Crop establishment and diversification strategies for intensification of rice-based cropping systems in rice-fallow areas in Odisha.

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-1 compared to 6-8 t ha-1 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 beushening) 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, Vigna radiata; black gram, Vigna mungo), and oilseeds (Brassica rapa var. toria, Helianthus annuus) in rice-fallow areas in the dry season. Methods: On-farm experiments were conducted between 2017 and 2019 in three districts of Odisha (Bhadrak, Cuttack and Mayurbhanj) to evaluate DSR compared to beushening and PTR-R; and PTR-M compared to PTR-R and manual line puddled transplanted rice (PTR-L) in the wet season. The data from Landsat-8 Operational Land Imager (OLI) and Sentinel-1satellite sensors was used to identify rice-fallow areas, and the daily SMAP (Soil Moisture Active Passive) L-band soil moisture was used for mapping suitable rice-fallow areas for growing pulses and oilseeds. Short duration crops were evaluated in suitable rice-fallow areas. Results: In the wet season, DSR (range -4 to + 53%) had a significant effect on rice yield over beushening. Similarly, PTR-M consistently increased rice yield by 16-26% over PTR-R, and by 5-23% over PTR-L. In the dry season, pulse crops (green gram and black gram) performed well compared to Indian mustard under rainfed cultivation. However, under irrigated conditions, dry-season rice yield was more productive than the rice equivalent yield of green gram, black gram and sunflower. We found that 1.03 M ha (i.e., ∼50%) of total rice-fallow areas of 2.1 M ha were suitable for growing short duration green gram and black gram in the dry season. Conclusions: We conclude that system productivity and cropping intensity can be increased by adoption of DSR and PTR-M in the wet season, and growing of green gram and black gram in the dry season. Implications: Odisha state can potentially produce an additional 0.67 million tonnes pulses if suitable rice-fallow areas are brought under green gram and black gram cultivation in the dry the season.

Failure to scale in digital agronomy: An analysis of site-specific nutrient management decision-support tools in developing countries.

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 meta-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. Despite their acclaimed yield benefits, we find that SSNM-DST have struggled to reach scale over the last few decades and, with strong heterogeneity in adoption among intended stakeholders and tools. For example, the log odds of a SSNM-DST reaching 5-10 % of the target farmers compared with reaching none, decreases by âˆ¼200% when a technical problem is stated as a reason for the tools' failure to be used at scale. We find a similar decrease in odds ratios when technical, socioeconomic, policy, and R&D constraints were identified as barriers to scaling by national extension and private systems. Meta-regression analysis indicates that the response ratio of using SSNM-DST over Farmer Fertilizer Practice (FFP) varies by non-tool related covariates, such as initial crop yield potential under FFP, current and past crop types, acidity class of the soil, temperature and rainfall regimes, and the amount of input under FFP. In general, the SSNM-DST have moved one step forward compared with the traditional 'blanket' fertilizer recommendation by accounting for in-field heterogeneities in soil and crop characteristics, while remaining undifferentiated in terms of demographic and socioeconomic heterogeneities among users, which potentially constrains adoption at scale. The SSNM-DSTs possess reasonable applicability and can be labeled 'ready' from purely scientific viewpoints, although their readiness for system-level uptake at scale remains limited, especially where socio-technical and institutional constraints are prevalent.

Influence of conservation agriculture-based production systems on bacterial diversity and soil quality in rice-wheat-greengram cropping system in eastern Indo-Gangetic Plains of India.

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-cum-crop establishment (TCE) methods on earthworm population, soil parameters as well as microbial diversity have not been well studied. Methods: Seven treatments (or scenarios) were laid down with the various tillage (wet, dry, or zero-tillage), establishment method (direct-or drill-seeding or transplantation) and residue management practices (mixed with the soil or kept on the soil surface). The soil samples were collected after 7 years of experimentation and analyzed for the soil quality and bacterial diversity to examine the effect of tillage-cum-crop establishment methods. Results and Discussion: Earthworm population (3.6 times), soil organic carbon (11.94%), macro (NPK) (14.50-23.57%) and micronutrients (Mn, and Cu) (13.25 and 29.57%) contents were appreciably higher under CA-based TCE methods than tillage-intensive farming practices. Significantly higher number of OTUs (1,192 ± 50) and Chao1 (1415.65 ± 14.34) values were observed in partial CA-based production system (p ≤ 0.05). Forty-two (42) bacterial phyla were identified across the scenarios, and Proteobacteria, Actinobacteria, and Firmicutes were the most dominant in all the scenarios. The CA-based scenarios harbor a high abundance of Proteobacteria (2-13%), whereas the conventional tillage-based scenarios were dominated by the bacterial phyla Acidobacteria and Chloroflexi and found statistically differed among the scenarios (p ≤ 0.05). Composition of the major phyla, i.e., Proteobacteria, Actinobacteria, and Firmicutes were associated differently with either CA or farmers-based tillage management practices. Overall, the present study indicates the importance of CA-based tillage-cum-crop establishment methods in shaping the bacterial diversity, earthworms population, soil organic carbon, and plant nutrient availability, which are crucial for sustainable agricultural production and resilience in agro-ecosystem.

Farm size limits agriculture's poverty reduction potential in Eastern India even with irrigation-led intensification.

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. OBJECTIVE: The main objective of this study is to use a large household survey (n = 15,572; rice: 8244, wheat: 7328; 2017/18) to assess the link between agricultural intensification and personal daily incomes from farming (FPDI) in the rice-wheat systems of the EGP - the dominant cropping system of the region. METHODS: We use the Intensification Benefit Index (IBI), a measure that relates farm size and household size to FPDI, to assess how daily incomes from rice-wheat production change with irrigation-led intensification across the EGP. RESULTS AND CONCLUSIONS: Relative to the international poverty line of 1.90 Purchasing Power Parity (PPP)$ day-1 and accounting for variations in HH size in the analysis, we found that small farm sizes limit the potential for agricultural intensification from irrigation to transform the poverty status of households in the bottom three quartiles of the IBI. The estimated median FPDI of households with intensified systems in the bottom three quartiles is only 0.51 PPP$ day-1 (a 0.15 PPP$ gain). The median FPDI increases to 2.10 PPP$ day-1 for households in the upper quartile of the IBI distribution (a 0.30 PPP$ gain). Irrigation-led agricultural intensification of rice-wheat systems in the EGP may provide substantial benefits for resilience to climatic change and food security but achieving meaningful poverty reduction will require complementary investments. SIGNIFICANCE: Transforming the poverty status of most smallholder farmers in the EGP requires diversified portfolios of rural on- and off-farm income-generating opportunities. While bolstering food- and climate security, agronomic intervention programs should consider smallholders' limited monetary incentives to invest in intensification. Irrigation-led agricultural intensification programs and policies should explicitly account for the heterogeneity in household resources, irrigation levels, and degree of dependence on agricultural income.

Large survey dataset of rice production practices applied by farmers on their largest farm plot during 2018 in India.

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, n = 8355, covers eight Indian states, viz., Andhra Pradesh, Bihar, Chhattisgarh, Haryana, Odisha, Punjab, Uttar Pradesh and West Bengal. Sampling frames were constructed separately for each district within states and farmers were selected randomly. The survey was deployed in 49 districts with a maximum of 210 interviews per district. The digital survey form was available on mobile phones of trained enumerators and was designed to minimize data entry errors. Each survey captured approximately 225 variables around rice production practices of farmers' largest plot starting with land preparation, establishment method, crop variety and planting time through to crop yield. Detailed modules captured fertilizer application, irrigation, weed management, biotic and abiotic stresses. Additional information was gathered on household demographics and marketing. Geo-points were recorded for each surveyed plot with an accuracy of <10 m. This dataset is generated to bridge a data-gap in the national system and generates information about the adoption of technologies, as well as enabling prediction and other analytics. It can potentially be the basis for evidence-based agriculture programming by policy makers.

Time management governs climate resilience and productivity in the coupled rice-wheat cropping systems of eastern India.

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. Our findings also indicate that transformative gains in wheat yields are only possible in eastern India if rice and wheat are managed as a coupled system. Steps taken to 'keep time' through better management of the annual cropping calendar will pay dividends for food security, profitability and climate resilience now and as a foundation for adaptation to progressive climate change.

How accurate are yield estimates from crop cuts? Evidence from smallholder maize farms in Ethiopia.

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. We compare yield from a full plot harvest with farmer assessments and with estimates from a variety of field sampling protocols: W-walk, transect, random quadrant, random octant, center quadrant, and 3 diagonal quadrants. We find that protocol choices are important: alternative protocols vary considerably in their accuracy relative to the whole plot, with absolute mean errors ranging from 23 (farmer estimates) to 10.6 (random octant). Furthermore, while most methods approximate the sample mean reasonably well, the divergence of individual measures from true plot-level values can be considerable. We find that randomly positioned quadrants outperform systematic sampling schemes: the random octant had the best accuracy and was the most cost-effective. The nature of bias is non-classical: bias is correlated with plot size as well as with plot management characteristics. In summary, our results advocate that even "gold standard" crop cut measures should be interpreted cautiously, and more empirical work should be carried out to validate and extend our conclusions.

Understanding decision processes in becoming a fee-for-hire service provider: A case study on direct seeded rice in Bihar, India.

While Direct Seeded Rice (DSR) has numerous potential benefits to smallholder farmers in the Eastern Gangetic Plains of South Asia, it's out-scaling has been limited by both a lack of demand by farmers and limited supply of DSR services by machinery owners. This contrasts with the comparatively more rapid scaling of zero tillage wheat in the region. This trend is yet to be fully explored, particularly when focus has been placed almost exclusively on understanding DSR adoption though the lens of farm-level agronomic, economic and environmental performance. Given that limited DSR service provision is likely to be governed outside of these considerations, this study explores with zero tillage drill owners the decision processes they apply in deciding how to use their zero tillage drills. Respondents highlight a complex web of interrelated considerations that highlight the additional complexities of DSR as compared to existing practices. Using a novel 'Decision-making Dartboard' qualitative framework, these complexities are unpacked and a set of potential changes to the assumed theory of change for DSR scaling are identified, including considerations for selection of potential DSR service providers and responsibilities for promotion and extension of DSR to overcome the prevalent negative perceptions of DSR held broadly across the communities explored. The proposed framework and analysis process are also potentially useful for exploration of other farmer decision making processes more broadly.

Implications of intra-plot heterogeneity for yield estimation accuracy: Evidence from smallholder maize systems in Ethiopia.

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. We surveyed agronomic decisions, biophysical variables, and accessibility characteristics of the surveyed fields. We quantify intra-plot heterogeneity using the coefficient of variation (CV) of stand density, cob weight, and maize grain yield. A generalized linear mixed model is used to explore the relationship between these variables and the method- and heterogeneity-dependence of yield estimation accuracy. We find inter-plot CV values ranging from 32 to 56 %, 22 to 73 % and 39 to 49 % in population density, cob weight and grain yield, respectively. Intra-plot heterogeneity constituted most of this variation, with across-method mean CV values of 41 %, 82 % and 63 %, respectively, of the total variability in population density, cob weight and grain yield. A rise in intra-plot heterogeneity of 0.5 % to 0.8 % is associated with a significant increase in yield estimation error under alternative yield estimation protocols. Regression analysis shows that interactions in agronomic decisions, input intensity and plot accessibility factors dictate intra-plot heterogeneity and method accuracy in smallholder systems. Intra-plot heterogeneity is larger than inter-plot heterogeneity in the current study area. Our analysis shows that the effect of intra-plot heterogeneity on yield estimation accuracies is method-dependent and yield estimation methods that fail to capture true intra-plot heterogeneity are more error-prone. Results of such estimations should be considered with caution when used as the basis of decision-making.

In pursuit of a better world: crop improvement and the CGIAR.

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. The importance of multidisciplinary teams working towards common objectives is stressed as a key factor to success. The role of the distinct disciplines, actors, and their interactions throughout the process from crop choice through to adoption by farmers is discussed and illustrated.

Agricultural labor, COVID-19, and potential implications for food security and air quality in the breadbasket of India.

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. The timing of rice transplanting at the beginning of the summer monsoon season has a cascading influence on productivity of the entire rice-wheat cropping system. To assess the potential for COVID-related reductions in the agriculture workforce to disrupt production of the dominant rice-wheat cropping pattern in these states, we use a spatial ex ante modelling framework to evaluate four scenarios representing a range of plausible labor constraints on the timing of rice transplanting. Averaged over both states, results suggest that rice productivity losses under all delay scenarios would be low as compare to those for wheat, with total system productivity loss estimates ranging from 9%, to 21%, equivalent to economic losses of USD $674 m to $1.48 billion. Late rice transplanting and harvesting can also aggravate winter air pollution with concomitant health risks. Technological options such as direct seeded rice, staggered nursery transplanting, and crop diversification away from rice can help address these challenges but require new approaches to policy and incentives for change.

Gender differentiated small-scale farm mechanization in Nepal hills: An application of exogenous switching treatment regression.

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. Our findings reveal that there is a significant gender gap in mini-tiller adoption between male-headed households (MH-HHs) and female-headed households (FH-HHs). Compared to MH-HHs, the mini-tiller adoption rate is significantly lower among the FH-HHs, and a large amount of unobserved heterogeneity is deriving this difference. Moreover, when MH-HHs and FH-HHs have similar observed attributes, the mini-tiller adoption rate among the food insecure FH-HHs is higher than in the food secure group. The gender-differentiated mini-tiller adoption rate can be minimized primarily by enhancing market access. Findings suggest that farm mechanization policies and programs targeted to the FH-HHs can reduce the gender-differentiated adoption gap in Nepal and similar hill production agro-ecologies in South Asia, which will enhance the farm yield and profitability.

Science-based decision support for formulating crop fertilizer recommendations in sub-Saharan Africa.

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. Nutrient Expert (NE) is a computer-based decision support system, which enables extension advisers to generate field- or area-specific fertilizer recommendations based on yield response to fertilizer and nutrient use efficiency. We calibrated NE for major maize agroecological zones in Nigeria, Ethiopia and Tanzania, with data generated from 735 on-farm nutrient omission trials conducted between 2015 and 2017. Between 2016 and 2018, 368 NE performance trials were conducted across the three countries in which recommendations generated with NE were evaluated relative to soil-test based recommendations, the current blanket fertilizer recommendations and a control with no fertilizer applied. Although maize yield response to fertilizer differed with geographic location; on average, maize yield response to nitrogen (N), phosphorus (P) and potassium (K) were respectively 2.4, 1.6 and 0.2 t ha-1 in Nigeria, 2.3, 0.9 and 0.2 t ha-1 in Ethiopia, and 1.5, 0.8 and 0.2 t ha-1 in Tanzania. Secondary and micronutrients increased maize yield only in specific areas in each country. Agronomic use efficiencies of N were 18, 22 and 13 kg grain kg-1 N, on average, in Nigeria, Ethiopia and Tanzania, respectively. In Nigeria, NE recommended lower amounts of P by 9 and 11 kg ha-1 and K by 24 and 38 kg ha-1 than soil-test based and regional fertilizer recommendations, respectively. Yet maize yield (4 t ha-1) was similar among the three methods. Agronomic use efficiencies of P and K (300 and 250 kg kg-1, respectively) were higher with NE than with the blanket recommendation (150 and 70 kg kg-1). In Ethiopia, NE and soil-test based respectively recommended lower amounts of P by 8 and 19 kg ha-1 than the blanket recommendations, but maize yield (6 t ha-1) was similar among the three methods. Overall, fertilizer recommendations generated with NE maintained high maize yield, but at a lower fertilizer input cost than conventional methods. NE was effective as a simple and cost-effective decision support tool for fine-tuning fertilizer recommendations to farm-specific conditions and offers an alternative to soil testing, which is hardly available to most smallholder farmers.

Transforming labor requirement, crop yield, and profitability with precision dry-direct seeding of rice and integrated weed management in Eastern India.

In many parts of Eastern India that have a very high prevalence of rural poverty and food insecurity, the prevailing rice establishment practice of 'beushening' is characterized by low yields and modest profitability, while labor and energy inputs are high. Beushening consists of broadcasting ungerminated rice seed at high rates (>100 kg ha-1) 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. On-farm trials were conducted from 2016 to 2018 in four districts of Odisha (Mayurbhanj, Cuttack, Bhadrak, and Puri) to evaluate the yield and economic performance of dry-DSR (drill and precision broadcast), coupled with herbicide-based IWM strategies, in comparison with conventional beushening. Drill-DSR with IWM increased grain yield by 1.7 t ha-1 in Mayurbhanj and 1.3 t ha-1 in Cuttack, but not in Bhadrak, compared to beushening. The combination of increased yield and lower variable cost in drill-DSR increased net benefit by 550, 395, and 166 US$ ha-1 in Mayurbhanj, Cuttack, and Bhadrak, respectively. For farmers without access to seed drills, precision broadcast-DSR with IWM increased yields by 0.91, 1.22 and 0.60 t ha-1, and net benefits by 270, 312, and 188 US$ ha-1 in Mayurbhanj, Puri, and Bhadrak, respectively. Among the IWM practices evaluated in dry-DSR, application of pretilachlor + safener @ 500 g ai ha-1 as pre-emergence, followed by bispyribac-sodium @ 20 g ai ha-1 at 15-25 days after sowing as post-emergence, and then one spot hand weeding at 30-35 days after sowing was effective in controlling weeds. These results suggest that rice yield gaps in eastern India can be reduced, and farmers' income from rice can be increased by more than 50 % by replacing beushening with drill-DSR or precision broadcast-DSR. The results could be applicable to approximately 6.4 million ha of lowland rice where beushening is currently practiced in Eastern India.

Farmers' preferences for high-input agriculture supported by site-specific extension services: Evidence from a choice experiment in Nigeria.

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. We use a choice experiment to provide ex-ante insights on the adoption potentials of site-specific extension services from the perspective of farmers. We control for attribute non-attendance and account for class as well as scale heterogeneity in preferences using different models, and find robust results. We find that farmers have strong preferences to switch from general to ICT-enabled site-specific soil fertility management recommendations which lend credence to the inclusion of digital technologies in agricultural extension. We find heterogeneity in preferences that is correlated with farmers' resource endowments and access to services. A first group of farmers are strong potential adopters; they are better-off, less sensitive to risk, and are more willing to invest in a high-input maize production system. A second group of farmers are weak potential adopters; they have lower incomes and fewer productive assets, are more sensitive to yield variability, and prefer less capital and labor intensive production techniques. Our empirical findings imply that improving the design of extension tools to enable provision of information on the riskiness of expected outcomes and flexibility in switching between low-risk and high-risk recommendations will help farmers to make better informed decisions, and thereby improve the uptake of extension advice and the efficiency of extension programs.

Balanced nutrient requirements for maize in the Northern Nigerian Savanna: Parameterization and validation of QUEFTS model.

Establishing balanced nutrient requirements for maize (Zea mays 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. Data from on-farm nutrient omission trials conducted in 2015 and 2016 rainy seasons in two agro-ecological zones in the Northern Nigerian Savanna (i.e. Northern Guinea Savanna "NGS" and Sudan Savanna "SS") were used to parameterize and validate the QUEFTS model. The relations between indigenous soil N, P, and K supply and soil properties were not well described with the QUEFTS default equations and consequently new and better fitting equations were derived. The parameters of maximum accumulation (a) and dilution (d) in kg grain per kg nutrient for the QUEFTS model obtained were respectively 35 and 79 for N, 200 and 527 for P and 25 and 117 for K in the NGS zone; 32 and 79 for N, 164 and 528 for P and 24 and 136 for K in the SS zone; and 35 and 79 for N, 199 and 528 for P and 24 and 124 for K when the data of the two zones were combined. There was a close agreement between observed and parameterized QUEFTS predicted yields in each of the agro-ecological zone (R2 = 0.69 for the NGS and 0.75 for the SS). Although with a slight reduction in the prediction power, a good fit between the observed and model predicted grain yield was also detected when the data for the two agro-ecological zones were combined (R2 = 0.67). Therefore, across the two agro-ecological zones, the model predicted a linear relationship between grain yield and above-ground nutrient uptake until yield reached about 50 to 60% of the yield potential. When the yield target reached 60% of the potential yield (i.e. 6.0 t ha-1), the model showed above-ground balanced nutrient uptake of 20.7, 3.4 and 27.1 kg N, P, and K, respectively, per one tonne of maize grain. These results suggest an average NPK ratio in the plant dry matter of about 6.1:1:7.9. We concluded that the QUEFTS model can be widely used for balanced nutrient requirement estimations and development of site-specific fertilizer recommendations for maize intensification in the Northern Nigerian Savanna.

Methodological approach for predicting and mapping the phenological adaptation of tropical maize (Zea mays L.) using multi-environment trials.

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. Maize plant phenological responses vary between varieties and quantifying these responses can help in predicting the timing and duration of critical periods for crop growth that affect the quality and quantity of seed. We used routine multi-environment trials data of diverse tropical maize varieties to: (1) fit 82 temperature dependent phenology models and select the best model for an individual variety, (2) develop a spatial framework that uses the phenology model to predict at landscape level the length of the vegetative and reproductive phases of diverse varieties of maize in different agro-ecologies. Multi-environment trial data of 22 maize varieties from 16 trials in Kenya, Ethiopia, and Sudan was analyzed and the Levenberg-Marquardt algorithm combined with statistical criteria was applied to determine the best temperature-dependent model. RESULTS: The Briere model, which is not often used in plant phenology, provided the best fit, with observed and predicted days to flowering showing good agreement. Linking the model with temperature and scaling out through mapping gave the duration from emergence to maturity of different maize varieties in areas where maize could potentially be grown. CONCLUSION: The methodology and framework used in the study provides an opportunity to develop tools that enhance farmers' ability to predict stages of maize development for efficient crop management decisions and assessment of climate change impacts. This methodology could contribute to increase maize production if used to identify varieties with desired maturity for a specific agro-ecology in in the targeted regions.

Implications of High Temperature and Elevated CO2 on Flowering Time in Plants.

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. Increasing ambient temperature is the major climatic factor that advances flowering time in crops and other plants, with a modest effect of e[CO2].Integrated environmental stimuli such as photoperiod, temperature and e[CO2] regulating flowering time is discussed. The critical role of plant tissue temperature influencing TOA is highlighted and crop models need to substitute ambient air temperature with canopy or floral tissue temperature to improve predictions. A complex signaling network of flowering regulation with change in ambient temperature involving different transcription factors (PIF4, PIF5), flowering suppressors (HvODDSOC2, SVP, FLC) and autonomous pathway (FCA, FVE) genes, mainly from Arabidopsis, provides a promising avenue to improve our understanding of the dynamics of flowering time under changing climate. Elevated CO2 mediated changes in tissue sugar status and a direct [CO2]-driven regulatory pathway involving a key flowering gene, MOTHER OF FT AND TFL1 (MFT), are emerging evidence for the role of e[CO2] in flowering time regulation.

Modelling the effect of plant water use traits on yield and stay-green expression in sorghum.

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. In this report, variation in traits that hypothetically contribute to drought adaptation (plant growth dynamics, canopy and root water conducting capacity, drought stress responses) were virtually introgressed into the most common post-rainy sorghum genotype, and the influence of these traits on plant growth, development, and grain and stover yield were simulated across different scenarios. Limited transpiration rates under high vapour pressure deficit had the highest positive effect on production, especially combined with enhanced water extraction capacity at the root level. Variability in leaf development (smaller canopy size, later plant vigour or increased leaf appearance rate) also increased grain yield under severe drought, although it caused a stover yield trade-off under milder stress. Although the leaf development response to soil drying varied, this trait had only a modest benefit on crop production across all stress scenarios. Closer dissection of the model outputs showed that under water limitation, grain yield was largely determined by the amount of water availability after anthesis, and this relationship became closer with stress severity. All traits investigated increased water availability after anthesis and caused a delay in leaf senescence and led to a 'stay-green' phenotype. In conclusion, we showed that breeding success remained highly probabilistic; maximum resilience and economic benefits depended on drought frequency. Maximum potential could be explored by specific combinations of traits.

A phenotypic marker for quantifying heat stress impact during microsporogenesis in rice (Oryza sativa L.).

Gametogenesis in rice (Oryza sativa L.), and particularly male gametogenesis, is a critical developmental stage affected by different abiotic stresses. Research on this stage is limited, as flowering stage has been the major focus for research to date. Our main objective was to identify a phenotypic marker for male gametogenesis and the duration of exposure needed to quantify the impact of heat stress at this stage. Spikelet size coinciding with microsporogenesis was identified using parafilm sectioning, and the panicle (spikelet) growth rate was established. The environmental stability of the marker was ascertained with different nitrogen (75 and 125kg ha-1) and night temperature (22°C and 28°C) combinations under field conditions. A distance of -8 to -9cm between the collar of the last fully opened leaf and the flag leaf collar, which was yet to emerge was identified as the environmentally stable phenotypic marker. Heat stress (38°C) imposed using the identified marker induced 8-63% spikelet sterility across seven genetically diverse rice genotypes. Identifying the right stage based on the marker information and imposing 6 consecutive days of heat stress ensures that >95% of the spikelets in a panicle are stressed spanning across the entire microsporogenesis stage.