Forage yield and composition of Avena strigosa Schreb at different harvesting frecuencies and intensities

Edmundo García-Moya Juan Burgueño Rodolfo Ramírez-Valverde Luis Alberto Miranda-Romero (2022, [Artículo])

Saia Oats Sward Height Residual Foliage CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA HARVESTING FREQUENCY FOLIAGE AVENA NUDA YIELDS

Use of DH lines in maize breeding programs: CIMMYT experience

Yoseph Beyene (2023, [Objeto de congreso])

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA MAIZE BREEDING PROGRAMMES HYBRIDS MARKER-ASSISTED SELECTION GRAIN YIELDS

Climate smart bread wheat (Triticum aestivum L.) variety development for optimum moisture areas of Ethiopia

Bekele Abeyo Ayele Badebo Huluka (2023, [Artículo])

GGE Biplot AMMI Model CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA SOFT WHEAT ENVIRONMENT GENOTYPES GRAIN YIELDS

Una breve pesquisa sobre Crossopetalum gaumeri (Celastraceae). To be, or not to be [endemic], that is the question

RODRIGO STEFANO DUNO DIEGO FRANCISCO ANGULO PEREZ GERMAN CARNEVALI FERNANDEZ CONCHA (2022, [Artículo])

A finales de abril del 2022, un [malvado] colega del herbario CICY informó que habíamos olvidado una especie endémica en nuestra última actualización de endemismo para la Provincia Biótica Península de Yucatán ¡Otra más! Después de algunas angustias y pesquisas sobre la planta, pensamos que era una excelente oportunidad para hablar de una hermosa (o al menos interesante) planta de la región y presentar el caso. Se trata de Crossopetalum gaumeri, de la familia Celastraceae.

ENDEMISMO FLORA FLORA AUTOCTONA FLORISTICA YUCATAN BIOLOGÍA Y QUÍMICA CIENCIAS DE LA VIDA BIOLOGÍA VEGETAL (BOTÁNICA) ECOLOGÍA VEGETAL ECOLOGÍA VEGETAL

Influence of novel coconut oil and beeswax edible coating and MAP on postharvest shelf life and quality attributes of lemon at low temperature

Mohammad Mainuddin Molla Ashfak Ahmed Sabuz Md Abdul Matin (2023, [Artículo])

Weight loss, turning of peel colour from green to yellow and microbial infections are the major postharvest problems of lemon. Lipid-based edible coatings and modified atmospheric packaging (MAP) are effective techniques in maintaining postharvest quality of fruits for long-term storage. With this view, an investigation was conducted for the preservation of green lemon using coconut oil and beeswax edible coating and MAP during storage at low temperature. Physiologically matured lemons were collected and washed with potable water; fruit surface water was removed and then coated with coconut oil-beeswax (90:10) or only coconut oil. After coating, lemons were packaged in MAP or kept in open crates and stored at 12±1 °C and 85±5% relative humidity (RH) for 8 weeks and a week interval, the sampling was conducted. The results revealed that coconut oil-beeswax coating had immense effect on retaining shiny green colour, reducing respiration, weight loss, shrivelling and preserving firmness and ascorbic acid of lemon throughout the storage. On the other hand, MAP mainly helped to retain moisture & firmness and reduce shrivelling. Uncoated lemons kept open lost the highest amount of ascorbic acid and retained only 13.7 mg/100 g that is significantly (p < 0.05) less than the lemons of all other treatments at 8th week of storage period. While lemons coated with coconut oil-beeswax and packaged in MAP was preserved the highest amount (24.2 mg/100 g) of ascorbic acid and there was no significant difference (p < 0.05) with the amount of ascorbic acid content of lemons coated with only coconut oil and packaged in MAP at the last week (8th week) of storage. Hue angle value was 93.4 in uncoated lemons packaged in MAP while it was 113.67 in coconut oil-beeswax coated lemon kept open and 112.64 in lemon coated with coconut oil-beeswax and packaged in MAP at 8th week of storage. Based on all sensory, physical and chemical parameters uncoated lemons kept open was acceptable up to 1 week, coconut oil-beeswax coated lemon kept open was 6 weeks and coconut oil-beeswax coated lemon packaged in MAP was 8 weeks with good quality and shiny green colour.

Edible Coating Sensory Quality Hue Angle Yellowing CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA EDIBLE FILMS RESPIRATION RATE LEMONS MODIFIED ATMOSPHERE PACKAGING COLD

La historia detrás de Gonolobus caamali (Apocynaceae), endémica de la península de Yucatán

GERMAN CARNEVALI FERNANDEZ CONCHA GUSTAVO ADOLFO ROMERO GONZALEZ José Luis Tapia Muñoz Ivón Mercedes Ramírez Morillo CLAUDIA JANETH RAMIREZ DIAZ William Rolando Cetzal Ix RODRIGO STEFANO DUNO KATYA JEANNETH ROMERO SOLER (2022, [Artículo])

Publicar una especie nueva para la ciencia es siempre una tarea interesante y retadora, sobre todo en los tiempos modernos, donde la comunidad de sistemáticos de plantas y las revistas científicas exigen investigaciones de biología comparada más completas, integrando diferentes fuentes de evidencia (morfológica y molecular), más allá de una simple descripción morfológica. Esta historia comenzó hace más de 15 años y terminó este año, cuando Gonolobus caamali Carnevali & R. Duno (Apocynaceae), fue descrita como una nueva especie para la ciencia. Presentamos aquí algunos detalles de esta especie.

ASCLEPIADOIDEAE EXTINCION MEXICO NOVEDAD TAXONOMICA YUCATAN BIOLOGÍA Y QUÍMICA CIENCIAS DE LA VIDA BIOLOGÍA VEGETAL (BOTÁNICA) TAXONOMÍA VEGETAL TAXONOMÍA VEGETAL

Parques vemos, biodiversidad no sabemos: el caso de la herpetofauna de la ciudad de Mérida

Roberto Carlos Barrientos Medina (2023, [Artículo])

La herpetofauna, constituida por las diferentes especies de anfibios y reptiles que se pueden encontrar en un hábitat, es un buen grupo indicador de diversidad, ya que presenta características de movilidad que los hacen ser más dependientes del hábitat (lugar en el que viven). En este trabajo se analizan los patrones de diversidad de los anfibios y reptiles que se pueden encontrar en los parques ecológicos de Mérida, en distintos niveles de expresión (alfa, beta y gamma). Los resultados señalan la influencia del grado de urbanización, de acuerdo con los patrones encontrados en las diversidades beta y gamma.

AMBIENTES ANTROPIZADOS ECOLOGIA URBANA NIVELES DE DIVERSIDAD PATRONES ECOLOGICOS YUCATAN BIOLOGÍA Y QUÍMICA CIENCIAS DE LA VIDA BIOLOGÍA ANIMAL (ZOOLOGÍA) HERPETOLOGÍA HERPETOLOGÍA

Big data, small explanatory and predictive power: Lessons from random forest modeling of on-farm yield variability and implications for data-driven agronomy

Martin van Ittersum (2023, [Artículo])

Context: Collection and analysis of large volumes of on-farm production data are widely seen as key to understanding yield variability among farmers and improving resource-use efficiency. Objective: The aim of this study was to assess the performance of statistical and machine learning methods to explain and predict crop yield across thousands of farmers’ fields in contrasting farming systems worldwide. Methods: A large database of 10,940 field-year combinations from three countries in different stages of agricultural intensification was analyzed. Random effects models were used to partition crop yield variability and random forest models were used to explain and predict crop yield within a cross-validation scheme with data re-sampling over space and time. Results: Yield variability in relative terms was smallest for wheat and barley in the Netherlands and for wheat in Ethiopia, intermediate for rice in the Philippines, and greatest for maize in Ethiopia. Random forest models comprising a total of 87 variables explained a maximum of 65 % of cereal yield variability in the Netherlands and less than 45 % of cereal yield variability in Ethiopia and in the Philippines. Crop management related variables were important to explain and predict cereal yields in Ethiopia, while predictive (i.e., known before the growing season) climatic variables and explanatory (i.e., known during or after the growing season) climatic variables were most important to explain and predict cereal yield variability in the Philippines and in the Netherlands, respectively. Finally, model cross-validation for regions or years not seen during model training reduced the R2 considerably for most crop x country combinations, while for wheat in the Netherlands this was model dependent. Conclusion: Big data from farmers’ fields is useful to explain on-farm yield variability to some extent, but not to predict it across time and space. Significance: The results call for moderate expectations towards big data and machine learning in agronomic studies, particularly for smallholder farms in the tropics where model performance was poorest independently of the variables considered and the cross-validation scheme used.

Model Accuracy Model Precision Linear Mixed Models CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA MACHINE LEARNING SUSTAINABLE INTENSIFICATION BIG DATA YIELDS MODELS AGRONOMY

Testing innovations for adoption of newer and more adapted maize varieties

Michael Ndegwa Pieter Rutsaert Jason Donovan Jordan Chamberlin (2023, [Objeto de congreso])

Changing Production Conditions Genetic Innovations Maize Hybrids CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA TESTING MAIZE VARIETIES YIELDS FARMERS EXPERIMENTATION

Enhancing maize yield in a conservation agriculture-based maize (Zea mays)- wheat (Triticum aestivum) system through efficient nitrogen management

C.M. Parihar Hari Sankar Nayak Dipaka Ranjan Sena Shankar Lal Jat Mahesh Gathala Upendra Singh (2023, [Artículo])

This study evaluated the impact of contrasting tillage and nitrogen management options on the growth, yield attributes, and yield of maize (Zea mays L.) in a conservation agriculture (CA)-based maize-wheat (Triticum aestivum L.) system. The field experiment was conducted during the rainy (kharif) seasons of 2020 and 2021 at the research farm of ICAR-Indian Agricultural Research Institute (IARI), New Delhi. The experiment was conducted in a split plot design with three tillage practices [conventional tillage with residue (CT), zero tillage with residue (ZT) and permanent beds with residue (PB)] as main plot treatments and in sub-plots five nitrogen management options [Control (without N fertilization), recommended dose of N @150 kg N/ha, Green Seeker-GS based application of split applied N, N applied as basal through urea super granules-USG + GS based application and 100% basal application of slow release fertilizer (SRF) @150 kg N/ha] with three replications. Results showed that both tillage and nitrogen management options had a significant impact on maize growth, yield attributes, and yield in both seasons. However, time to anthesis and physiological maturity were not significantly affected. Yield attributes were highest in the permanent beds and zero tillage plots, with similar numbers of grains per cob (486.1 and 468.6). The highest leaf area index (LAI) at 60 DAP was observed in PB (5.79), followed by ZT(5.68) and the lowest was recorded in CT (5.25) plots. The highest grain yield (2-year mean basis) was recorded with permanent beds plots (5516 kg/ha), while the lowest

was observed with conventional tillage (4931 kg/ha). Therefore, the study highlights the importance of CA practices for improving maize growth and yield, and suggests that farmers can achieve better results through the adoption of CA-based permanent beds and use of USG as nitrogen management option.

Green Seeker Urea Super Granules CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA MAIZE UREA YIELDS ZERO TILLAGE NITROGEN