Publications by authors named "Craufurd P"

Unlabelled: Far removed from the agricultural fire "hotspots" of Northwestern India, rice residue burning is on the rise in Eastern India with implications for regional air quality and agricultural sustainability. The underlying drivers contributing to the increase in burning have been linked to the adoption of mechanized (combine) harvesting but, in general, are inadequately understood. We hypothesize that the adoption of burning as a management practice results from a set of socio-technical interactions rather than emerging from a single factor.

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Yield gap analysis is used to characterize the untapped production potential of cropping systems. With emerging large-n agronomic datasets and data science methods, pathways for narrowing yield gaps can be identified that provide actionable insights into where and how cropping systems can be sustainably intensified. Here we characterize the contributing factors to rice yield gaps across seven Indian states, with a case study region used to assess the power of intervention targeting.

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Context Or Problem: In the Indian state of Odisha, rice-based system productivity is poor due to: (i) low rice yield in the monsoon (wet) season (2-4 t ha compared to 6-8 t ha in Punjab or Haryana); and (ii) limited cropping during the post-monsoon (dry) season (59% of the wet season rice area is left fallow in the dry season).

Objective: Our study identifies strategies for increasing rice-based system productivity through: (i) alternative crop establishment methods in the wet season (Dry-Direct Seeded Rice or DSR, and mechanical puddled transplanted rice or PTR-M) to traditional methods such as broadcasting followed by post-emergence tillage (locally known as ) and manual random puddled transplanted rice (PTR-R); (ii) to identify rice-fallow areas suitable for pulse and oilseed cultivation in the dry season; and (iii) to evaluate the performance of short-duration pulses (green gram, ; black gram, ), and oilseeds ( var. toria, ) in rice-fallow areas in the dry season.

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While many have extolled the potential impacts of digital advisory services for smallholder agriculture, the evidence for sustained uptake of such tools remains limited. This paper utilizes a survey of tool developers and researchers, as well as a systematic -analysis of prior studies, to assess the extent and challenges of scaling decision support tools for site-specific soil nutrient management (SSNM-DST) across smallholder farming systems, where "scaling" is defined as a significant increase in tool usage beyond pilot levels. Our evaluation draws on relevant literature, expert opinion and apps available in different repositories.

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Introduction: Conservation agriculture (CA) is gaining attention in the South Asia as an environmentally benign and sustainable food production system. The knowledge of the soil bacterial community composition along with other soil properties is essential for evaluating the CA-based management practices for achieving the soil environment sustainability and climate resilience in the rice-wheat-greengram system. The long-term effects of CA-based tillage--crop establishment (TCE) methods on earthworm population, soil parameters as well as microbial diversity have not been well studied.

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India will need to produce 30% more wheat by 2050, and these gains must principally come from intensification in eastern India where low productivity is common. Through a dense network of on-farm surveys for the rice-wheat system in this region, we show that contemporary wheat sowing dates have a central influence on achieved and attainable yields, superseding all other crop management, soil and varietal factors. We estimate that untapped wheat production potential will increase by 69% with achievable adjustments to wheat sowing dates without incurring undesirable trade-offs with rice productivity, irrigation requirements or profitability.

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Context: Millions of people living in the Eastern Gangetic Plains (EGP) of India engage in agriculture to support their livelihoods yet are income poor, and food and climate insecure. To address these challenges, policymakers and development programs invest in irrigation-led agricultural intensification. However, the evidence for agricultural intensification to lift farmers' incomes above the poverty line remains largely anecdotal.

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This dataset provides detailed information on rice production practices being applied by farmers during 2018 rainy season in India. Data was collected through computer-assisted personal interview of farmers using the digital platform Open Data Kit (ODK). The dataset,  = 8355, covers eight Indian states, viz.

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Agricultural statistics and applied analyses have benefitted from moving from farmer estimates of yield to crop cut based estimates, now regarded as a gold standard. However, in practice, crop cuts and other sample-based protocols vary widely in the details of their implementations and little empirical work has documented how alternative yield estimation methods perform. Here, we undertake a well-measured experiment of multiple yield estimation methods on 237 smallholder maize plots in Amhara region, Ethiopia.

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Article Synopsis
  • Direct Seeded Rice (DSR) shows promise for smallholder farmers in the Eastern Gangetic Plains, but its adoption is slowed by low demand and insufficient service availability from machinery owners.
  • There is a noticeable contrast in the adoption rates of DSR and zero tillage wheat, with the latter gaining traction more quickly, yet the reasons behind this trend have not been thoroughly investigated.
  • The study examines the decision-making processes of zero tillage drill owners, revealing a complex interplay of factors that affect DSR service provision and suggesting potential strategies to change community perceptions and improve DSR adoption.
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In many parts of Eastern India that have a very high prevalence of rural poverty and food insecurity, the prevailing rice establishment practice of '' is characterized by low yields and modest profitability, while labor and energy inputs are high. consists of broadcasting ungerminated rice seed at high rates (>100 kg ha) prior to the onset of monsoon rain, followed by ploughing at 4-6 weeks after crop emergence to control weeds with subsequent manual gap filling through seedling redistribution to ensure stand uniformity. Dry-direct seeding of rice (DSR), both drill-DSR and precision broadcast-DSR in combination with integrated weed management (IWM) may offer a pathway for simultaneously reducing costs and markedly increasing productivity.

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Intra-plot heterogeneity in yield is often observed in smallholder farming systems, although its implications for yield measurement remain under-investigated. Using a unique dataset on smallholder maize production in Ethiopia, we quantify the magnitude of inter- and intra-plot heterogeneity, describe the relationship between intra-plot heterogeneity and maize productivity, and document the implications of intra-field heterogeneity on the accuracy of alternative yield estimation protocols. Our data include five common yield estimation protocols, as well as full plot harvests of 230 smallholder maize fields.

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The CGIAR crop improvement (CI) programs, unlike commercial CI programs, which are mainly geared to profit though meeting farmers' needs, are charged with meeting multiple objectives with target populations that include both farmers and the community at large. We compiled the opinions from >30 experts in the private and public sector on key strategies, methodologies, and activities that could the help CGIAR meet the challenges of providing farmers with improved varieties while simultaneously meeting the goals of: (i) nutrition, health, and food security; (ii) poverty reduction, livelihoods, and jobs; (iii) gender equality, youth, and inclusion; (iv) climate adaptation and mitigation; and (v) environmental health and biodiversity. We review the crop improvement processes starting with crop choice, moving through to breeding objectives, production of potential new varieties, selection, and finally adoption by farmers.

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To contain the COVID-19 pandemic, India imposed a national lockdown at the end of March 2020, a decision that resulted in a massive reverse migration as many workers across economic sectors returned to their home regions. Migrants provide the foundations of the agricultural workforce in the 'breadbasket' states of Punjab and Haryana in Northwest India.There are mounting concerns that near and potentially longer-term reductions in labor availability may jeopardize agricultural production and consequently national food security.

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Emerging evidence supports the intuitive link between chronic health conditions associated with air pollution and the vulnerability of individuals and communities to COVID-19. Poor air quality already imposes a highly significant public health burden in Northwest India, with pollution levels spiking to hazardous levels in November and early December when rice crop residues are burned. The urgency of curtailing the COVID-19 pandemic and mitigating a potential resurgence later in the year provides even more justification for accelerating efforts to dramatically reduce open agricultural burning in India.

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When properly calibrated and evaluated, dynamic crop simulation models can provide insights into the different components of genotype by environment interactions (GEIs). Modelled outputs could be used to complement data from multi-environment trials. Field experiments were conducted in the rainy and dry seasons of 2015 and 2016 across four locations in maize growing regions of Northern Nigeria using 16 maize varieties planted under near-optimal conditions of moisture and soil nitrogen.

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Farm mechanization among smallholder farming systems in developing countries is emerging as a viable option to off-set the effects of labor out-migration and shortages that undermine agricultural productivity. However, there is limited empirical literature on gender and farm mechanization. This study assesses the impacts of the gender of household heads on mini-tiller adoption in the hills of Nepal, using an exogenous switching treatment regression model.

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In sub-Saharan Africa, there is considerable spatial and temporal variability in relations between nutrient application and crop yield, due to varying inherent soil nutrients supply, soil moisture, crop management and germplasm. This variability affects fertilizer use efficiency and crop productivity. Therefore, development of decision systems that support formulation and delivery of site-specific fertilizer recommendations is important for increased crop yield and environmental protection.

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Agricultural extension to improve yields of staple food crops and close the yield gap in Sub-Saharan Africa often entails general recommendations on soil fertility management that are distributed to farmers in a large growing area. Site-specific extension recommendations that are better tailored to the needs of individual farmers and fields, and enabled by digital technologies, could potentially bring about yield and productivity improvements. In this paper, we analyze farmers' preferences for high-input maize production supported by site-specific nutrient management recommendations provided by an ICT-based extension tool that is being developed for extension services in the maize belt of Nigeria.

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Establishing balanced nutrient requirements for maize ( L.) in the Northern Nigerian Savanna is paramount to develop site-specific fertilizer recommendations to increase maize yield, profits of farmers and avoid negative environmental impacts of fertilizer use. The model QUEFTS (QUantitative Evaluation of Fertility of Tropical Soils) was used to estimate balanced nitrogen (N), phosphorus (P) and potassium (K) requirements for maize production in the Northern Nigerian Savanna.

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Most crop simulation models require the use of Genotype Specific Parameters (GSPs) which provide the Genotype component of G×E×M interactions. Estimation of GSPs is the most difficult aspect of most modelling exercises because it requires expensive and time-consuming field experiments. GSPs could also be estimated using multi-year and multi locational data from breeder evaluation experiments.

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Background: The phenological development of the maize crop from emergence through flowering to maturity, usually expressed as a rate (i.e. 1/duration), is largely controlled by temperature in the tropics.

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Flowering is a crucial determinant for plant reproductive success and seed-set. Increasing temperature and elevated carbon-dioxide (e[CO2]) are key climate change factors that could affect plant fitness and flowering related events. Addressing the effect of these environmental factors on flowering events such as time of day of anthesis (TOA) and flowering time (duration from germination till flowering) is critical to understand the adaptation of plants/crops to changing climate and is the major aim of this review.

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Background: Recent developments in unmanned aerial platforms (UAP) have provided research opportunities in assessing land allocation and crop physiological traits, including response to abiotic and biotic stresses. UAP-based remote sensing can be used to rapidly and cost-effectively phenotype large numbers of plots and field trials in a dynamic way using time series. This is anticipated to have tremendous implications for progress in crop genetic improvement.

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Post-rainy sorghum (Sorghum bicolor (L.) Moench) production underpins the livelihood of millions in the semiarid tropics, where the crop is affected by drought. Drought scenarios have been classified and quantified using crop simulation.

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