop intensification in soybean (SCI) is an agricultural production system that boosts soybean yields, improves the soil environment, and maximizes the efficiency of input utilization, although the contribution of SCI to crop productivity is not well understood as different genotypes of soybean exhibit different physiological responses. Therefore, a field study was conducted in 2014–2015 and 2015–2016 using three crop establishment methods (SCI at a 45 cm × 45 cm row spacing, SCI at 30 cm × 30 cm, and a conventional method at 45 cm × 10 cm) assisted in vertical strips with four genotypes (Pusa 9,712, PS 1347, DS 12–13, and DS 12–5) using a strip-plot design with three replications. Compared with standard methods of cultivation, the adoption of SCI at 45 cm × 45 cm resulted in a significantly higher stomatal conductance (0.211 mol H2O m−2 s−1), transpiration rate (7.8 mmol H2O m−2 s−1), and net photosynthetic rate (398 mol CO2 m−2 s−1). The implementation of an SCI at 30 cm × 30 cm had significantly greater intercepted photosynthetic active radiation (PAR) (1,249 mol m−2 s−1) than the conventional method system, increasing crop yield from 9.6 to 13.3% and biomass yield from 8.2 to 10.7%. In addition, under an SCI at 30 cm × 30 cm, there were more nodules, significantly larger root volume and surface density, and increased NPK uptake compared with the other methods. Significantly greater soil dehydrogenase activity, alkaline phosphatase activity, acetylene-reducing assay, total polysaccharides, microbial biomass carbon, and soil chlorophyll were found with SCI at 45 cm × 45 cm (13.63 g TPF g−1 soil hr.−1, 93.2 g p-nitro phenol g−1 soil hr.−1, 25.5 n moles ethylene g−1 soil hr.−1, 443.7 mg kg−1 soil, 216.5 mg kg−1 soil, and 0.43 mg g−1 soil, respectively). Therefore, the adoption of an SCI at 30 cm × 30 cm and/or 45 cm × 45 cm could provide the best environment for microbial activities and overall soil health, as well as the sustainable productivity of soybean aboveground.