The input reduction principle of agroecology is wrong when it comes to mineral fertilizer use in sub-Saharan Africa

Gatien Falconnier Marc Corbeels Frédéric Baudron Antoine Couëdel leonard rusinamhodzi bernard vanlauwe Ken Giller (2023, [Artículo])

Can farmers in sub-Saharan Africa (SSA) boost crop yields and improve food availability without using more mineral fertilizer? This question has been at the center of lively debates among the civil society, policy-makers, and in academic editorials. Proponents of the “yes” answer have put forward the “input reduction” principle of agroecology, i.e. by relying on agrobiodiversity, recycling and better efficiency, agroecological practices such as the use of legumes and manure can increase crop productivity without the need for more mineral fertilizer. We reviewed decades of scientific literature on nutrient balances in SSA, biological nitrogen fixation of tropical legumes, manure production and use in smallholder farming systems, and the environmental impact of mineral fertilizer. Our analyses show that more mineral fertilizer is needed in SSA for five reasons: (i) the starting point in SSA is that agricultural production is “agroecological” by default, that is, very low mineral fertilizer use, widespread mixed crop-livestock systems and large crop diversity including legumes, but leading to poor soil fertility as a result of widespread soil nutrient mining, (ii) the nitrogen needs of crops cannot be adequately met solely through biological nitrogen fixation by legumes and recycling of animal manure, (iii) other nutrients like phosphorus and potassium need to be replaced continuously, (iv) mineral fertilizers, if used appropriately, cause little harm to the environment, and (v) reducing the use of mineral fertilizers would hamper productivity gains and contribute indirectly to agricultural expansion and to deforestation. Yet, the agroecological principles directly related to soil fertility—recycling, efficiency, diversity—remain key in improving soil health and nutrient-use efficiency, and are critical to sustaining crop productivity in the long run. We argue for a nuanced position that acknowledges the critical need for more mineral fertilizers in SSA, in combination with the use of agroecological practices and adequate policy support.

Manure Crop Yields Smallholder Farming Systems Environmental Hazards CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA BIOLOGICAL NITROGEN FIXATION LEGUMES NUTRIENT BALANCE SOIL FERTILITY AGROECOLOGY YIELD INCREASES LITERATURE REVIEWS

Smallholder maize yield estimation using satellite data and machine learning in Ethiopia

Zhe Guo Jordan Chamberlin Liangzhi You (2023, [Artículo])

The lack of timely, high-resolution data on agricultural production is a major challenge in developing countries where such information can guide the allocation of scarce resources for food security, agricultural investment, and other objectives. While much research has suggested that remote sensing can potentially help address these gaps, few studies have indicated the immediate potential for large-scale estimations over both time and space. In this study we described a machine learning approach to estimate smallholder maize yield in Ethiopia, using well-measured and broadly distributed ground truth data and freely available spatiotemporal covariates from remote sensing. A neural networks model outperformed other algorithms in our study. Importantly, our work indicates that a model developed and calibrated on a previous year's data could be used to reasonably estimate maize yield in the subsequent year. Our study suggests the feasibility of developing national programs for the routine generation of broad-scale and high-resolution estimates of smallholder maize yield, including seasonal forecasts, on the basis of machine learning algorithms, well-measured ground control data, and currently existing time series satellite data.

Sentinel-2 Smallholder Agriculture Yield Prediction CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA INTENSIFICATION SMALLHOLDERS AGRICULTURE YIELD FORECASTING

Using microsatellite data to estimate the persistence of field-level yield gaps and their drivers in smallholder systems

Balwinder-Singh Meha Jain (2023, [Artículo])

One way to meet growing food demand is to increase yields in regions that have large yield gaps, including smallholder systems. To do this, it is important to quantify yield gaps, their persistence, and their drivers at large spatio-temporal scales. Here we use microsatellite data to map field-level yields from 2014 to 2018 in Bihar, India and use these data to assess the magnitude, persistence, and drivers of yield gaps at the landscape scale. We find that overall yield gaps are large (33% of mean yields), but only 17% of yields are persistent across time. We find that sowing date, plot area, and weather are the factors that most explain variation in yield gaps across our study region, with earlier sowing associated with significantly higher yield values. Simulations suggest that if all farmers were able to adopt ideal management strategies, including earlier sowing and more irrigation use, yield gaps could be closed by up to 42%. These results highlight the ability of micro-satellite data to understand yield gaps and their drivers, and can be used to help identify ways to increase production in smallholder systems across the globe.

Yield Drivers Yield Mapping CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA MICROSATELLITES YIELD GAP SMALLHOLDERS FOOD PRODUCTION YIELD INCREASES

High Throughput-Phenotyping at CIMMYT: Experiences and needs

Francisco Pinto (2021, [Objeto de congreso])

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA BREEDING PROGRAMMES GENETIC GAIN CROSS-BREEDING TECHNOLOGY YIELD POTENTIAL FIELD EXPERIMENTATION

A 'wiring diagram' for sink strength traits impacting wheat yield potential

Gustavo Slafer John Foulkes Matthew Paul Reynolds Erik Murchie A Elizabete Carmo-Silva Simon Griffiths (2023, [Artículo])

Grain Number Grain Weight Yield Physiology CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA BREEDING GRAIN HARVEST INDEX SOURCE SINK RELATIONS YIELD COMPONENTS WHEAT

MLN disease diagnostics, surveillance, MLN disease-free seed production, and MLN disease management

Suresh L.M. (2022, [Objeto de congreso])

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA DISEASES DISEASE MANAGEMENT SEED PRODUCTION MAIZE NECROSIS YIELD LOSSES ECONOMIC IMPACT SURVEILLANCE SYSTEMS TRAINING

Identification and validation of stable quantitative trait loci for yield component traits in wheat

Yong Zhang Zhonghu He xianchun xia Yan Zhang Shuanghe Cao (2023, [Artículo])

Grain Number Per Spike KASP Markers QTL Mapping Thousand Grain Weight CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA QUANTITATIVE TRAIT LOCI MAPPING TRITICUM AESTIVUM GRAIN YIELD COMPONENTS MARKER-ASSISTED SELECTION

Genetic effects of Rht-B1b and Rht-D1b dwarfing alleles on plant height and agronomic traits of bread wheat (Triticum aestivum L.) breeding lines

Zine El Abidine Fellahi Abderrahmane Hannachi Susanne Dreisigacker deepmala sehgal Hamenna Bouzerzour (2023, [Artículo])

Pleiotropic Effects Reduced Height Genes CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA PLANT HEIGHT TRITICUM AESTIVUM YIELD COMPONENTS ALLELES BREEDING LINES

Mapping QTL for phenological and grain-related traits in a mapping population derived from high-zinc-biofortified wheat

Gopalareddy Krishnappa Govindan Velu (2023, [Artículo])

DArT-Seq Gene Mapping Yield Component Traits CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA WHEAT QUANTITATIVE TRAIT LOCI CANDIDATE GENES QUANTITATIVE TRAIT LOCI MAPPING YIELD COMPONENTS BIOFORTIFICATION

Catching-up with genetic progress: Simulation of potential production for modern wheat cultivars in the Netherlands

João Vasco Silva Frits K. Van Evert Pytrik Reidsma (2023, [Artículo])

Context: Wheat crop growth models from all over the world have been calibrated on the Groot and Verberne (1991) data set, collected between 1982 and 1984 in the Netherlands, in at least 28 published studies to date including various recent ones. However, the recent use of this data set for calibration of potential yield is questionable as actual Dutch winter wheat yields increased by 3.1 Mg ha-1 over the period 1984 – 2015. A new comprehensive set of winter wheat experiments, suitable for crop model calibration, was conducted in Wageningen during the growing seasons of 2013–2014 and of 2014–2015. Objective: The present study aimed to quantify the change of winter wheat variety traits between 1984 and 2015 and to examine which of the identified traits explained the increase in wheat yield most. Methods: PCSE-LINTUL3 was calibrated on the Groot and Verberne data (1991) set. Next, it was evaluated on the 2013–2015 data set. The model was further recalibrated on the 2013–2015 data set. Parameter values of both calibrations were compared. Sensitivity analysis was used to assess to what extent climate change, elevated CO2, changes in sowing dates, and changes in cultivar traits could explain yield increases. Results: The estimated reference light use efficiency and the temperature sum from anthesis to maturity were higher in 2013–2015 than in 1982–1984. PCSE-LINTUL3, calibrated on the 1982–1984 data set, underestimated the yield potential of 2013–2015. Sensitivity analyses showed that about half of the simulated winter wheat yield increase between 1984 and 2015 in the Netherlands was explained by elevated CO2 and climate change. The remaining part was explained by the increased temperature sum from anthesis to maturity and, to a smaller extent, by changes in the reference light use efficiency. Changes in sowing dates, biomass partitioning fractions, thermal requirements for anthesis, and biomass reallocation did not explain the yield increase. Conclusion: Recalibration of PCSE-LINTUL3 was necessary to reproduce the high wheat yields currently obtained in the Netherlands. About half of the reported winter wheat yield increase was attributed to climate change and elevated CO2. The remaining part of the increase was attributed to changes in the temperature sum from anthesis to maturity and, to a lesser extent, the reference light use efficiency. Significance: This study systematically addressed to what extent changes in various cultivar traits, climate change, and elevated CO2 can explain the winter wheat yield increase observed in the Netherlands between 1984 and 2015.

Light Use Efficiency Potential Yield CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA CROP MODELLING LIGHT PHENOLOGY MAXIMUM SUSTAINABLE YIELD TRITICUM AESTIVUM WINTER WHEAT