CREA Journals (Consiglio per la ricerca in agricoltura e l’analisi dell’economia agraria)
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Maize : potential crop for provitamin A biofortification
Get PDFCereals are the only source of nutrition for one-third of the world’s population especially in developing and underdeveloped nations of Sub-Saharan Africa and South-east Asia. Among the cereals, only the yellow maize exhibits tremendous natural variation for provitamin A carotenoids to exploit through plant breeding and being a carotenogenic plant, it is considered as one of the model cereal crops, showing promise for provitamin A biofortification. This paper deals with the maize carotenid biosynthetic pathway, genetic variability for kernel carotenoids, native genetic system for kernel carotenoids, marker assisted backcross breeding for enhancing provitamin A, recent advances in provitamin A biofortification and quantification of provitamin A carotenoids
Tree inventory data of Pinus nigra J.F.Arnold subsp. laricio (Poir.) Maire in southern Italy
Get PDFThe dataset supplied in this article provides data from a stand of Pinus nigra J.F.Arnold subsp. calabrica (Poir.) Maire (Calabrian black pine) characterized by old trees, with a relevant role for forest community biodiversity. Natural stands of Calabrian black pine have both outstanding conservation and cultural values, to be taken under consideration in forest and land uses management and monitoring plans.A time series of dendrometric parameters is provided for 58 pine trees: the data were collected during three forest surveys (in 1976, 1986 and 2016). These data, in combination with other forest stand and environmental parameters, may effectively contribute to understand the dynamics of Calabrian black pine forests in southern Italy, thus how the natural and human disturbances have affected the structure and species composition of these forest ecosystems with high ecological value.Dataset access at https://zenodo.org/record/1100340. Associated metadata available at https://zenodo.org/record/110034
Statistical inferential techniques for approaching forest mapping. A review of methods
Get PDFThe increasing availability of remote sensing data at no or low costs can be used as ancillary data in order to spatialize and improve the estimation of forest attributes and without increasing the sampling effort and costs. In this review paper, a description of the main statistical inferential techniques for approaching forest mapping is proposed. This article reviews the most used forest mapping methods based on the sole spatial information as well as techniques exploiting auxiliary information from remotely sensed data. The advantages and drawbacks of each method have been described on the basis of several factors, such as the aims of the investigation and the area under examination. Two main groups were here discussed with model-based methods on one side and model-assisted methods on the other, moving the attention from the model used to interpolate surfaces to the sampling scheme. Model-based methods include kriging, locally weighted regression, K-NN, decision trees and neural networks, while the inverse distance weighting interpolator is presented in the model-assisted group.Reliable and up-to-date information on forest characteristics are mandatory tools for any decisional process. The main input data of such systems are wall-to-wall maps depicting the spatial structures of forests and additional elements. Actually, if the original aim of forest inventories was to estimate harvestable timber amounts, a general interest towards multipurpose surveys is mandatory. Such information must deal with increased costs and more time-consuming procedures.
Communicating facts, findings and thinking to support evidence-based strategies and decisions
Get PDFHandicraft using corn ear husk and pest damage affecting its production
Get PDFFamily farmers use corn [Zea mays L (Poales: Poaceae)] ear husk to produce handicrafts. Income from selling handicrafts supplements their earnings and is used to buy food, home appliances, education (taxes) payment for children and grandchildren, etc. In addition, the extra work and income reduce artisan stress and improve physical and psychological health. EMBRAPA Corn and Sorghum, in Sete Lagoas, Minas Gerais state, Brazil, reports that corn genetic materials must have good productivity characteristics (main feature) and ears with husk of the proper color, length, texture, and width to be used for handicraft works which characteristics varies according to region and manufactured item. Moreover, plants must have good resistance characteristics to lodging and breakage, and seeds with good germination index. Birds, mammals, insects, and micro-organisms are corn pests, damaging plants and ear husks, and feeding on the kernels. Insects and micro-organisms usually cause lower damage to husks than birds and mammals. Identification of these organisms have been reported, such as an inverted «Y» on the head of the fall armyworm, Spodoptera frugiperda (Lepidoptera: Noctuidae) differentiating it from the corn earworm, Helicoverpa zea (Lepidoptera: Noctuidae). Main pest control methods were reported, e.g. for birds: construction of refuge places; propane applied with cannons; scarecrows with colorful fabrics; pyrotechnics (fireworks releasing); hunting (firearms used according to the law); seeds colored with inert substances (generally red, making them to resemble to toxic seeds of native plants); resistant cultivars (hard husk); covering ears with cloth bags (physical barrier); biological control with birds; commercially available repellent materials, and others. Handicraft using corn ear husk is important activity and expanding worldwide, but pests can destroy or severely damage production of this material
Effects of various leguminous intercrops on maize yield
Get PDFIntercropping increases a field’s utilization rate and maintains soil fertility. By comparing the single cropping of corn (SCC) with the intercropping of corn with three leguminous crops; i.e., mung bean (CM), black soybean (CB), and peanut (CP), this study investigated the effects of various leguminous intercrops on corn growth and yield. The experiment results indicate that intercropping corn with the mentioned leguminous crops increases the plant height, leaf area, and relative growth rate of the corn. In addition, the average single ear weight was 14.6%, 15.93%, and 22.1% higher in the CB, CM, and CP, respectively, when compared with that in the SCC, suggesting that the intercropping of corn with peanut is most beneficial for corn yield. Moreover, the number of rhizobia in the CP was 4.0 and 5.9 times the numbers in the CM and CB during the harvest period; the highest soil nitrogen content was also found in the CP (147.5 mg/kg), 2.0–2.2 times those in the other arrangements. This suggests that the abundant rhizobia on peanut roots increase the nitrogen content of soil and substantially boost corn yield. Intercropping corn with a leguminous crop thus increases both the growth and yield of the corn; compared with mung bean and black soybean, peanut was discovered to maximize growth and yield benefits as the most profitable intercro
Breeding strategies for improving growth and yield under waterlogging conditions in maize: A review
Get PDFWaterlogging, caused by flooding, excessive rains and poor drainage is a serious abiotic stress determining crop productivity worldwide. Maize (Zea mays L) is a basic food grain in many areas and several cultures and is culti- vated under much diverse agro-climatic zones extending from subtropical to cooler temperate regions. Therefore, the crop remains open to varied types of biotic as well as abiotic stresses. Among various abiotic stresses, water- logging is one of the most important constraints for maize production and productivity. Breeding for improved wa- terlogging tolerance includes modification of plant morphology, use of tolerant secondary traits and development of resistant varieties through conventional breeding and biotechnological approaches. A successful programme in conventional breeding should involve the integration of several criteria into one selection index and also successful breeding programmes for improved tolerance to submergence stress frequently combine two or more breeding strategies. Marker assisted selection (MAS) is an effective approach to identify genomic regions of crops under stress and construction of molecular linkage maps enable carry out pyramiding of desirable traits to improve sub- mergence tolerance through MAS
Pheromone-based monitoring of the European corn borer (Ostrinia nubilalis) in Hungary
Get PDFDespite the fact that the pheromone structure and composition of the European corn borer (Ostrinia nubilalis) was identified in the early 1970s, an effective pheromone-based monitoring method of this species has not been established yet in Hungary. The aim of this study was to find an optimal monitoring strategy for this economically important pest using pheromone traps. We compared three trap designs, five ratios and four doses of the earlier identified pheromone components in three different locations in Hungary. In the first year there was no significant difference between the delta and the cone traps as both were able to catch males in sufficient numbers. How- ever, in the second year the cone traps captured significantly more males. In a comparison of the different ratios of the two pheromone components, our results demonstrate that the usage of 97:3 Z:E [97% (Z)11-tetradecenyl acetate and 3% (E)11-tetradecenyl acetate] ratio attracted the highest number of males. Therefore, we suggest that the Z pheromone strain exists in the three monitored regions. In the experiment, where the different doses were compared, there was no significant difference in the number of males caught. In 2015, the flight dynamics of the species showed that males start to fly in the beginning of June and the highest flight peak occurs in mid June. Based on our results we conclude that in Hungary the pheromone traps are able to attract and monitor European corn borer males using the appropriate trap design, dose and ratio under field conditions
Use of satellite remote-sensing techniques to predict the variation of the nutritional composition of corn (Zea mays L) for silage
Get PDFThe nutritional composition of corn (Zea mays L) silage can vary substantially within a same silo. Environmental differences within the cornfield could contribute to this variability. We explored using green vegetation index maps, known as normalized difference vegetation index (NDVI) maps, to identify differences in the nutritional composition of corn at the field level. We hypothesized that the nutritional composition of the corn plant differs within the corn- field according to the vegetation index maps as detected by satellite remote-sensing techniques. Three cornfields from 3 commercial dairy farms located within the state of Virginia were utilized in this study. Landsat satellite data were obtained from the US Geological Survey to develop NDVI maps. Each cornfield was segregated in 3 regions classified as low NDVI, mid NDVI, and high NDVI. Corn plants from each region were harvested to determine their nutritional composition. At harvesting, corn plants were cut, weighed, chopped, and analyzed in the laboratory. Data were analyzed as for a complete block design, where fields and NDVI regions were considered blocks and treatments, respectively. The concentrations of ash (40 g kg-1), crude protein (102 g kg-1), neutral detergent fiber (398 g kg-1), acid detergent fiber (232 g kg-1), acid detergent lignin (14 g kg-1), and starch (304 g kg-1) did not differ at different NDVI regions. In our study none of the cornfields seemed to be environmentally stressed during the growing season of 2014. Therefore, it is plausible that the intrinsic variation of the cornfields was minimum due to the adequate growing conditions
Multi-environment field testing to identify stable sources of resistance to charcoal rot (Macrophomina phaseolina) disease in tropical maize germplasm
Get PDFThe charcoal rot caused by Macrophomina phaseolina is the devastating component of post flowering stalk rot (PFSR) complex which may cause 25 to 32 % yield loss in maize. Therefore for the first time, the study was carried out with multi-environments screening of 137 inbreds at three and 48 maize hybrids at six environments under artificially created epiphytotics at hot-spot locations to identify stable sources of charcoal rot resistance in Indian maize germplasm. Analysis of variance revealed strong effect of genotype by environment interaction on disease response and therefore indicated its complex nature. The mean disease score was ranging from 2.37 to 7.20 in inbreds, and 3.63 to 6.08 in hybrids. Additive main effects and multiplicative Interactions (AMMI) analysis could identifed, DQL1020, DML339, DML1, DQL1019, CM117-1-1 in inbreds and A-7501, CMH08-287, CMH08-292, BIO-562, and CMH08-350 in hybrids as stable sources of charcoal rot resistance. Each testing site viz., Ludhiana, Hyderabad and Delhi was identified as a separate test environment for screening against charcoal rot disease in India. In this study, AMMI model offers a good tool to assess the stability of genotypes and GGE biplot found an efficient tool to identify the mega environments in multi-environment testing. The identified sources of resistance in inbreds can be used in resistant breeding and hybrids can be recommended for cultivation in charcoal rot disease prone area