With relation to the present issue about the influence of the periodic water deficit on the content and yield of the main chemical components, summarized annual data have been used including years of different characteristics, with droughts in different vegetation phenophases of soybean: very dry, averagely dry and average. The experiment was conducted at the Agricultural University of Plovdiv. The experiment was set in 4 repetitions with a size of experimental plots - 30 m 2 , and the crop plots - 10 m 2 . Criteria for watering performance was pre-watering moisture of soil at option 5-80% under-soil moisture for the layer 0-60 cm. The irrigation norm for all options was 50 mm. The irrigation norm for option 5 was 150 mm, and for options 2, 3 and 4-100 mm. Irrigation was performed gravitative along short closed furrows. After the completion of all experimental options, there were established the content and yield of the main chemical components in soybean grains - raw fat content, raw protein, raw fibres, raw ash and non-nitrogen extracted substances. Watering cancellations in the period of seed filling decrease the raw protein content. Watering cancellation in the bean formation period has a negative influence on protein content in soybean or does not influence it at all. Watering cancellation during the reproductive period decreases raw protein yield, which leads to a decrease in grain yield. Regarding raw fats, the most favourable is the water cancellation in the period of seed filling which favours growth in their content. Watering cancellation in the period of seed filling leads to a more significant decrease in lysine content. Despite the watering cancellation in a particular phase, the application of the other two waterings increases carbohydrate content in soybean grains compared to that obtained in non-watering conditions.
The purpose of this study was to establish the impact of irrigation canceling at different growth stages on the components of sunflower yield -1000 seed weight, test weight and head diameter. The experiment was carried out during the 2006 -2010 period in the experimental field of the Agricultural University -Plovdiv, with the PR64E83 hybrid. Variants of the experiment: 1) without irrigation; 2) optimum irrigation at 75% of FC; 3) without first irrigation; 4) without second irrigation; 5) without third irrigation. The optimum irrigation regime increased the value of the 1000 seed weight, test weight and head diameter. There were no significant differences in the variants with irrigation canceling.Key words: sunflower, irrigation, 1000 seeds weight, test weight, head diameter. ВЪВЕДЕНИЕСлънчогледът е сухоустойчив, но реагира много добре на напояване, особено през години с продължителни засушавания през периода от бутонизация до наливане на семената (включително). Благоприятният водно-въздушен режим в активния почвен слой на културата води до увеличаване на добива, като наред с това се променят и някои от стойностите на структурните му елементи. Съществуват противоречия относно това дали почвено-климатичните условия в района на Пловдив са благоприятни за развитието на слънчогледа. Според изследвания на Тahsin et al. (2006) продуктивността на редица съвременни слънчогледови хибриди не се отличава от установената за други, типични за културата райони на страната.Основните изследвания у нас, свързани с оптимизиране на поливния режим на културата, са проведени основно през 70-те и 80-те години на миналия век. При напояване по схема 70-80-70% от ППВ абсолютното тегло на семената за условията на Югоизточна България се увеличава със 17,3 g, а хектолитровото -с почти 5 kg (Mihov, 1974). Изследвания с напояване на 238 30.
The purpose of this study was to establish the impact of single irrigation during different growth stages on the components of sunflower yield -1000 seed weight, test weight and head diameter. The experiment was carried out during the 2006-2010 period in the experimental field of the Agricultural University -Plovdiv, with the PR64E83 hybrid. Variants of the experiment: 1) without irrigation; 2) optimum irrigation at 75% of FC; 3) first irrigation only; 4) second irrigation only; 5) third irrigation only. The optimum irrigation regime increased the value of 1000 seed weight, test weight and head diameter. There were no significant differences in the variants with only one irrigation.Key words: sunflower, irrigation scheduling, 1000 seeds weight, test weight, head diameter. ВЪВЕДЕНИЕКато една от основните маслодайни култури през последните години слънчогледът заема все по-големи площи. Според Таhsin (2006) районът на Пловдив е благоприятен за отглеждането на културата наред с останалите типични за производството й райони на страната. Известно е, че слънчо-гледът е сухоустойчив, но реагира много добре на напояване. Поради това той може да се отглежда в условията на регулиран воден дефицит върху поливни площи, разполагащи с ограничени водни ресурси. Във връзка с това научноизследователската работа трябва да бъде насочена към установяване на чувствителността на културата през отделните фенофази от вегетацията към воден дефицит, както и на периода, през който реализирането на единствена вегетационна поливка би имала най-висок ефект върху добива и неговите структурни елементи.Според Ghani et al. (2000) даването на две поливки (в началото на вегетацията и през цъфтежа) увеличава диаметъра на питата с 27,3%, в сравнение с ненапоявания слънчоглед, а броят на семената в една пита 31.
Fresh water supplies for irrigation purposes must be used sparingly and judiciously, as water is an invaluable natural resource that is in short supply in much of the Earth. Soil moisture in fields is not uniform everywhere, and deploying thousands of sensors is unnecessarily expensive. The purpose of this publication is to model and predict the relationship between tomato plants leaf color, soil moisture, and thus manage the irrigation process in an optimal manner. The research was conducted using generally accepted methods, the field method, and the method of statistical evaluation of results. Machine learning algorithms (MLA) and data mining are utilized in this paper to model the relationship between RGB color values from tomato leaves and soil moisture and temperature. The color of the leaves of open field tomato plantations grown without stakes is the focus of this study. Three main tasks are fulfilled: to prove that there is a relationship between leaf color and soil moisture, to study its supposedly nonlinear type and to model this relationship with MLA. First, a classifier is trained, and then a model is created and saved. Finally, the efficiency of the chosen model is tested using a different test data set. The name “12-9-6-3” for the methodology of measurements is fgiven. It is proven that the young leaves are more informative about the need for watering. As a result, there is less than a 1% error in predicting soil moisture using the color of tomato leaves considering also soil temperature, using M5P regression model. This predictive model can be used in creation of automated systems for optimal irrigation management and water saving
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