Performance assessment of the AquaCrop model to estimate rice yields under alternate wetting and drying irrigation in the coast of Peru

Peru is the second-largest rice producer in Latin America, with 406166 ha grown annually, predominately on the Peruvian north coast. However, rice is primarily irrigated by flooding (93%), which demands high water use (15000-18000 m3 ha−1) owing to low water-use efficiency. Additionally, the intensification of climate change is of great concern as it causes high variability as well as a decreasing trend in water resource availability. Alternate wetting and drying (AWD) irrigation technique reportedly reduce the irrigation volumes while maintaining conventional yield rates. The AquaCrop model was calibrated and assessed to simulate rice yield response to the AWD technique under water shortage conditions on the Peruvian central coast. The AquaCrop model exhibited a “very good” to “good” performance in predicting canopy cover development, soil water content, aerial biomass, and grain yield using performance indicators, such as the Nash-Sutcliffe efficiency coefficient, the RMSE observations standard deviation ratio (RSR), Willmott index, and determination coefficient. The calibrated model showed a good performance of rice under AWD irrigation, indicating that this technique can be used to assess rice production under Peruvian arid conditions

Improving the monitoring of corn phenology in large agricultural areas using remote sensing data series

Aim of study: Mexico's large irrigation areas demand non-structural actions to improve the irrigation service, such as monitoring crop phenology; however, its application has been limited by the large volumes of field information generated, diversity of crop management and climatic variability. The objective of this study was to generate and validate a methodology to monitor corn (Zea mays L.) phenology from the historical relationship of the vegetation indexes (VIs), EVI and NDVI, with the phenological development (PD) of corn grown in large irrigation zones.Area of study: Irrigation District (ID) 075 “Valle del Fuerte”, northern Sinaloa, Mexico.Material and methods: We used a database of 20 years of climate, field crop growth and crop phenology data, and Landsat satellite images. A methodology was proposed on a large scale supported with GIS and remote sensing data series.Main results: The methodology was validated in 19 plots with an acceptable correlation between observed PD and estimated PD for the two VIs, with slightly better values for EVI than for NDVI. NDVI and EVI models agreed with experimental PD observations in 92.1% of the farms used to validate the methodology, in 2.5% only the NDVI model coincided with the real, in 3.1% only the EVI model coincided, and in 2.3% both models disagreed with observation, generated a stage out of phase with respect to the real phenological stage.Research highlights: is possible to generalize the methodology applied to large irrigation zones with remote sensing data and GIS

Estimation of rice crop evapotranspiration in Perú based on the METRIC algorithm and UAV images

[EN] Modern remote measurement techniques using cameras mounted on an unmanned aerial vehicle (UAV) have made possible to acquire high-resolution images and estimating evapotranspiration at more detailed spatial and temporal scales. The objective of the present research was to estimate crop evapotranspiration (ETc) of rice crop using the “mapping evapotranspiration with internalized calibration model (METRIC)” using high spatial resolution multispectral and thermal images obtained from a UAV. A total of 18 flights with UAV were performed to get the images; likewise, data were collected from the weather station and thermocouple information installed in the crop canopy under soil water potential conditions of –10 kPa (T1), –15 kPa (T2), –20 kPa (T3) and a control of 0 kPa (T0), from November 13, 2017, to April 30, 2018. The results indicate that the METRIC model compared to ETc measurements recorded by a field drainage lysimeter presents a Pearson correlation coefficient (r) of 0.97, root mean square error (RMSE) of 0.51 mm d–1, Nash-Sutcliffe coefficient (EF) of 0.87 and underestimation of 7 %. Evapotranspiration reached values of 7.48 mm d–1, with differences between treatments of 0.2 %, 6 % and 8 % concerning to T0 and yield reduction of 9 %, 34 % and 35 % for T1, T2 and T3 soil water potential. The high[1]resolution images allowed obtaining detailed information on the spatial variability of ETc that could be used in the more efficient application of plot irrigation.[ES] Las modernas técnicas de mediciones remotas con el uso de cámaras (multiespectral y térmica) acopladas a un vehículo aéreo no tripulado (VANT) han permitido adquirir imágenes de alta resolución, haciendo posible estimar la evapotranspiración a una mayor escala espacial y temporal. El objetivo de la presente investigación fue estimar la evapotranspiración del cultivo (ETc) de arroz mediante el modelo METRIC (Mapping evapotranspiration at high resolution with internalized calibration) a partir de imágenes multiespectrales y térmicas de alta resolución espacial obtenidas desde un VANT. Se realizaron 18 vuelos con VANT para obtener las imágenes, así mismo, se recolectaron datos de una estación meteorológica e información de termopares instalados en el dosel del cultivo en condiciones de potencial hídrico del suelo de –10 kPa (T1), –15 kPa (T2), –20 kPa (T3) y un control de 0 kPa (T0), desde el 13 de noviembre del 2017 al 30 de abril del 2018. Los resultados indican que el modelo METRIC, comparado con las medidas de ETc registradas por un lisímetro de drenaje en campo, presenta un coeficiente de correlación de Pearson (r) de 0,97, un error cuadrático medio (RMSE) de 0,51 mm d–1, un coeficiente de Nash-Sutcliffe (EF) de 0,87 y subestimación del 7 %. La evapotranspiración alcanzó valores de 7,48 mm d–1, con diferencias entre tratamientos de 0,2%, 6% y 8% con respecto al T0 y una reducción del rendimiento del 9 %, 34 % y 35 % para T1, T2 y T3 del potencial hídrico del suelo. Las imágenes de alta resolución permitieron obtener información detallada de la variabilidad espacial de ETc que podría ser utilizada en la aplicación más eficiente del riego parcelario.Al Proyecto “Uso de sensores remotos para determinar índice de estrés hídrico en el mejoramiento del manejo de riego de arroz (Oryza sativa) en zonas áridas, para enfrentar al cambio climático”. Convenio N° 008-2016-INIA-PNIA/UPMSI/IE.Quille-Mamani, JA.; Ramos-Fernández, L.; Ontiveros-Capurata, RE. (2021). Estimación de la evapotranspiración del cultivo de arroz en Perú mediante el algoritmo METRIC e imágenes VANT. Revista de Teledetección. 0(58):23-38. https://doi.org/10.4995/raet.2021.13699OJS2338058Abrishamkar, M., Ahmadi, A. 2017. Evapotranspiration Estimation Using Remote Sensing Technology Based on SEBAL Algorithm. Iranian Journal of Science and Technology Transactions of Civil Engineering, 41, 65-76. https://doi.org/10.1007/s40996-016-0036-xAlberto, M.C.R., Wassmann, R., Hirano, T., Miyata, A., Hatano, R., Kumar, A., … Amante, M. 2011. Comparisons of energy balance and evapotranspiration between flooded and aerobic rice fields in the Philippines. Agricultural Water Management, 98(9), 1417-1430. https://doi.org/10.1016/j.agwat.2011.04.011Allen, R., Tasumi, M., Trezza, R., Waters, R. 2002. Bastiaanssen, W. Surface Energy Balance Algorithm for Land (SEBAL)-Advanced Training and Users Manual; Idaho Department of Water Resources, University of Idaho: Moscow, ID, USA.Allen, R., Tasumi, M., Trezza, R. 2007a. Satellite-based energy balance for mapping evapotranspiration with internalized calibration (METRIC) model. ASCE, Journal of Irrigation and Drainage Engineering, 133, 380-394. https://doi.org/10.1061/(ASCE)0733-9437(2007)133:4(380)Allen, RG., Tasumi, M., Morse, A., Trezza, R., Wright, JL., Bastiaanssen, W., Kramber, W., Lorite, I., Robison, CW. 2007b. Satellite-Based Energy Balance for Mapping Evapotranspiration with Internalized Calibration (METRIC)-Applications. Journal of Irrigation and Drainage Engineering, 133(4), 395-406. https://doi.org/10.1061/(ASCE)0733-9437(2007)133:4(395)Allen, R., Trezza, R., Hendrickx, J., Bastiaanssen, W., Kjaersgaard, J. 2011. Satellite-based ET estimation in agriculture using SEBAL and METRIC. Hydrological Processes, 25(26), 4011-4027. https://doi.org/10.1002/hyp.8408Allen, RG., Burnett, B., Kramber, W., Huntington, J., Kjaersgaard, J., Kilic, A., Kelly, C., Trezza, R. 2013. Automated calibration of the METRIC-Landsat evapotranspiration process. 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A remote sensing surface energy balance algorithm for land (SEBAL) 1. Formulation. Journal of Hydrology 212-213(1- 16), 198-212. https://doi.org/10.1016/S0022-1694(98)00253-4Bastiaanssen, W.G.M., Pelgrum, H., Wang, J., Ma, Y., Moreno, J.F., Roerink, G.J., Van Der Wal, T. 1998b. A remote sensing surface energy balance algorithm for land (SEBAL): 2. Validation. Journal of Hydrology, 212-213(1-4), 213-229. https://doi.org/10.1016/S0022-1694(98)00254-6Bastiaanssen, W.G.M. 2000. SEBAL-based sensible and latent heat fluxes in the irrigated Gediz Basin, Turkey. Journal of Hydrology, 229(1-2), 87-100. https://doi.org/10.1016/S0022-1694(99)00202-4Bhattarai, N., Quackenbush, L.J., Im, J., Shaw, S.B. 2017. A new optimized algorithm for automating endmember pixel selection in the SEBAL and METRIC models. Remote Sensing of Environment, 196, 178- 192. https://doi.org/10.1016/j.rse.2017.05.009Brenner, C., Zeeman, M., Bernhardt, M., Schulz, K., 2018. Estimation of evapotranspiration of temperate grassland based on high-resolution thermal and visible range imagery from unmanned aerial systems. International Journal of Remote Sensing, 39(15-16), 5141-5174. https://doi.org/10.1080/01431161.2018.1471550Cha-Um, S., Yooyongwech, S., Supaibulwatana, K. 2010. Water deficit stress in the reproductive stage of four Indica rice (Oryza sativa L.) genotypes. Journal of Botany, 42(5), 3387-3398.Enciso, J., Jung, J., Chang, A., Chavez, J.C., Yeom, J., Landivar, J., Cavazos, G. 2018. Assessing land leveling needs and performance with unmanned aerial system. Journal of Applied Remote Sensing, 12(1). https://doi.org/10.1117/1.JRS.12.016001Han, L., Yang, G., Dai, H., Xu, B., Yang, H., Feng, H., Li, Z., Yang. X. 2019. Modeling maize above-ground biomass based on machine learning approaches using UAV remote-sensing data. Plant Methods, 15, 10(2019). https://doi.org/10.1186/s13007-019-0394-zHeros, E., Gómez, L., Sosa, G. 2017. Utilización de los índices de selección en la identificación de genotipos de arroz (Oryza sativa L.) tolerantes a sequía. Producción Agropecuaria y Desarrollo Sostenible 2(2), 11-31. https://doi.org/10.5377/payds.v2i0.4326Hilmi, H., Saad, H. 2005. Estimation of Rice Evapotranspiration in Paddy Fields Using Remote Sensing and Field Measurements. Universiti Putra Malaysia, Malaysia.Hoffmann, H., Nieto, H., Jensen, R., Guzinski, R., Zarco-Tejada, P., Friborg, T. 2016. Estimating evaporation with thermal UAV data and two-source energy balance models. Hydrology and Earth System Sciences, 20(2), 697-713. https://doi.org/10.5194/hess-20-697-2016Huete, A.R. 1988. A Soil-Adjusted Vegetation Index (SAVI). Remote Sensing of Environment, 25, 295- 309. https://doi.org/10.1016/0034-4257(88)90106-XKato, Y., Okami, M., Katsura, K. 2009. Yield potential and water use efficiency of aerobic rice (Oryza sativa L.) in Japan. Field Crops Research, 113(3), 328-334. https://doi.org/10.1016/j.fcr.2009.06.010Kiptala, J.K., Mohamed, Y., Mul, M.L., Van Der Zaag, P. 2013. Mapping evapotranspiration trends using MODIS and SEBAL model in a data scarce and heterogeneous landscape in Eastern Africa. Water Resources Research, 49(12), 8495-8510. https://doi.org/10.1002/2013WR014240Kukal, S.S., Hira, G.S., Sidlu, A.S. 2005. Soil matric potential-based irrigation scheduling to rice (Oryza sativa). Irrigation Science, 23(4), 153-159. https://doi.org/10.1007/s00271-005-0103-8Lage, M., Bamouh, A., Karrou, M., El Mourid, M. 2003. Estimation of rice evapotranspiration using a microlysimeter technique and comparison with FAO Penman-Monteith and Pan evaporation methods under Moroccan conditions. Agronomie, EDP Sciences, 23(7), 625-631. https://doi.org/10.1051/agro:2003040Lee, Y., Kim, S. 2016. The Modified SEBAL for Mapping Daily Spatial Evapotranspiration of South Korea Using Three Flux Towers and Terra MODIS Data. Remote Sensing, 8(12), 983. https://doi.org/10.3390/rs8120983Li, G., Jing, Y., Wu, Y., Zhang, F. 2018. Improvement of Two Evapotranspiration Estimation Models Using a Linear Spectral Mixture Model over a Small Agricultural Watershed. Water, 10(4), 474. https://doi.org/10.3390/w10040474Liu, X., Xu, J., Zhou, X., Wang, W., Yang, S. 2019. Evaporative fraction and its application in estimating daily evapotranspiration of water-saving irrigated rice field. Journal of Hydrology, 584, 124317. https://doi.org/10.1016/j.jhydrol.2019.124317Maruyama, A., Kuwagata, T. 2010. Coupling land surface and crop growth models to estimate the effects of changes in the growing season on energy balance and water use of rice paddies. Agricultural and Forest Meteorology, 150(7-8), 919-930. https://doi.org/10.1016/j.agrformet.2010.02.011Moriasi, D.N., Arnold, J.G., Van Liew, M.W., Bingner, R.L., Harmel, R.D., Veith, T.L. 2007. Model Evaluation Guidelines for Systematic Quantification of Accuracy in Watershed Simulations. Transactions of the ASABE, 50(3), 885-900. https://doi.org/10.13031/2013.23153Morton, C.G., Huntington, J.L., Pohll, G.M., Allen, R.G., Mcgwire, K.C., Bassett, S.D. 2013. Assessing Calibration Uncertainty and Automation for Estimating Evapotranspiration from Agricultural Areas Using METRIC. Journal of the American Water Resources Association, 49(3), 549-562. https://doi.org/10.1111/jawr.12054Nahar, S., Vemireddy, L.R., Sahoo, L., Tanti, B. 2018. Antioxidant Protection Mechanisms Reveal Significant Response in Drought-Induced Oxidative Stress in Some Traditional Rice of Assam, India. Rice Science, 25(4), 185-196. https://doi.org/10.1016/j.rsci.2018.06.002Nassar, A., Torres-Rua, A., Kustas, W., Nieto, H., McKee, M., Hipps, L., Stevens, D., Alfieri, J., Prueger, J., Mar Alsina, M., McKee, L., Coopmans, C., Sanchez, L., Dokoozlian, N. 2020. Influence of Model Grid Size on the Estimation of Surface Fluxes Using the Two Source Energy Balance Model and sUAS Imagery in Vineyards, Remote Sensing, 12(3), 342. https://doi.org/10.3390/rs12030342Norasma, C.Y.N., Abu Sari, M.Y., Fadzilah, M.A., Ismail, M.R., Omar, M.H., Zulkarami, B., Hassim Y.M.M., Tarmidi, Z. 2018. Rice crop monitoring using multirotor UAV and RGB digital camera at early stage of growth. IOP Conference Series: Earth and Environmental Science, 169, 012095. https://doi.org/10.1088/1755-1315/169/1/012095Ortega-Farías, S., Ortega-Salazar, S., Poblete, T., Kilic, A., Allen, R., Poblete-Echeverría, C., Ahumada-Orellana, L., Zuñiga, M., Sepúlveda, D. 2016. Estimation of energy balance components over a drip-irrigated olive orchard using thermal and multispectral cameras placed on a helicopter-based unmanned aerial vehicle (UAV). Remote Sensing, 8(8), 1-18. https://doi.org/10.3390/rs8080638Ramírez-Cuesta, J.M., Allen, R.G., Zarco-Tejada, P.J., Kilic, A., Santos, C., Lorite, I.J. 2019. Impact of the spatial resolution on the energy balance components on an open-canopy olive orchard. International Journal of Applied Earth Observation and Geoinformation, 74, 88-102. https://doi.org/10.1016/j.jag.2018.09.001Rauneker, P., Lischeid, G. 2012. Spatial distribution of water stress and evapotranspiration estimates using an unmanned aerial vehicle (UAV). EGU General Assembly Conference Abstracts, 14, 10477.Sagan, V., Maimaitijiang, M., Sidike, P., Eblimit, K., Peterson, KT., Hartling, S., Esposito, F., Khanal, K., Newcomb, M., Pauli, D., Ward, R., Fritschi, F., Shakoor, N., Mockler, T. 2019. UAV-based high resolution thermal imaging for vegetation monitoring, and plant phenotyping using ICI 8640 P, FLIR Vue Pro R 640, and thermomap cameras. 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Rice Science, 25(2), 82-93. https://doi.org/10.1016/j.rsci.2018.02.00

Diversity and Genetic Structure of Scarlet Plume (Euphorbia fulgens), an Endemic Plant of Mexico

[EN] Euphorbia fulgens is an ornamental species cultivated in Europe and endemic to Mexico; its ecological, genetic, and evolutionary aspects are not known. The objectives of this study were to determine its distribution, describe the places it inhabits, and analyze the diversity and genetic structures of wild populations of E. fulgens. A bibliographic review of the herbarium specimens and a field evaluation were carried out to develop a potential distribution map based on a multi-criteria analysis of the climatic and topographic variables. Three populations (forty-five individuals) from pine–oak and cloud forests located in the Southern Sierra of Oaxaca were analyzed using ten microsatellite loci. The analysis was conducted using Arlequin v. 3.5, Mega v. 10, and Structure v. 2.3 programs. Eight loci were polymorphic, and a total of thirty-eight alleles were obtained. The average number of alleles per polymorphic locus was 4.6. The average heterozygosity of the three populations was high (Ho = 0.5483), and genetic differentiation between populations were low, with a high genetic flow, suggesting that it could be an ancestral population that became fragmented and was just beginning to differentiate genetically. The information generated on this restricted distribution species can be used in conservation programs pertaining to human activities that endanger the habitats where it is found.S

Movimiento del agua freática y concentración de sales en suelos agrícolas

In rainy periods 223.8 ha in San Martín Nezahualcóyotl, Mexico State, have problems with excess moisture and high concentrations of soluble salts in the soil layers and groundwater, which vary throughout the year with fluctuations of the water table res ulting in low crop yields. Isobaths planes were developed in this work, to locate areas of excessive moisture, 1 sohypsess how the di re cti o ns and move me nt o f groundwater flows and isos ali nity in s oil profiles. Water table oscillation was determined by analyzing 27 samples of soil and water per year over the period 2006-2011. It was found that rains in August (33 mm) and September (100.5 mm) cause the rise of the water table and excess water in the soil at 0.58 ha to 0.65 ha per mm of rainfall in 223.8 ha. In water tables over 1.51 m deep, soils had low salinity and sodicity (72.36 ha). In water tables less than 1.5 mm deep and groundwater medium to high in salts, saline soils and / or sodic soils were found, covering 59 ha (26 %) of the total area.En periodos de lluvias223.8 ha en San Martín Netzahualcóyotl, Estado de México, presentan problemas de exceso de humedad y altas concentraciones de sales solubles en los estratos del suelo y aguas freáticas, que varían a lo largo del año con el movimiento descendente y ascendente del nivel freático que provoca bajos rendimientos de los cultivos. En éste trabajo se elaboraron planos de isobatas, para ubicar las áreas de exceso de humedad, isohypsas muestran las direcciones y movimiento de los flujos subterráneos e isosalinidad en los perfiles del suelo. Se determinó la oscilación del nivel freático mediante el análisis de 27 muestras de suelo y agua por año durante el periodo de 2006 a 2011. Se encontró que las lluvias de agosto (33 mm) y septiembre (100.5 mm) son las causantes del ascenso del nivel freático y excesos de agua en el suelo en 0.58 ha a 0.65 ha por milímetro de precipitación en 223.8 ha. A niveles freáticos mayores a 1.51 m de profundidad los suelos presentaron baja salinidad y sodicidad (72.36 ha). A niveles freáticos menores a 1.5 mm y aguas freáticas de mediana a alta en sales, se encontraron, suelos salinos y/o sódicos cubriendo 59 ha. (26%) de la superficie total

Estimation of salinity wastewater using near infrared spectroscopy

The visible and near infrared spectroscopy is a fast, and inexpensive non-destructive technique for the prediction of concentrations of salts in wastewater. Conventional chemical methods are usually used which are very accurate but take time and require special techniques for sampling, storing and pretreatment of wastewater. In this work we studied the spectral characteristics of water and the effect of salts on the perturbations in the water absorption bands. The generation of multiple regression models with principal components (PCR) was carried out on standard solutions with composition of salts similar to that of wastewater samples taken along the drainage channel network of the Mexico City Metropolitan Area. The spectral signatures were obtained in situ and laboratory using a portable high-resolution spectroradiometer (ASD FieldSpect3). The prediction model generated showed high precision in the estimation of salinity in wastewater, a coefficient of determination of 89.6% and a low root mean square error of 0.12 ?.Pages: 1774-178

Improving the monitoring of corn phenology in large agricultural areas using remote sensing data series

Aim of study: Mexico's large irrigation areas demand non-structural actions to improve the irrigation service, such as monitoring crop phenology; however, its application has been limited by the large volumes of field information generated, diversity of crop management and climatic variability. The objective of this study was to generate and validate a methodology to monitor corn (Zea mays L.) phenology from the historical relationship of the vegetation indexes (VIs), EVI and NDVI, with the phenological development (PD) of corn grown in large irrigation zones.Area of study: Irrigation District (ID) 075 “Valle del Fuerte”, northern Sinaloa, Mexico.Material and methods: We used a database of 20 years of climate, field crop growth and crop phenology data, and Landsat satellite images. A methodology was proposed on a large scale supported with GIS and remote sensing data series.Main results: The methodology was validated in 19 plots with an acceptable correlation between observed PD and estimated PD for the two VIs, with slightly better values for EVI than for NDVI. NDVI and EVI models agreed with experimental PD observations in 92.1% of the farms used to validate the methodology, in 2.5% only the NDVI model coincided with the real, in 3.1% only the EVI model coincided, and in 2.3% both models disagreed with observation, generated a stage out of phase with respect to the real phenological stage.Research highlights: is possible to generalize the methodology applied to large irrigation zones with remote sensing data and GIS

Onset of the growing season and dry periods in Tabasco, Mexico

In rainfed agriculture, information about dates for the onset of rainy periods is used to plan activities inherent to exploitation, and even determines the success or failure of crops. The results are partially reflected after planting (germination) and at harvesting time. Dry periods are another very important factor to the agricultural cycle, causing poor germination, stunted growth, deficient development and considerable reductions in yield. Therefore, an analysis was performed at the onset of the growing season in Tabasco in order to identify different levels of probabilities for the dates for the beginning of this period. The frequency of 7-day dry periods was also studied (defined by a threshold of 1 mm) using daily rainfall and evaporation information from 18 weather stations in the state. A relationship was found between the average start of the growing season with the latitude and average annual rainfall. This was corroborated by a linear regression analysis, in which values for r2 of 0.6884 and 0.8112 were found for each case. The earliest dates for the beginning of the growing season relate to low probabilities for the onset of the rainy season; Tabasco has three regions in which the beginning of the growing season (80%) is distinctly affected by the occurrence of 7-day dry periods

Calidad de fruta de lima 'Persa' en diferentes portainjertos en Veracruz, México

The 'Persian' lime is the most exported citrus in Mexico, the principal producing area is concentrated in Martinez de la Torre, Veracruz. The rootstock most used in the region is the 'Agrio'orange, but is susceptible to tristeza citrus virus. New options for fruit production are longer necessary. Objective of this work was to determine the fruit quality of 'Persian' lime on different rootstocks (Citrumelo 'Swingle', 'Macrophylla' lemon, 'Agrio' orange, 'C35' and 'Troyer' citrange, 'Volkamer' lemon, 'Palestine Sweet lime' and 'Flying Dragon' orange). From each treatment 10 fruits were harvested. Variables evaluated were fruit mass, polar diameter, equatorial diameter, polar/equatorial diameter ratio, skin thickness, fruit firmness, and export fruit percentage. The experimental design was a completely randomized with eight treatments and five repetitions. A tree as experimental unit was used. An analysis of variance and Tukey test (p≤0.05) was performed. Average of five harvest dates for fruit weight ranged between 72.89 g and 109.57 g. The polar diameter was 57.32 mm to 67.75 mm; the equatorial diameter varied between 49.29 mm and 56.52 mm; the polar diameter and equatorial diameter ratio was 1.14 mm to 1.23 mm; the skin thickness was between 2.64 mm and 4.25 mm; fruit firmness was 3979-4966 gf, percentage of fruit export quality in all treatments was greater than 80%El estudio se realizó en el año 2015 en el municipio de Martínez de la Torre, Veracruz, en el Rancho  “San Antonio”  ubicado en la localidad El Diamante con  100 m de altura sobre el nivel del mar. El objetivo del presente trabajo fue determinar la calidad de fruta de lima 'Persa'   en diferentes portainjertos. De cada tratamiento se cosecharon 10 frutos. Algunas de las variables que se evaluaron fueron peso de fruto, diámetro polar, diámetro ecuatorial, relación diámetro polar y diámetro ecuatorial, grosor de cáscara y firmeza de fruto. El diseño experimental fue un completamente al azar con 8 tratamientos y 5 repeticiones, se utilizó un árbol como unidad experimental. Se realizaron análisis de varianza y prueba de Tukey (p ≤0.05). El promedio de 5 fechas de corte para el peso de fruto osciló de 109.57 gramos a 72.89 gramos, el diámetro polar fue de 57.32 milímetros a 67.75 milímetros, el diámetro ecuatorial fue de 49.29 milímetros a 56.52 milímetros, la relación diámetro polar y diámetro ecuatorial fue de 1.14 milímetros a 1.23 milímetros, el grosor de cáscara osciló de 2.64 milímetros  a 4.25 milímetros, la firmeza del fruto fue de 3,979  a  4,966 g fuerza y el porcentaje de fruto de exportación en todos los tratamientos fue superior a 80 %

A Curriculum Learning Approach to Classify Nitrogen Concentration in Greenhouse Basil Plants Using a Very Small Dataset and Low-Cost RGB Images

The automatic classification of plants with nutrient deficiencies or excesses is essential in precision agriculture. In particular, being able to perform early detection of nutrient concentrations would increase the production of crop yields and make appropriate use of fertilizers. RGB cameras represent a low-cost alternative sensor for plant monitoring, but this task is complicated when it is purely visual and has limited samples. In this paper, we analyze the Curriculum by Smoothing technique with a small dataset of RGB images (144 images per class) to classify nitrogen concentrations in greenhouse basil plants. This Deep Learning method changes the texture found in the images during training by convolving each feature map (the output of a convolutional layer) of a Convolutional Neural Network with a Gaussian kernel whose width increases as training progresses. We observed that controlled information extraction allows a state-of-the-art deep neural network to perform well using little training data containing a high variance between items of the same class. As a result, the Curriculum by Smoothing provides an average accuracy 7% higher than the traditional transfer learning method for the classification of the nitrogen concentration level of greenhouse basil ‘Nufar’ plants with little data