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Santiago Lopez-Ridaura (2023, [Artículo])
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.
Bio-Economic Farm Model Smallholder Farms CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA CASH CROPS INDICATORS SMALLHOLDERS CROPPING SYSTEMS MAIZE
Editorial: Model organisms in plant science: Maize
Manje Gowda (2023, [Artículo])
Model Organism Genomic Selection CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA MAIZE PLANT SCIENCES RESEARCH CROP IMPROVEMENT PLANT PHYSIOLOGY PLANT BREEDING
Impact of manures and fertilizers on yield and soil properties in a rice-wheat cropping system
Alison Laing Akbar Hossain (2023, [Artículo])
The use of chemical fertilizers under a rice-wheat cropping system (RWCS) has led to the emergence of micronutrient deficiency and decreased crop productivity. Thus, the experiment was conducted with the aim that the use of organic amendments would sustain productivity and improve the soil nutrient status under RWCS. A three-year experiment was conducted with different organic manures i.e. no manure (M0), farmyard manure@15 t ha-1 (M1), poultry manure@6 t ha-1(M2), press mud@15 t ha-1(M3), rice straw compost@6 t ha-1(M4) along with different levels of the recommended dose of fertilizer (RDF) i.e. 0% (F1), 75% (F2 and 100% (F3 in a split-plot design with three replications and plot size of 6 m x 1.2 m. Laboratory-based analysis of different soil as well as plant parameters was done using standard methodologies. The use of manures considerably improved the crop yield, macronutrients viz. nitrogen, phosphorus, potassium and micronutrients such as zinc, iron, manganese and copper, uptake in both the crops because of nutrient release from decomposed organic matter. Additionally, the increase in fertilizer dose increased these parameters. The system productivity was maximum recorded under F3M1 (13,052 kg ha-1) and results were statistically identical with F3M2 and F3M3. The significant upsurge of macro and micro-nutrients in soil and its correlation with yield outcomes was also observed through the combined use of manures as well as fertilizers. This study concluded that the use of 100% RDF integrated with organic manures, particularly farmyard manure would be a beneficial resource for increased crop yield, soil nutrient status and system productivity in RWCS in different regions of India.
CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA ORGANIC FERTILIZERS YIELDS SOIL PROPERTIES RICE WHEAT CROPPING SYSTEMS
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
C.M. Parihar Hari Sankar Nayak Renu Pandey ML JAT (2021, [Artículo])
Biological Yield Permanent Beds Yield Attributes CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA YIELDS NITROGEN NUTRIENT UPTAKE CROP PERFORMANCE MAIZE
Brendan Brown Pragya Timsina Emma Karki (2023, [Artículo])
While crop diversification has many benefits and is a stated government objective across the Eastern Gangetic Plains (EGP) of South Asia, the complexity of assessment has led to a rather limited understanding on the progress towards, and status of, smallholder crop diversification. Most studies focus on specific commodities or report as part of a singular index, use outdated secondary data, or implement highly localized studies, leading to broad generalisations and a lack of regional comparison. We collected representative primary data with more than 5000 households in 55 communities in Eastern Nepal, West Bengal (India) and Northwest Bangladesh to explore seasonally based diversification experiences and applied novel metrics to understand the nuanced status of farm diversification. While 66 crops were commercially grown across the region, only five crops and three crop families were widely grown (Poaceae, Malvaceae, and Brassicaceae). Non-cereal diversification across the region was limited (1.5 crops per household), though regional differentiation were evident particularly relating to livestock and off-farm activities, highlighting the importance of cross border studies. In terms of farmer's largest commercial plots, 20% of systems contained only rice, and 57% contained only rice/wheat/maize, with substantial regional diversity present. This raises concerns regarding the extent of commercially oriented high value and non-cereal diversification, alongside opportunities for diversification in the under-diversified pre-monsoon and monsoon seasons. Future promotional efforts may need to focus particularly on legumes to ensure the future sustainability and viability of farming systems.
Agricultural Production Systems Farming Systems Change CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA AGRICULTURAL PRODUCTION CROPPING SYSTEMS DIVERSIFICATION FARMING SYSTEMS SUSTAINABLE INTENSIFICATION
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, [Artículo])
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.
rapeseed classification damaged crops deep neural networks INGENIERÍA Y TECNOLOGÍA CIENCIAS TECNOLÓGICAS TECNOLOGÍA DE LOS ALIMENTOS
Carlo Montes Anton Urfels Eunjin Han Balwinder-Singh (2023, [Artículo])
Rainy Season TIMESAT APSIM Agricultural Production Systems Simulator Climate Adaptation CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA RICE WHEAT MONSOONS WET SEASON CROP MODELLING CLIMATE CHANGE ADAPTATION
Comprehending the evolution of gene editing platforms for crop trait improvement
deepmala sehgal Apekshita Singh SoomNath Raina (2022, [Artículo])
Cas9 Base Editing Prime Editing Epigenome Editing CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA CRISPR ABIOTIC STRESS ARABIDOPSIS CROP IMPROVEMENT DNA ELECTROPORATION GENE EDITING RICE WHEAT