Economics of crop residue management

Vijesh Krishna Maxwell Mkondiwa (2023)

More than five billion metric tons of agricultural residues are produced annually worldwide. Despite having multiple uses and significant potential to augment crop and livestock production, a large share of crop residues is burned, especially in Asian countries. This unsustainable practice causes tremendous air pollution and health hazards while restricting soil nutrient recycling. In this review, we examine the economic rationale for unsustainable residue management. The sustainability of residue utilization is determined by several economic factors, such as local demand for and quantity of residue production, development and dissemination of technologies to absorb excess residue, and market and policy instruments to internalize the social costs of residue burning. The intervention strategy to ensure sustainable residue management depends on public awareness of the private and societal costs of open residue burning.

Article

Crop Biomass Residue Burning Environmental Effects CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA CROPS BIOMASS RESIDUES ENVIRONMENTAL IMPACT CLIMATE CHANGE SMALLHOLDERS TECHNOLOGY ADOPTION

Agroecology can promote climate change adaptation outcomes without compromising yield in smallholder systems

Sieglinde Snapp Yodit Kebede Eva Wollenberg (2023)

A critical question is whether agroecology can promote climate change mitigation and adaptation outcomes without compromising food security. We assessed the outcomes of smallholder agricultural systems and practices in low- and middle-income countries (LMICs) against 35 mitigation, adaptation, and yield indicators by reviewing 50 articles with 77 cases of agroecological treatments relative to a baseline of conventional practices. Crop yields were higher for 63% of cases reporting yields. Crop diversity, income diversity, net income, reduced income variability, nutrient regulation, and reduced pest infestation, indicators of adaptative capacity, were associated with 70% or more of cases. Limited information on climate change mitigation, such as greenhouse gas emissions and carbon sequestration impacts, was available. Overall, the evidence indicates that use of organic nutrient sources, diversifying systems with legumes and integrated pest management lead to climate change adaptation in multiple contexts. Landscape mosaics, biological control (e.g., enhancement of beneficial organisms) and field sanitation measures do not yet have sufficient evidence based on this review. Widespread adoption of agroecological practices and system transformations shows promise to contribute to climate change services and food security in LMICs. Gaps in adaptation and mitigation strategies and areas for policy and research interventions are finally discussed.

Article

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA CLIMATE CHANGE CROPS FOOD SUPPLY GAS EMISSIONS GREENHOUSE GASES FARMING SYSTEMS AGROECOLOGY FOOD SECURITY LESS FAVOURED AREAS SMALLHOLDERS YIELDS NUTRIENTS BIOLOGICAL PEST CONTROL CARBON SEQUESTRATION LEGUMES

Modular ontology to support manufacturing SMEs toward industry 4.0

ZAIDA ANTONIETA MORA ALVAREZ OSCAR HERNANDEZ URIBE RAMON ALBERTO LUQUE MORALES LEONOR ADRIANA CARDENAS ROBLEDO (2023)

Industry 4.0 (I4.0) implementation is a hot topic among manufacturing organizations to reach smart factory status and integrate a fully connected ecosystem. Achieving such a transition presents notable challenges for Small and Medium Enterprises (SMEs) since they often face resource and skilled personnel limitations. This study developed a domain ontology to represent various stages of maturity toward I4.0 implementation. Ontology provides a tool for SMEs to self-assess in situations of machines, processes, and factories for the dimensions of control, integration, and intelligence. This study focused on the identification of classes and relationships according to I4.0 implementation situations in the context of a manufacturing setting, the reuse of ontologies related to the domain of observations to model situations, and the creation and validation of the ontology through the information obtained from the questionnaires applied to SMEs. Finally, the ontology delivers a tool to understand SMEs' current state concerning I4.0 implementation and plan based on informed decisions about the maturity state and the technology required to advance to the next stage in their manufacturing processes.

This study was partially supported by the grants CONAHCYT-CIATEQ CVU 899567 and 162867 and CONAHCYT SNI.

We express our gratitude to Teresa Novales Hernandez for the library support.

Article

Domain ontology Industry 4.0 SMEs Smart factory SPARQL Semantic web INGENIERÍA Y TECNOLOGÍA CIENCIAS TECNOLÓGICAS OTRAS ESPECIALIDADES TECNOLÓGICAS OTRAS OTRAS

Towards gender-inclusive innovation: Assessing local conditions for agricultural targeting

Diana E. Lopez Romain Frelat Lone Badstue (2022)

Article

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA AGRICULTURE CLIMATE FEMALES GENDER HUMANS GENDER EQUALITY

Multicriteria assessment of alternative cropping systems at farm level. A case with maize on family farms of South East Asia

Santiago Lopez-Ridaura (2023)

CONTEXT: Integration of farms into markets with adoption of maize as a cash crop can significantly increase income of farms of the developing world. However, in some cases, the income generated may still be very low and maize production may also have strong negative environmental and social impacts. OBJECTIVE: Maize production in northern Laos is taken as a case to study how far can farms' performance be improved with improved crop management of maize with the following changes at field level: good timing and optimal soil preparation and sowing, allowing optimal crop establishment and low weed infestation. METHODS: We compared different farm types' performance on locally relevant criteria and indicators embodying the three pillars of sustainability (environmental, economic and social). An integrated assessment approach was combined with direct measurement of indicators in farmers' fields to assess eleven criteria of local farm sustainability. A bio-economic farm model was used for scenario assessment in which changes in crop management and the economic environment of farms were compared to present situation. The farm model was based on mathematical programming maximizing income under constraints related to i) household composition, initial cash and rice stocks and land type, and ii) seasonal balances of cash, labour and food. The crop management scenarios were built based on a diagnosis of the causes of variations in the agronomic and environmental performances of cropping systems, carried out in farmers' fields. RESULTS AND CONCLUSIONS: Our study showed that moderate changes in crop management on maize would improve substantially farm performance on 4 to 6 criteria out of the 11 assessed, depending on farm types. The improved crop management of maize had a high economic attractiveness for every farm type simulated (low, medium and high resource endowed farms) even at simulated production costs more than doubling current costs of farmers' practices. However, while an improvement of the systems performance was attained in terms of agricultural productivity, income generation, work and ease of work, herbicide leaching, improved soil quality and nitrogen balance, trade-offs were identified with other indicators such as erosion control and cash outflow needed at the beginning of the cropping season. SIGNIFICANCE: Using farm modelling for multicriteria assessment of current and improved maize cropping systems for contrasted farm types helped capture main opportunities and constraints on local farm sustainability, and assess the trade-offs that new options at field level may generate at farm level.

Article

Bio-Economic Farm Model Smallholder Farms CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA CASH CROPS INDICATORS SMALLHOLDERS CROPPING SYSTEMS MAIZE

Emmer wheat eco-geographic and genomic congruence shapes phenotypic performance under mediterranean climate

Dana Fuerst SHAILESH YADAV Rajib Roychowdhury Carolina Sansaloni Sariel Hübner (2022)

Article

Emmer Wheat CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA WHEAT GENETIC VARIATION CLIMATE PHENOLOGY YIELDS MEDITERRANEAN CLIMATE

Editorial: Conservation agriculture: knowledge frontiers around the world

Stéphane Cordeau ML JAT Cameron Pittelkow Christian Thierfelder (2023)

Article

No-Tillage Direct Seeding Cover Crops Crop Diversification CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA COVER PLANTS DIVERSIFICATION CROPPING SYSTEMS DIRECT SOWING ZERO TILLAGE

Agricultural value chains in Sudan: an annotated bibliography

Hugo De Groote Paswel Marenya (2023)

Book

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA AGRICULTURAL VALUE CHAINS CASH CROPS FOOD CROPS LIVESTOCK SOCIOECONOMIC ASPECTS GENDER SOCIAL INCLUSION POSTHARVEST LOSSES BIBLIOGRAPHIES

A Novel Technique for Classifying Bird Damage to Rapeseed Plants Based on a Deep Learning Algorithm.

Ali Mirzazadeh Afshin Azizi Yousef Abbaspour_Gilandeh José Luis Hernández-Hernández Mario Hernández Hernández Iván Gallardo Bernal (2021)

Estimation of crop damage plays a vital role in the management of fields in the agricultura sector. An accurate measure of it provides key guidance to support agricultural decision-making systems. The objective of the study was to propose a novel technique for classifying damaged crops based on a state-of-the-art deep learning algorithm. To this end, a dataset of rapeseed field images was gathered from the field after birds¿ attacks. The dataset consisted of three classes including undamaged, partially damaged, and fully damaged crops. Vgg16 and Res-Net50 as pre-trained deep convolutional neural networks were used to classify these classes. The overall classification accuracy reached 93.7% and 98.2% for the Vgg16 and the ResNet50 algorithms, respectively. The results indicated that a deep neural network has a high ability in distinguishing and categorizing different image-based datasets of rapeseed. The findings also revealed a great potential of Deep learning-based models to classify other damaged crops.

Article

rapeseed classification damaged crops deep neural networks INGENIERÍA Y TECNOLOGÍA CIENCIAS TECNOLÓGICAS TECNOLOGÍA DE LOS ALIMENTOS

Distribution of Puccinia striiformis f. sp. tritici races and virulence in wheat growing regions of Kenya from 1970 to 2014

Lesley Boyd sridhar bhavani Cristobal Uauy Annemarie Fejer Justesen Mogens Hovmoller (2022)

Article

Cereals and Grains Pathogen Diversity Puccinia f. sp. tritici Stripe Rust Yellow Rust CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA CEREALS FIELD CROPS FUNGI PATHOGENICITY RUSTS TRITICUM AESTIVUM