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Hyperspectral Spectroscopic Study of Soil Properties- A Review

Soil analysis is required for efficient use of inputs viz. seeds, fertilizers, irrigation water and other agricultural planning. However, there are several disadvantages of soil analysis such as they are time consuming, expensive and labour intensive. Many approaches are developed to overcome these difficulties. Hyperspectral spectroscopy is emerging as a promising tool for studying soil, water and vegetation. Therefore, an attempt has been made to review the scope of using hyperspectral reflectance spectroscopy for estimation of soil properties as an alternative to traditional laboratory soil analysis methods. Spectral signature of soil can be used for fast and non destructive estimation of soil properties. Diffuse reflectance in 350-2500 nm range of electromagnetic spectra forms the basis of hyperspectral spectroscopy. An object is characterized by the characteristic absorptions and peaks in the electromagnetic spectra. A number of calibration techniques are applied for establishing relationship between reflectance spectra and soil properties. Multiple Linear Regression (MLR), Principal Component Regression (PCR) and Partial Least Square Regression (PLSR) are most commonly used techniques. Review Article Goswami et al.; IJPSS, 32(7): 14-25, 2020; Article no.IJPSS.57229 15 MLR, PCR and PLSR are also used for prediction of several soil properties such as pH, soil organic carbon content, nitrogen, phosphorus, potassium, calcium, magnesium, sodium, iron, manganese, zinc, copper, boron, molybdenum, sand silt, clay and soil moisture. Some commonly used spectral indices are also applied for prediction of soil properties. Some of the soil physical properties viz. sand, silt and clay as well as chemical properties viz. pH and organic carbon could be estimated with good to very good prediction using pure spectra of soil. However, contrasting results of prediction of soil properties using multivariate analysis techniques have also been reported. The content of this review article will be helpful for researchers who are working on alternate methods of estimation of soil properties.

INTRODUCTION
Soil is the most vital natural resource for all the productive activity of the world. Soil provides all the basic requirements of human being i.e. food, feed, fodder, fibre and fuel. Thousands of years are required to produce one centimeter of soil through natural process (weathering of rocks and minerals). On the other hand, human population of the world is increasing at the rate of 1.16% and this rate is even more (1.25%) for South Asian Countries [1]. This has been projected that the human population of the world will reach 8.6 billion in 2030, 9.8 billion in 2050 and 11.2 billion in 2100 from the current population of 7.6 billion [2]. The increasing human population has put tremendous pressure on the natural resources including the soil; most vital natural resource.
Nutrient status of soil is very dynamic (with respect to time) and diverse (with respect to space). Hence, periodic monitoring of nutrient status of soil and inventory of spatial variability map of soil is the need of the hour [3]. Though soil analysis is essential for agricultural planning, this has several disadvantages such as they are expensive, time consuming, and often cause environmental pollution. Therefore, alternative techniques may be developed which are rapid, repeatable, cost effective and environment friendly. This can be achieved through the use of new technologies such as mass spectroscopy, X-Ray diffraction, nuclear magnetic resonance, hyperspectral spectroscopy etc.

HYPERSPECTRAL REMOTE SENSING OF SOIL
Hyperspectral sensors are instruments that acquire reflectance in several, narrow, contiguous spectral bands in the visible, near infrared (NIR), mid infrared (MIR) and thermal infrared (TIR) regions of the electromagnetic radiation (EMR). Laboratory and field studies have revealed that certain soil characteristics exhibit characteristic absorption band, which could be used for their identification. For instance, soil water exhibit weaker absorption bands at 970 nm, 1200 nm and 1770 nm and prominent absorption bands at 1400 nm and 1900 nm. Similarly, gypsum and montmorillonite exhibit absorption bands at 1800 nm and 2300 nm, and between 520 nm and 1000 nm, respectively [4]. Most of the currently operating optical sensors have coarse spectral resolution on the order of 50 to 200 nm. As a result, such measurements are not adequate to resolve subtle variations in soil units arising due to variation in chemical composition. This has led to the development of high spectral resolution spectrometers capable of providing several spectral bands of typically 1 to 5 nm bandwidths. Hyperspectral remote sensing in large continuous narrow wavebands provides significant advancement in understanding the subtle changes in biochemical and biophysical properties of the crop plants and their different physiological processes, which otherwise are indistinct in multispectral remote sensing [5]. Hyperspectral remote sensing techniques have been developed from a laboratory-based near infrared spectroscopy (NIRS) technique [6]. The narrow sensitive band range (10 nm or less) makes it possible to detect subtle variations in the reflectance spectra, which are caused by differences in biochemical composition and physiology of vegetation [7,8]. In recent years, researchers have extended the technique of reflectance spectroscopy to measure biochemical parameters by field spectroradiometer, airborne and space borne sensors, trying to explore the variation in chemical composition in a spatial context [8,9,10]. The potential of hyperspectral spectroscopy has been recognized by soil scientists since a few decades [11,12].
Hyperspectral spectroscopy can be divided into three distinguished types of measurements for soils viz. laboratory measurements, proximal sensing measurements and remote sensing measurements. The two latter techniques are able to collect spectral data in-situ and are therefore usually exploited to map soil properties [13]. Many authors reported the development of spectral sensors mounted on tractors [14,15]. These systems are generally used in precision agriculture to manage the quantity of nutrient inputs into soils [16]. Proximal sensing may also include hand-held measurements, which is used as a fast tool to monitor soil properties in-situ [17,18]. Ben-Door et al.
[19] presented a hyprspectral reflectance device able to collect insitu 3D spectral data through an entire soil profile, allowing a rapid and objective soil classification. Remote sensing of soil properties has also been attempted using aerial photographs [20], multispectral [21] and hyperspectral images (imaging spectroscopy) [22]. Imaging spectroscopy differs from multispectral imaging in its contiguous number of wavebands, enabling precise recording of the spectrum and a detailed analysis of spectral properties of the soil surface. However, the transfer of relationships established at the laboratory level up to higher scales poses several problems associated with possible factors of confusion, such as (i) changes in soil roughness, moisture, illumination and view conditions; (ii) sensor characteristics like spectral and spatial resolution, radiometric calibration which may also change relationships between measured reflectance and actual soil characteristics, and (iii) possible atmospheric effects.
Reflection spectra have been used for many years as one of the source of information about variation in earth surface composition. A wide range of information can be obtained from natural and chemical properties of soil [23]. This is mainly based on specific absorption of spectrally active groups known as chromophores such as Fe, OHin water and minerals, CO

SPECTRAL SIGNATURE OF SOIL
The spectral reflectance of soil varies with a range of chemical and physical properties which facilitates discrimination of different soils [13,24]. The most important characteristics of a soil influencing properties are: Moisture (inversely proportional to reflectance; wet soils appear darker than dry soils), organic matter (inversely proportional to reflectance; increasing organic matter content gives darker soils), texture (sandy soils are more reflective than clay soils), surface roughness (inversely proportional to reflectance; decrease in surface roughness slightly increases reflection), iron content (increase in iron oxide changes soil colour towards brick-red resulting in increased reflection in the red and a decreased reflection in green region) [22,24,25].
The soil properties influencing the spectral reflectance are known as chromophores. Soil chromophores may be chemical chromophores or physical chromophores based on their nature of influence on the soil spectrum [26]. The incoming EMR is absorbed at discrete wavebands by the chemical chromophores. On the contrary, physical chromophores influence the entire spectra of EMR [27]. Therefore, sharp reflection and/ or absorption peaks might be attributed to presence or absence of chemical chromophores. Physical chromophores influence the shape of the reflectance spectra. Soil moisture, organic matter, clay minerals and iron oxides are dominant chemical chromophores influencing reflection and absorption peaks of soil spectra. On the other hand, sand, silt, clay and geometry are dominant physical chromophores influencing the shape of reflectance spectra [28].
Spectral reflectance decreases with increase in gravimetric soil moisture content ( Fig. 1) [28]. This is attributed to presence of O-H bond which is the strongest absorber of EMR. For stretched O-H bond, absorption peak use to occur in 3106 nm, for H-O-H bending, absorption peak occurs in 6079 nm and for asymmetric O-H stretching, absorption peak occurs in 2903 nm spectral band in the EM spectra [29]. Again, clear absorption peak occurs in 1400 nm due to presence of O-H overtone stretching. Absorption peak in the 1900 nm is due to combination of H-O-H bending and O-H stretching [30]. On the other hand, absorption peak in 2200 to 2300 nm occurs due to combined influence of metal-OH bending and O-H stretching [29]. Soil moisture is the most dominant chromophore which may influence all other chromophores in the reflectance spectra of soil [31].
Soil Organic Matter (SOM) and its intermediate decomposition products significantly influence the spectral reflectance of mineral soils [32]. SOM has inverse relation with spectral reflectance of soil, removal of SOM results in increase in spectral reflectance of soil ( Fig. 2) [33]. Absorption peaks occurring due to presence of SOM and its intermediate decomposition products are weak which may not able to distinguish with naked eye [34]. However, influence of SOM on the overall spectral signature of soil is distinct in the visible region of electromagnetic spectra [23].
Clay minerals are also found to have significant influence on the spectral signature of soil [35]. The OH functional group use to be associated with the 2:1 type octahedral sheets or with the water molecules adsorbed to the mineral surface (lattice water). Therefore, all the absorption characteristics shown by OH group are shown by the clay minerals in the reflectance spectra [36]. Again, iron content also significantly influence the spectral reflectance of soil in the form of Fe 2+ and Fe 3+ oxides or its impurities [37]. Spectral reflectance of dominant clay minerals has been studied adequately by Clark [30] (Fig. 3). Among the physical chromophores, particle size of soil is the most dominant factor influencing the spectral signature of soil. Spectral reflectance of soil increases exponentially with the decrease in particle size, particularly when particle size is smaller than 0.4 mm diameter (Fig. 4) [38]. Soil surface becomes smoother as the particle size decreases and thus they reflect more part of the incident EMR. On the contrary, increase in particle size increases the surface roughness, thus major portion of the incident EMR gets trapped in the spaces between the soil particles resulting in lower reflectance [23,39].
Stoner and Baumgardner [25] identified five characteristic soil spectral reflectance curves which they considered representative of the diversity of soil reflectance found in wide ranges of naturally occurring surface soils. These curve forms were identified by curve shape and the presence or absence of absorption features representing distinctive organic matter and iron content, as well as texture. Das et al. [28] studied the spectral signature of major soils of India and it was found that the spectral reflectance varied across soil types. Vertisols of Karnataka showed lower soil reflectance in the entire electromagnetic spectra compared to the Inceptisols of Uttar Pradesh (soils of Agra region) and Aridisols of Rajasthan (soils of Jodhpur region). This was due to darker colour of Vertisols in comparison to Inceptisols of Agra region and Aridisols of Jodhpur region. On the other hand, deep red Alfisols of lateritic origin showed intermediate spectral reflectance values (Fig. 5).
The analysis of mineralogy with spectral proximal sensing has made great progress over the years. Nowadays, several institutes provide spectral libraries with comprehensive collections of a wide variety of materials. For example, the ASTER spectral library version 2.0, which is a collection of contributions from the Jet Propulsion Laboratory, Johns Hopkins University and the United States Geological Survey, is a widely used spectral library which contains over 2400 spectra of a wide variety of minerals, rocks, vegetation and manmade materials covering the wavelength range of 400 to 1540 nm [40]. Partial Least Square Regression (PLSR) can be used to match collected spectral samples to those in the spectral libraries [41].
Global spectral library with 23631 soils representing 92 countries have been developed in which only 67 soils were from India [42]. There is no reported study on spectral signatures of soil and its correlation with soil properties for the North Eastern hill region of India. With a large variation in soil properties across our country, there is a requirement for developing more extensive spectral libraries representing specific regions and there are initiatives to expand existing spectral libraries into a national soil spectral library [43].
Reflectance data have been successfully used for study of soil properties such as moisture, soil organic carbon (SOC), inorganic carbon, total nitrogen (N), cation exchange capacity (CEC), pH, potassium (K), magnesium (Mg), calcium (Ca), zinc (Zn), iron (Fe) and manganese (Mn) with various levels of accuracies [44]. Since spectral signature of soils reflect a set of soil properties like organic matter content and some chemical and biological properties, some researchers have hypothesized that spectral signature could probably be used to discriminate clusters of soil samples differing in their quality.

MULTIVARIATE ANALYSIS FOR PREDICTION OF SOIL PROPERTIES
Hyperspectral data being of large volume, overlapping of weak overtones with fundamental vibrational band makes it difficult for direct interpretation. Therefore, a number of calibration techniques are applied for establishing relationship between spectra and soil properties. Multiple Linear Regression (MLR), Principal Component Regression (PCR) and PLSR are most commonly used techniques [45]. A number of indicators are used for validation of prediction of soil properties such as coefficient of determination (R 2 ), Root Mean Square Error (RMSE), Ratio of Performance to Deviation (RPD), Ratio of Performance to Inter Quartile (RPIQ) and Bias [46].
For quantitative prediction of chemical soil properties such as pH, PCR has been reported to be best multivariate method [47], followed by PLSR [48] and Stepwise Multiple Linear Regression (SMLR) [49]. Again, PLSR has been found to be most suitable multivariate method for quantitative prediction of soil carbon [50,51] followed by PCR [52]. Similarly, for quantitative prediction of total soil nitrogen, PLSR has been observed to be the most suitable multivariate method [50]. However, PCR has been found to be most suitable for quantitative prediction of mineralized soil nitrogen [52]. On the contrary, Neural Network (NN) was fond to be most suitable quantitative prediction of available soil phosphorus and available potassium [53]. However, PCR is most suitable for quantitative prediction of exchangeable potassium [52]. MARS [35] and PCR [52] have been found to be most suitable multivariate method for quantitative prediction of CEC, Ca 2+ and Mg 2+ . For prediction of micronutrients such as Cu and Fe, modified PLSR has been reported as most suitable for quantitative prediction [54]. On the other hand, PCR was found to be most suitable multivariate method for quantitative prediction of Zn and Mn.
For quantitative prediction of physical soil properties such as sand (%), PCR has been reported to be best multivariate method [52] followed by Multivariate Adaptive Regression Spline (MARS) [35] and modified PLSR [54]. Similarly, PCR has been reported to be best multivariate method for quantitative prediction of silt [52] followed by modified PLSR [54] and MARS [35]. On the other hand, modified PLSR has been reported to be the best multivariate method for quantitative prediction of clay [54] followed by MARS [35] and PCR [47,52]. Again, PCR and SMLR have been found to be most suitable multivariate method for quantitative prediction of moisture content of soil [47,49].
Soil pH has been predicted with R 2 value of more than 0.8 at local level [55,56] and at regional level [57,58]. However, at global level, pH has been predicted with R 2 value of more than 0.7 [35]. On the other hand, this has been observed that pH has been predicted with R 2 value of less than 0.5 at local level [59,60] and at regional level [61]. SOC has been predicted with R 2 value of more than 0.9 at local level [62,63] and regional level [62,64,65,66,67,68,69,70]. However, at global level SOC has been predicted with R 2 value of more than 0.8 [71]. On the contrary, R 2 value of less than 0.5 has been reported for predicted SOC at local level [60]. Macro nutrients of soil such as N, P, K, Na, Ca, Mg and micro nutrients such as Fe, Mn, Zn, Cu, B and Mo has been found to be predicted with R 2 value of less than 0.5 [72,73].
Soil physical properties such as sand content was also predicted with R 2 value of more than 0.8 at local level [59,60], R 2 value of more than 0.9 at regional level [57] and R 2 value of more than 0.7 at global level [35]. On the contrary, R 2 value of less than 0.5 was predicted at the local level [60] as well as at the regional level [61,69]. Silt content with R 2 value of more than 0.7 was predicted at the local level [45,74] as well as at the regional level [57]. At the global level, R 2 value of more than 0.6 was predicted for silt [35]. On the contrary, R 2 value of less than 0.3 was predicted at the local level [59,60] and R 2 value of less than 0.4 was predicted at the regional level [61,69]. On the other hand, clay content has been predicted with R 2 value of more than 0.9 at the local level [59], more than 0.8 at the regional level [69,75] and R 2 value of more than 0.7 at the global level [76]. On the contrary, R 2 value of less than 0.3 was reported at the local level [73,77], while R 2 value of less than 0.5 was reported at the regional level [78,79].

SPECTRAL INDICES FOR ESTIMATING SOIL PROPERTIES
Although a qualitative interpretation of hyperspectral spectra through visual analysis can be achieved [25], direct quantitative prediction of soil characteristics is almost impossible because soil constituents interact in a complex way to produce a given spectrum. Statistical models are usually used for quantification of the property of interest which is known as Chemometrics. Geladi [80] has reported the overview of the use of chemometrics in spectroscopy. The quantitative analysis of HRS data may be conducted in two ways, both requiring the implementation of multivariate statistics [81]. Firstly, clustering techniques can be used to discriminate samples or to detect changes in sample properties [82]. On the other hand, regression methods can be used for prediction of unknown properties using calibration equations which relate spectral information to sample properties [52].
An increasing number of studies emphasize the ability of hyperspectral spectroscopic analysis for quantitative prediction of soil physical, chemical and biological properties [43]. Most hyperspectral regression models are based on laboratory measurements under controlled conditions, which avoid disturbing factors characterizing field measurements like soil moisture content, soil roughness and vegetation cover [17]. Some of spectral indices used for estimating soil properties using spectral reflectance are Simple Ratio Index (

CONCLUSION
Assessment of soil physical and chemical properties is important for understanding the spatial variability of soil. Traditionally, soil samples are collected and analyzed in the laboratory for the soil fertility properties for assessment of spatial variability. Spectral signatures of soil reflect variation in some of the important soil properties viz. moisture content, organic carbon content, particle size and type of clay minerals. Hyperspectral spectroscopy has been found to be useful in estimation of soil properties with moderate accuracy level. Some authors have reported encouraging results for prediction of soil physical (sand, silt & clay) and chemical properties (pH & OC). On the contrary, many authors have reported contradictory results on prediction of soil properties using the multivariate analysis techniques. However, the regression models will be useful for researchers who are working on alternate methods for estimation of soil properties. Spectral indices are found to predict soil properties with low level of confidence. Therefore, there is a scope for development of spectral indices capable of assessing and predicting soil properties for major soil types.

DISCLAIMER
The products used for this research are commonly and predominantly used products in our area of research and country. There is absolutely no conflict of interest between the authors and producers of the products because we do not intend to use these products as an avenue for any litigation but for the advancement of knowledge. Also, the research was not funded by the producing company rather it was funded by personal efforts of the authors.


provenance: AgriculturalAndFoodSciences,2019-2020-Agricultural And Food Sciences-2020.jsonl.gz.gz

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Onfarm Validation of Agricultural Technologies for Supporting Tef Extension Package Formulation in Ethiopia

Tef is an important crop in Ethiopian production system because of its dual function both as a staple crop that improves food security and as an income-generating crop. However, the grain yield is low, at 1.75kgha . The objectives of this research were; to compare biological superiority of the treatments with full technology package; to conduct partial budget cost-benefit analysis of the treatments and to improve the full package of recommendations by incorporating benefits derived from the production with identification of possible ways to reduce the cost of production by constructing partial budget model. Economic constraints and opportunities for improving tef production systems in Ethiopia must be understood as the basis for research and developing interventions. The field experiment comprising three interventions packages on the tef production system namely: extension package, Agricultural transformation Agency of Ethiopia package and the research package (which had been split in to two sub packages which were row and broadcast planting) application was laid out in a randomized complete block design with the replication(farmers/ locations as replication). The field experimental plot size was 500m. This study presented both the agronomic yield comparison of the four packages and the partial budget analysis (PBA) framework for the economic analysis of different tef package treatments for their benefit returns. The result indicates that research package on broadcast planting and raw planting systems were found to be superior in grain yield 1580kgha and 1550 kgha, respectively. Similarly research row sowing and broadcasting recommendations were gave higher above ground biomass 10167kgha and 10000kgha, respectively as compared to the ATA and Extension package practice. Thus, the result indicates that seed rate of 10-15 kgha both broad cast and row sowing gives better grain yield and shoot biomass providing the highest return with marginal rate of return , whereas ATA package was found to be the least economically viable treatment having minimum MRR. The partial budget analysis revealed that net returns of treatments extension package, research row planting package and research broadcasting package exceeded the net return of the controlATA package by Ethiopian birr (EB) (0.32), 1.09 and 1.65, respectively (US$ 1 = EB 27.49). The decrease in cost for treatment of extension package relative to the control-ATA package was EB 1.03; the added net benefit from this treatment was EB 0.75 per unit, giving a marginal rate of return of 137%. The decrease in cost of treatment research with row planting package relative to treatment of the control-ATA package was EB 71%, while the increase in net return was EB 32.6 per unit of production, giving a marginal rate of return on the increased expenditure of 218%. The relative decreasing cost of treatment research tef broadcast planting was EB 60.7% per unit of production as compared to the control-ATA package, while the increase in net return relative to treatment the control was EB 3.38 for a marginal rate of return of 1795%. Given the high cost of capital, treatments of the control-ATA and the extension package cannot be recommended as they indicate negative benefit cost ration with (0.51) and (0.31) respectively while 1.09 and 1.65 for research row planting and broadcast planting, respectively yet; the broadcast planting of tef production indicated superior in returns of EB 0.65 for EB 1 invested in the production at small scale level. Considering the lack of appropriate tef row planting at the moment, broadcast planting with 10-15 seed rate should be used as tef production package in the country.

Introduction
Tef (Eragrostis tef) is the most important cereal crop of Ethiopia. The crop is annually grown on over 3.02 million hectares of land, accounting for about one-third of the total cereal acreage and about one-fifth of the gross cereal grain production in the country (CSA, 2015). It is grown by about 6.6 million smallholder farmers. Tef offers numerous advantages over the other cereals grown in the country with respect to both husbandry and utilization of both the grains and the straw. The crop grows under wider range of ecological conditions from sea level up to 3000meters above sea level and performs better than the other cereals under adverse and margin-al conditions. Tef constitutes the main daily staple food for over 70 million Ethiopians providing good nutrition for the consumers. Furthermore, tef straw has a much value as the grain because of its use for fodder, bedding and construction material. Thus, it is valued for the quality of grain and fodder that it provides, both of which have a high market price (Assefa et al., 2011).
Tef is a very nutritious cereal grain. Its nutritional content is generally comparable to that of the major world cereals like wheat, barley, rice, maize and sorghum. In fact, it is superior in many aspects particularly in minerals such as iron, calcium, magnesium and zinc. In recent years, tef has become popular as health and performance food in the global market. Since the grains are gluten-free, it is useful as food for humans suffering from gluten protein allergy ailments known as celiac disease (Spaenij-Dekking et al., 2005). Its low glycemic index characterized by slow release type starches make it particularly suitable for diabetic people. Moreover, its high iron content is associated with the low prevalence of hook-worm (Ethiopian Nutrition Survey, 1959) and pregnancy related anemia in people consuming tef as staple food. As tef is gluten-free and rich in amino acids and minerals, especially iron and calcium, it is widely marketed in Europe and the USA-in organic stores as well as via the Internet-and appreciated by the Ethiopian communities. In cooperation with American and European institutes, Ethiopia is breeding tef with higher yields-by traditional selection, hybridization, and marker-assisted breeding (Heiniger, U., 2016).
As Ethiopia's population is ever increasing, so too will the demand for grain. Moreover, tef is one of the most important crops for Ethiopia's agricultural economy, both in terms of consumption and production (Worku et al. 2014). Its high nutritional qualities and the absence of gluten make tef increasingly known even outside Ethiopia, which increases the demand for tef (Andersen and Winge 2012). The area of tef has been increasing gradually from time to time partly because of the general increase in the total cultivated area and partly at the expense of the area of the other cereals. At the same time, both the production and productivity have also increased due to the development of new varieties.
Scientific research on tef was started in 1950's. Over the years commendable achievements have been made with respect to the development of improved technologies involving varieties along with improved management practices, generation of information and promotion of improved technologies. The mean tef yield is lower (1.58 t ha -1 ) than other cereal crops such as maize (3.4 t ha -1 ), sorghum (2.4 t ha -1 ), wheat (2.5 t ha -1 ), and barley (1.97 t ha -1 ) (CSA, 2015). And this is far lower than the potential yield of 6 t ha-1 estimated by Ketema (1997), primarily because of low access to technology/innovations (Assefa et al., 2011). The need for a new and updated national tef research is felt in order to tackle priority problems of tef through concerted up-to-date research and increase its productivity and production and thereby contribute to the overall agricultural transformation plan of Ethiopia.
Cost of production statistics generally only benefits the data suppliers indirectly through improved policymaking, better administrative decisions and more efficient markets. However, there is also potential for the data supplier, namely the farmers themselves, to reap direct benefits. At the farm level, Cost of production data contributes to improve the economic assessment of farm operation. They allow the producer to question his own operation and to benchmark it against the best practices of farms in the same region with similar characteristics. This, in turn, can lead to better informed decisions at the farm-level and improved market efficiency and performance.
A recommendation is information that farmers can use to improve the productivity of their resources. A good recommendation can be thought of as the practices which farmers would follow, given their current resources, if they had all the information available to the researchers. Farmers may be able to use a recommendation directly, as in the case of a particular variety. Or they may adjust it somewhat to their own conditions and needs, as in the case of a fertilizer level or storage technique. The agronomic data upon which the recommendations are based must be relevant to the farmers' own agro ecological conditions, and the evaluation of those data must be consistent with the farmers' goals and socioeconomic circumstances.
Cost of production statistics provide farm extension workers with evidence to support their training and outreach activities, which helps evaluate an individual farm's management practice against norms for the region. It also allows better targeting to the largest payoffs for their activities, which, in turn, elevates productivity.

Objectives
 To compare biological superiority of the treatments with full technology package.  To conduct cost-benefit analysis of the treatments as well as full technology package.  To improve the full package of recommendations by incorporating gainful information derived from treatments.

METHODOLOGY 2.1. Field Experiment
Four different packages were taken for comparison of returns these were; Extension Package-which was an old recommendation of the research and it's still applied by Ministry of Agriculture extension system, Agricultural transformation agency (ATA) of Ethiopia system which is the new recommendation, New agronomic research finding of row sowing method recommendation and New research broadcasting recommendations with different seed rate, fertilizer, herbicide, insecticide, and agronomic management system were used as treatments ( Table 1).
Journal of Biology, Agriculture and Healthcare www.iiste.org ISSN 2224-3208 (Paper) ISSN 2225-093X (Online) Vol.10, No.17, 2020 3 The experiment were carried out at five locations (four on farm and one on station) which were used as replication and each plot size of 20mx25m (500m 2 ). The variety used was Kora.

Data and Methods of Analysis
Relevant agronomic data were collected from the experimental trial. Primary data on grain yield, above ground biomass and straw was calculated. Mean comparison of the four packages were done for agronomic traits collected (Table2). On the other hand, cost data were collected on labor and oxen rent, and application rates of inputs such as seed, fertilizer and pesticides were based on recommendations used for the trial. Data were initially calculated for each farmer separately and then combined across three locations. All costs and revenues were quantified based on 500m 2 and converted to hectare base; furthermore mean extrapolated to the hectare basis. Because of the wide variety of cost concepts, it is not possible to deal with all of them in a single section; for reason only the following items was dealt with for short term benefit:- Variable costs  Total and average costs  Marginal costs  Gross margin  Benefits cost ratio Variable costs: -Variable costs are a function of output and are only incurred if there is production. There is therefore a relationship between the volume of production and costs. For this study variable costs are seed, fertilizer, pesticide, wage rate, and oxen rent if production decisions have to be made on the quantities of variable inputs that must be used to maximize benefit over the short term, only variable costs are relevant since fixed costs remain constant.
Total costs: -Total costs are the sum of the total fixed and total variable costs, for this study of the short-term analysis variable only variable cost was taken. CpT = CS+CF+CP+CoR+CL (1) Where:-CPT= cost of production of tef CS= cost of seed CF = cost of fertilizer CP = cost of pesticides COR= cost of oxen rent CL= cost of labor-(which includes cost of planting, cost of fertilizer application, cost of hand weeding, cost of Journal of Biology, Agriculture and Healthcare www.iiste.org ISSN 2224-3208 (Paper) ISSN 2225-093X (Online) Vol.10, No.17, 2020 insecticide spraying, cost of herbicides spraying , cost of harvesting and cost of threshing) Average costs: -Average or unit costs are the costs per unit such as cost per kilogram or quintal, per hectare, per liter. Average variable and average total costs can, depending on the circumstances, be calculated by dividing the specific cost amount by the corresponding units. AVC= (2) As in short run analysis focus on the operational cost analysis and the fixed cost is constant then; The assumption is that for this research the fixed cost is constant and taken the variability among the costs that can be used for validation of benefits for different practices; so that ATC equals to AVC.
Marginal costs: -marginal costs are the extra or additional costs attached to the last unit of output marginal costs are calculated by dividing the change in costs (△ costs) by the change in output (△ yield), that is: Marginal costs are only determined by an increase in variable costs. As long as marginal income is bigger than marginal costs, the benefit will be increased.
(4) Tells us how much cost rises per unit increase in yield of tef. Marginal cost for any change in output is equal to shape of total cost curve along that interval of yield. If the MC> AVC then the average cost is rising for kilogram of tef yield per plot or per hectare. If the MC=AVC then the average cost is at its lowest point. If MC<AVC then the average cost is falling for kilogram of yield. Benefit cost ratio: -is an indicator, used in cost-benefit analysis, which attempts to summarize the overall value for money of a tef production treatments. It is an important tool to assess economics of farming. It is the ratio of all net value of tef produced after deducting the costs of different inputs after their summation in the production process. BCR= (5) Where; BCR= benefit cost ratio GB= gross benefits TVC= total variable cost Marginal rate of return: -technically, the marginal rate of return is the marginal return or the amount of revenue per additional item, divided by marginal cost (the cost per additional item produced). In other words, it's the amount of additional revenue that a tef production can expect to earn per each additional birr that it spends on production. Using marginal rate of return, a farmer can determine whether or not its operations has a benefit or loss.
Marginal rate of return becomes most powerful when it's used as a decision-making tool. As long as a marginal rate of return is greater than one, a farmer can make a profit by producing one additional unit. Because marginal rate of return tends to decrease as more and more units are produced, a farmer will maximize its benefits by expanding production until its marginal rate is one. Basically, this is where marginal revenue equals marginal cost (MR=MC). If a company produces beyond this point, the marginal rate of return drops below one (MR<1), and the company will be spending more per each additional item than it is bringing in revenue.

RESULTS DISCUSSION
Research both broadcasting and row sowing recommendations gave better grain yield 1580kgha 1 and 1550kgha -1 , respectively. Similarly research row sowing and broadcasting recommendations were gave higher shoot biomass 10167kgha -1 and 10000kgha -1 , respectively as compared to the rest treatments. It indicates that straw yield for the two research practices were better than the ATA and Extension package practice. The result indicates that seed rate of 10-15 kgha -1 both broad cast and row sowing gives better grain yield and aboveground biomass. From this experiment, the two-planting methods row sowing and broadcasting revealed the same results considering the lack of appropriate planting machine for tef in Ethiopia for the time being. Therefore, we can conclude that the research recommendation and farmers practice are better for tef production than the ATA and Extension package recommendations (Table 2). According to Hailu, G. et al. (2017); the major drivers for productivity differences appear to be the levels of input use, so this research applied different package system of inputs for productivity and validated that the research broad casting has more advantage.

ΔTC MC 
Journal of Biology, Agriculture and Healthcare www.iiste.org ISSN 2224-3208 (Paper) ISSN 2225-093X (Online) Vol.10, No.17, 2020  On station level analysis of treatments indicate that the net revenue for treatment of extension package, ATA package, research with row planting and research with broad cast planting system show a positive return from the farming investment for production of tef; which was found 44,640.20, 31,000.20, 54,164.20 and 58,371.20 birr per hectare. The return from the treatment of research with broadcasting planting system application has 27,371 birr returns of benefits when compared to the ATA package treatment. Considering the first household on farm trial had a loss of (19,989.80) and (23,604.20) birr per hectare in the first and second treatments while he had a positive net return of 46,789.20 and 50,991.20 birr hectare from third and fourth treatments; which indicate that recommendation of treatment four is superior to the household on farm tef production as compare to the rest of the application modalities. On the other hand application of treatment packages on the second household on farm trial though all the management system had a positive return still research broadcasting had a good net benefit returns when equated to the rest with gross net benefit of 58,371.2 birr per hectare (Table 3 and 4). Source: own data computed 2017 Note: Tef grain price 2200 birr/ql; straw price= 500 birr/ql, and plot area = 500 m 2 Note: Tef grain price 2200 birr/ql; straw price= 500 birr/ql, and plot area = 500 m 2 , ql= quintal which equivalent to 100kg Based on the trial record sheet kept by researchers' close observation, the total variable costs were determined using the respective input prices. On average, the total variable cost for inputs in tef production was found 33,559.80 birr per hectare with the application of package. From the gross total variable cost the oxen rent has incurred 15,490.00ha -1 birr which is covering the 46.2% and 14840 birr for labors which 44.2% out of the gross. The total variable cost for treatment of ATA package, research with row planting and research with broad cast Journal of Biology, Agriculture and Healthcare www.iiste.org ISSN 2224-3208 (Paper) ISSN 2225-093X (Online) Vol.10, No.17, 2020 6 varies accordingly with 34,679.80, 24,965.80 and 21,043.8 birr per hectare respectively. The highest yield per hectare in kilogram was recorded in treatment of research with application of broadcast planting which was 1,580 while research with row planting was 1,550; at the same time yield for extension package and ATA package was found 1,083.33 and 993.33 kg per hectare; and tef market price per kg in the sample district was 22 birrs (Table  5).
Net gross revenue with the assumption that if the farmer sells its entire yield the gain per hectare was found for each treatment-for extension package, for ATA package, research with application of row planting and research with application of broadcast planting system had gross revenue of 56,333.33, 51,678.33, 77,183.33 and 76, 860 birr per hectare; this state that research applying row planting has the upper rate of gross benefit while the net benefit was found 22,773.53, 16,998.53, 52,217.53 and 55,816.2 birr per hectare tef production. When the treatment four is equated to treatment two the first has on average a net benefits of 38,817.67 birr per hectare for tef production (Table 5). Rule of thumb, when the farmer output is relatively small, the average cost decreases, whereas when the output starts increasing, the average cost increases too. Farmers producing tef that seek to maximize their profits, use the average cost to determine the point that they should shut down production in the short term. Therefore, if the price of a tef is higher than the AVC of the good, it means that the firm is covering all the variable costs. In this case, farmers will continue in tef production. On the contrary, if the price they receive for tef yield is lower than the AVC, firms cease production to avoid additional variable costs. Benefit-maximizing farmer will use the AVC to determine at what point they should shut down production in the short run. If the price they are receiving for the good is more than the AVC given the output they are producing. As long as price is above the AVC and covering some of the total variable costs, you are better off continuing production. If the price falls below the AVC, then the farmer may decide to shut down production in the short run because the price is no longer covering any portion of the all of the variable costs (Table 6).
Marginal cost the increase or decrease in the total cost of a production run for the production of additional unit of tef. The purpose of analyzing marginal cost is to determine at what point of a farmer can achieve economies of scale in tef production. The calculation is most often used among farmers as a means of isolating an optimum production level. Change of tef production from ATA package to extension package the total production cot for unit tef per hectare decreases by 12.45 birr while change of production from treatment of research with row planting can decrease cost for unit tef per hectare by 17.45 birr (Table 6). Marginal costs are variable costs consisting of all input costs in the production at the short run. In companies where average costs are fairly constant, marginal cost is usually equal to average cost. However, in small scale tef production at household level require minimum capital investment as compare to commercial investment in tef producers as a rule of thumb and have low average costs, it is comparatively very low ( Table 6).
Journal of Biology, Agriculture and Healthcare www.iiste.org ISSN 2224-3208 (Paper) ISSN 2225-093X (Online) Vol.10, No.17, 2020 7 The productions of tef with a benefit-cost ratio greater than 1 have greater benefits than costs; hence they have positive net benefits. The higher the ratio, the greater the benefits relative to the costs; note that simple benefitcost ratio is insensitive to the magnitude of net benefits and therefore may favor production with small costs and benefits over those with higher net benefits. (This problem can be eliminated by the use of the incremental benefitcost ratio or the net present value.) The higher the BCR the better the treatment to apply; general rule of thumb is that if the benefit is higher than the cost the production process in tef is a good investment. If a project has a BCR that is greater than 1, it indicates that benefits outweigh of the costs. Therefore, the treatment should be considered if the value is significantly greater than 1. If the BCR is equal to 1, the ratio indicates that expected benefits equal the costs. If the production BCR is less than 1, the costs outweigh the benefits and it should not be considered. Considering Table 6 treatments of extension package and ATA package had a BCR of (0.32) and (0.51), which indicates that the two treatments cost has outweighed the benefit that show every birr of 1 cost added will result a loss of 0.32 and 0.51 birr; while applying treatment of research row planting and research broadcast planting in tef production at small scale level had a benefit of 1.09 and 1.65 birr for each 1 birr of its cost invested (Table 6). Recommendation and findings of Hailu, G. et.al (2017) states that reducing the costs of remoteness through the construction of rural roads and increasing distribution outlets of modern inputs is likely to have a positive impact on tef productivity; this study also justifies that producers of tef in the nation are widely dispersed so input costs mark-up can vary accordingly and will have impact on the change of TVC and BCR.

CONCLUSIONS AND RECOMMENDATIONS
The objective of this on farm experiment was to validate and recommend on farm economically superior technology packages to small scale farmers who are engaged in the tef production. keeping constant all other factors that can create a variation among smallholder producers and soil type variability the result indicates that research package on broadcast planting and raw planting systems were found to be superior in the potential producer of sample selected districts research both broadcasting and row sowing recommendations gave better grain yield 1580kgha -1 and 1550 kgha -1 , respectively. Whereas ATA package and extension package recommendations gave grain yield 993kgha -1 and 1083 kgha -1 , respectively. Similarly research row sowing and broadcasting recommendations were gave higher above ground biomass 10167kgha -1 and 10000kgha -1 , respectively as compared to the ATA and Extension package practice. The result indicates that seed rate of 10-15 kgha -1 both for broad cast and row sowing gives better grain yield and shoot biomass providing the highest return with marginal rate of return of, whereas ATA package was found to be the least economically viable treatment having minimum MRR. However, the profitability of the four treatment packages varied across the three farm trials. The variation could be both due to the treatments and location specific condition with soil type variability or other different heterogeneous factors; yet the research packages with two different planting methods were found high yielding with low total variable cost incurred and high benefit cost ratio as compared to other treatments. So; it was found that the research package with broadcast planting method of tef was more profitable and followed by the raw planting methods when compared to the extension and ATA packages. Intervention and scaling up of the two methods of planting in research package can benefits farmers to gain good returns as compared to others for profitability and to increase the market supply or sustaining consumption of the household. This study recommends a research package that reduces the TVC can increase profitability; which Hailu, G. et.al (2017) also stated innovations that reduce labor requirements for growing tef might satisfy the increasing demands for tef at an affordable price.


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Biochemical profile, antioxidant capacity and allelopathic effects from five Ziziphyus spina-christi (L.) provenances growing wild in Saudi Arabia

The aim of this work was to evaluate phenolic profile, antioxidant capacity and allelopathic effects of six Ziziphyus spina-christi provenances in Saudi Arabia. Total phenols, flavonoids, tannins and antioxidant activity were evaluated. Total phenols, condensed tannins and total flavonoids were present at levels of 62.29 mg GAE/g DM, 16.69 mg CE/g DM and 15.45 μg mg QE/g DM, respectively. The high antioxidant activity (0.15 mg/ml) was noted in Mecca Road provenance. The highest germination, shoots and radicle lengths of tested species were observed in At-taif provenance. Z. spina-christi leaf extracts may be suggested in foods and pharmaceutical industries. Leaf extracts could also provide a natural herbicide with a positive impact on the environment. Provenance of Jizan, Northern Borders and Mecca Road were shown to be particularly effective in antioxidant capacity, while Provenance of Riyadh and Northern Borders shown to have the best allelopathic activity.

Introduction
Ziziphyus spina-christi (Z. spina-christi), an evergreen tree, had been credited with many medicinal fields of applications, including immunity and nutrition (Jiang et al., 2007). The fruit of Z. spina-christi, as known as 'Nbeg', tasted like a mixture of dates and apples and was usually eaten fresh or dried (Bukar et al., 2015). Many glycoproteins, proteoglycans and glycopeptides had been identified from the Z. spina-christi honey (Seif Eldin et al., 2015). In addition, the allelopathy activity, an important biological process in ecology, had been widely employed to protect crops and replace herbicides, fungicides and insecticides being harmful to belongs to the family of Rhamnaceae with about 85 species and Ziziphyus is the most common plants of economic importance in Saudi Arabia and are the major floral sources of high-valued expensive honeys Alqarni, 2015). Z. spina-christi can grow either as a tree or as a shrub. The leaves are short, the flowers are pedunculated and the yellow or red fruits are edible . Ziziphyus jujuba, a plant locally grown in Saudi Arabia and used extensively for its health benefits. The medicinal properties of Ziziphyus tree, also known as Nabq or Sidr, were also recognized and have been in use in Pharaonic carpentry, diet, and medicine (El-Ansary et al., 2018). Z. spina-christi is a medicinal plant and its leaf extract (peptide and cyclopeptide alkaloids) has neuroprotective and therapeutic roles against pentylenetetrazol convulsant effect (Waggas et al., 2010). The Quran mentions the sidr tree twice and accordingly it is highly respected by the Muslims throughout the Middle East (Farooqi, 1997). It is traditionally used in the Muslim countries to wash the bodies of dead Muslims prior to burial, with water in which Ziziphyus jujuba leaves had been soaked (Dafni et al., 2005. In Saudi Arabia, it is used for the treatment of many diseases like wounds, ulcers, etc. Mizrahi et al. (2002) reported that Ziziphyus species are cultivated in hot and arid regions. Some pharmacological screening studies indicated that Z. spina-christi leaves appear to be a safe alternative to lower the blood glucose level. Honeys originating from Sidr (Ziziphyus spina-christi L.) trees in Saudi Arabia exhibited substantial antimicrobial activity against pathogenic (Owayss et al., 2020). Leaves of Ziziphyus jujuba contain a compound known as Ziziphyus which demonstrates medicinal properties and is commonly used in traditional medicine. Among the medicinal properties of Ziziphyus jujube are sedative properties, anticancer, antioxidants, antimicrobial and anti-inflammatory effects (Li et al., 2005;Abdel-Zaher et al., 2014). In Saudi Arabia, Ziziphyus spina-christi is one of the most popular species of Ziziphyus. It is a wild and cultivated plant distributed in the Middle East, Pakistan and in the North and East of Africa (Alansi et al., 2016).
In this study, total phenolic, total flavonoid, condensed tannin contents and antioxidant activity of Ziziphyus spina-christi methanolic leaf extracts harvested from six Saudi Arabia provenances were evaluated and compared. In vitro allelopathic activities of aqueous extracts of the leaves were also tested on Trigonella foenum-graecum and Lens culinaris seeds.

Materials and Methods
Plant material Leaves of Z. spina-christi were sampled from At-taif, Riyadh, Jizan, Northern Borders, Mecca Road, Jeddah ( Figure 1). The plant species were collected (200-250 g per species) during the vegetative phase. The harvested provenances of Z. spina-christi were authenticated and named using existing literature (Cope, 1985;Chaudhary and Akram, 1987;Mighaid, 1996;Collenette, 1999;Chaudhary, 1999Chaudhary, 1999Chaudhary, , 2000Al-Hassan, 2006). The harvested plant samples were processed (powdered at around 100 mesh) then dried in the shade at room temperature for two weeks) and finally stored in in plastic bags in the dark until chemical analysis.

Preparation of the plant extracts
The aerial part of each provenance was finely powdered and used for the different biochemical assays. The solvent is used in order to obtain plant extracts solutions (1 g / 10 ml), which were macerated for 24h in shaking conditions (50 rpm) and used to assay the total content of polyphenols, the total content of flavonoids and the total antioxidant activity (DPPH test). Then extracts were pooled and concentrated under vacuum (Hammi et al., 2015). Total polyphenol content Total phenolics were determined with Folin-Ciocalteu assay as per the Singleton et al. (1999) method which was slightly modified by Deawanto et al. (2002). The results are obtained using a UV/Vis Jenway-6300 spectrophotometer (United Kingdom) under 760 nm. The total phenolics content was expressed as milligrams of Gallic acid equivalents per gram of dry matter (mg GAE/g DM) through the calibration curve of Gallic acid.
The sample was analysed in three replications (Rouz et al., 2015).

Total flavonoid contents
Total flavonoid contents were determined using the Aluminium trichloride method (Rice-Evans et al. 1996;Popova et al., 2004;). 1 ml of AlCl3 (2%) was added to 1 ml of plant extract. The volume was adjusted to 25 ml with methanol and thoroughly mixed. The absorption was measured after 40 min by a Shimadzu UV-160 (Tokyo, Japan) spectrophotometer at 420 nm. Total flavonoids were expressed in milligrams quercetin equivalents per gram of dry matter (mg QE/g DM) through the calibration curve of quercetin. All measurements were repeated three times for accuracy and reliability (Elaloui et al., 2016).

Condensed tannin contents
Condensed tannin levels were assayed following the Earp et al. (1981) method. 1 ml of vanillin (1%) mixed with 4 ml of HCl were added to 200 µl of leaf extracts and incubated 20 min in obscurity. Catechin was used as a standard (0-1250 µg/ml) and the results were expressed as microgram catechin equivalent per gram dry weight (µg CE/g DM). All measurements were performed in three replications. After agitation, the absorbance was read at 500 nm using a Jenway 6100 spectrophotometer.

Antioxidant activity
In test tubes 2.36 mg of DPPH, previously dissolved in 100 ml of ethanol, was mixed and incubated in obscurity. Different concentrations (0.75; 0.5; 0.25; 0.125 µg/ml) were prepared from 1 mg/ml of each leaf extracts. The control sample was done using ethanol and DPPH. The absorbance was measured at 490 nm after incubation for 30 min in dark. Measurements for each experiment were done in triplicate. Antioxidant activity expressed as inhibitory effect of the DPPH radical was calculated using this formula: The percentage of inhibition = [(A0 -Ac) / A0] × 100 Where A0 was the absorbance of the control and Ac was the absorbance of the plant extract/ standard. The IC50 value, the concentration (in μg/ml) of the compound required to scavenge DPPH radical by 50, were determined graphically by the linear regression (Basuny et al., 2013).
Allelopathic activity of Ziziphyus spina-christi leaf aqueous extracts Extracts were obtained by macerating from the Ziziphyus spina-christi provenances leaf extracts as various concentrations: 5 g, 20 g, 40 g, 60 g and 100 g powdered plant in 1 litre of distilled water for 24 h. The solutions were filtered through double layers of muslin cloth followed by filter paper. Trigonella foenumgraecum and Lens culinaris seeds were sterilized with 0.3% calcium hypochlorite, rinsed in distilled water, and dried on filter paper in the laboratory at room temperature for 7 days. For germination, two layers of filter papers were placed in 90-mm-diameter glass petri dishes. Twenty seeds were placed in each petri dish, followed by 02 mL of plant extract. The control groups were each given 2 ml of deionized water and leave at room temperature (25 °C). The Petri dishes were sealed with plastic wrap to prevent the loss of moisture and avoid contamination. Starting from the first day after the experiment began, germinated seeds were counted and removed daily. The experimental design was carried out as a randomized complete block (RCB) with 5 replications. The germination percentage (GP) was calculated. For growth bioassays, the seeds of Trigonella foenum-graecum and Lens culinaris were germinated on filter paper in the dark at room temperature (25 °C) and a photoperiod of 16 hours. Fifteen germinated seeds were transferred to petri dishes, which were filed with 25 g of sterilized quartz sand, and 02 mL of tested extract was added. In addition, control sample was added to the experiment without any treatment. Shoot (SL) and root lengths (RL) of seedlings were measured 15 days after treatment (DAT).

Statistical analysis
A descriptive analysis was performed to describe the entire results within each kind of test. Concerning the biochemical composition analysis and antioxidant activity a one-way analysis of variance (ANOVA oneway) followed by Duncan test was performed to test possible significant differences among mean values from different provenances. The level of significance was set at P<0.05 for all analyses. Statistical analyses were performed using PSS v.23 software.

Analysis of secondary metabolites and antioxidant properties
Total polyphenol, total flavonoid and tannins contents Total polyphenol levels varied from 23.65 mg GAE/g DM of the At-taif provenance to 62.29 mg GAE/g DM of the Mecca Road provenance (Table 1). The Jizan provenance has an important total polyphenol level (50.63 GAE/g DM). The relative values of total flavonoids (Table 1) oscillated between 6.35 (At-taif) and 15.45 mg QE/g DM (Jeddah). The Riyadh provenance has an important total polyphenol level (12.68 QE g/g DM). As we see in these results, the tree of Ziziphyus spina-christi in At-taif was the most stressed tree provenance. Leaf extracts of Jizan Z. spina-christi found to contain higher amounts of tannins (16.69 mg CE/g DM) as compared to provenances of At-taif (12.36 mg CE/g DM), Riyadh (9.25 mg CE/g DM) Northern Borders (11.26 mg CE/g DM) Mecca Road (7.16 mg CE/g DM) and Jeddah (14.39 mg CE/g DM).
Antioxidant activity The antioxidant activity ranged between 0.15 mg/mL and 0.06 mg/mL, respectively ( Table 2). The provenance of At-taif, Riyadh and Jeddah provenances have a lower value of IC50 compared with Jizan, Northern Borders and Mecca Road provenances.  Effects of aqueous Z. spina-christi leaf extracts on L. culinaris and T. foenum-graecum Effects on seed germination T. foenum-graecum seeds were more sensitive than those of L. culinaris seeds after treatment by aqueous leaf extracts with concentrations of 60 and 100 g/l (Tables 3 and 4). All extract of provenances of Ziziphyus have a negative effect on germination of T. foenum-graecum and L. culinaris seeds. The extract of Riyadh and Northern Borders provenance have a very remarkable influence on the germination of T. foenum-graecum (3 and 4% at 100 g/l respectively) and the germination of L. culinaris (9% and 8% respectively at 100 g/l).

Effects on root and shoot lengths
Root lengths are very sensitive to aqueous Z. spina-christi leaf extracts (Tables 3 and 4). Compared with other provenances, the two provenances which have a great effect on the root length of Trigonella foenumgraecum L. are those of Riyadh (10 and 16 mm at 20 and 100 g / l respectively) and Northern Borders (15 and 2 mm at 60 and 100 g / l respectively). These two provenances also have the greatest effect on the root length of Lens culinaris L.: 13 and 9 mm at 60 and 100 g / l respectively for Riyadh provenances and 14 and 8 mm at 60 and 100 g / l for Northern Borders provenances (Tables 3 and 4). Shoot lengths are very sensitive to aqueous Z. spina-christi leaf extracts (Tables 3 and 4). Riyadh Northern Borders provenance have a very negative effect on seedling shoots of Trigonella foenum-graecum L. compared with other provenances with 23 and 8 mm at provenance have a very negative effect on seedling shoots of Lens culinaris L. compared with other provenances with 15 and 8 mm at 60 and 100 g / l respectively and 24 and 13 mm at 60 and 100 g / l respectively (Tables 3  and 4).

Analysis of secondary metabolites and antioxidant properties
The total polyphenol content varies from one species to another. The leaves of the Ziziphyus of Mecca Road presented the highest total polyphenol (62.29 mg GAE/g DM) while Ziziphyus of At-Taif is the lowest one (23.65 mg GAE/g DM). The variations are probably due to the genetic characteristics of the species and by the environmental conditions in which the plants are found. These results corroborate with those obtained by Bettaieb et al. (2012), Hadacek (2002), Miliauskas et al. (2004), Ebrahimi et al. (2008), Andarwulan et al. (2010). Similar results were reported by Rouz et al. (2015). Our results were higher than those obtained for the Ziziphyus spina-christi Tunisian provenances (Elaloui et al., 2016a;2016b) where trees are from a young age than ours. This variability the total polyphenol levels could reflect the influence of the geographic conditions (humidity, temperature, altitude), the soil-growth conditions, and the origin and the period of leaves harvest (Brito et al., 2015). The methanol was found to be the efficient solvent to extract Ziziphyus leaves. This idea was also confirmed by Medini et al. (2014). Indeed, the increase in the biosynthesis and accumulation of phenolic compounds occurs frequently in plant tissue in response to biotic and abiotic stresses. These compounds are involved in the defence against reactive oxygen species (ROS), which are inevitably produced when the aerobic metabolism or photosynthetic is weakened by environmental stress. Genetic factors and growth conditions of the plant can also play an important role in the formation of secondary metabolites, including phenolic acids (Islam et al., 2003;Hashempour et al., 2010). Other factors especially the extraction method and the quantification method may also influence the estimate of the content of total phenols (Lee et al., 2003). The polyphenols played an important role in disease resistance by exerting free-radical scavenging, modulation of enzymatic activity and alteration of signal transduction pathways (Elaloui et al., 2016a). This study revealed a strong influence of the localities on the constituent of the leaf's extracts. This composition could also be influenced by the extraction time and the ratio of aqueous methanol (Elaloui et al., 2016c). As well, this variability could be explained by many factors including the origin, the period of harvest, the age and the stage of plant development. Other environmental factors (temperature, altitude, sunshine, animal aggression and diseases) could also influenced this variability (Elaloui et al., 2017). The amount of flavonoids of Z. spina-christi significant varied (P <0.01) between 6.35 (At-taif provenance) and 15.45 mg QE/g DM for Jeddah provenance. With the same method, Z. spina-christi leaves for our provenance had more important flavonoid levels than those obtained for Z. joazeiro (Elaloui et al., 2016a;2016b;Adzu and Haruna, 2007). Similar results were reported by Rouz et al. (2015). It has been proven that the contents of total phenols and flavonoids are high. The difference in the phenolic content including flavonoids described in the literature can be attributed to several factors such as the extraction method and the quantification method. Moreover, variables such as temperature, humidity and light intensity, added to the effects of the biota and the physiochemical structure of the soil can affect not only the production of secondary metabolites but also the chemical structure of substances (Reigosa et al., 2013). It has been proved that the levels of total phenols and flavonoids were high when the environment conditions of the plant were not adequate. In this case, the plant promoted the synthesis of secondary metabolites in order to adapt and survive Tim and Lamb (2005). A few papers reported the amount of phenolics in some of plants; recently, in a review about the biochemical composition of different parts of Z. lotus, Azize (2016) reported around 7 mg/g of phenolics to be present in the leaves, almost 5 times less than the amount measured in Tlili et al. (2019). Moreover, in the same review, the tannin content observed in the leaves was the same that Tlili et al. (2019) measured (around 3.0 mg/g). Conversely, the content of phenolics in the leaves of T. hirsuta and R. tripartitum, including flavonoids, and the DPPH values found by Akrout et al. (2011) andItidel et al. (2013) were in line with those measured by Tlili et al. (2019). Habib et al. (2014), studied the phenolic compounds in some types of honeys including Z. spina-christi L. Sidr honey which was found to contain the highest amount of total phenolics. Z. spina-christi L. samples were obtained from two different regions in Yemen. Ours results were in consistence with those obtained in Z. mauritiana (IC50 = 0.11 mg/mL) (Ashraf et al., 2015). Ours studies showed that the antioxidant activity augmented by the increase in total phenol levels. Adzu and Haruna (2007) also confirmed this idea. For Ziziphyus lotus (L.) Tlili et al. (2019) found the same results as we found in our study. When Alghazeer et al. (2012) studied the antioxidant activity of some plants growing in Libya, he found two times higher the amount of polyphenols in Hyoscyamus albus than we found in this study. The flavonoids in honey make it a good source of antioxidants (Bader et al., 2020).
Effects of aqueous Z. spina-christi leaf extracts on L. culinaris and T. foenum-graecum Effects on seed germination For both target species (L. culinaris and T. foenum-graecum), the highest germination was obtained for the control and inhibition of germination, which increases by elevating the concentration of aqueous extracts.
The concentration of 100 g/l gives the lowest germination for both species with a respective L. culinaris and T. foenum-graecum of 8 at 19% and 2 at 12%. Similar results were reported by Rouz et al. (2015). Inhibitory effect on germination and seedling development were obtained especially at higher concentrations (60 and 100 g/l).
Similar findings were also recorded by many researchers (Arora et al., 2015;Prasad et al., 2016;Turker et al., 2008). The degree of inhibition was largely dependent on the concentration of the aqueous extracts . These results confirm the herbicidal properties of this medicinal specie of Z. spina-christi containing natural molecules like juglone and artemisin that affect membrane permeability, water balance and osmotic regulation (Sanchez-Moreiras et al., 2008).

Effects on root and shoot lengths
Ours results showed that interaction between level of concentration of aqueous extracts and species decrease significantly the roots growth. Similar results were reported by Rouz et al. (2015). With the concentrations of 100 g/l the length of the roots of L. culinaris varied between 8.16 and 18.15 mm and the shoot varied between 8.15 and 21.15 mm. With same concentration the length of the roots of T. foenumgraecum varied between 4.36 and 16.84 mm and the shoot varied between 6.45 and 19.35 mm. The root lengths were more inhibited than shoot lengths. These results are in agreement with those of Patil and Kore (2016).
These results show that the aqueous extracts of the six provenances of Ziziphyus studied have allelopathic potential and significantly inhibit the germination and growth of T. foenum-graecum and L. culinaris. These excerpts are provided with a potent cytotoxic activity. Root growth is more sensitive to different concentrations of aqueous extracts of six provenances of this medicinal specie than germination.  concluded that the aqueous extracts of allelopathic plants generally act on root growth rather than growth of the hypocotyl. This was explained by the fall, which made the roots in contact with the first allelochemicals inhibit cell division in meristematic tissues (Ashrafi et al., 2008). Mitosis is the most important event in the development of the plant and many enzymes and regulatory factors of these phenomena are affected by allelochemicals via a chromosome aberration (Turker et al., 2008). Thus, the aqueous extract can affect the absorption of water by the seed and delay the mobilization of reserves (Kato-Noguchi and Macias, 2006). Even if the seed happens to germinate, we recorded a blocking root growth and / or the aerial part of plants. Tucker et al. (2008) reports that the growth phenomenon is more sensitive to the phytotoxic allelochemicals than germination. So, the exact identity of the compounds responsible for this apparent phytotoxic activity, and quantified with certainty needs to be known. Overall, the observed results could form the basis for further investigations of the biological properties of aqueous extracts of six provenances of this medicinal specie. In addition, the use of these aqueous extracts as a biopesticide is a promising path towards recovery of this fraction.

Conclusions
This study demonstrated that allelopathic potential of aqueous extracts of six provenances of medicinal specie (Ziziphyus) and invasive grass by influencing either the germination or growth are the two phenomena that target both species. This indicates that these extracts are rich in natural bioactive substances, suggesting that their importance in the development of natural bioherbicides as an alternative to minimize the release of synthetic non-degradable molecules in crop production. Further studies are needed to understand the mode of action of these allelochemicals. Also, a separation, purification and identification of bioactive molecules that could potentially be used as herbicides or as plant growth regulators would be need to be recorded for further study. Allelopathy, used as herbicides, had an economic benefit to farmers and also reduced negative impacts on the environment and on the health of the human being. In conclusion, all the data confirm the importance of the Saudi Arabia local vegetation as a potential source of various bioactive phytochemical compounds; the investigation is based on the need for different biological agents from natural sources with potent activity and lesser side effects as substitutes for chemical therapeutics.

Authors' Contributions
Both authors read and approved the final manuscript.


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Increase in meat productivity of young cattle and horses when using environmentally friendly feed additives

The article presents the outcomes of studies confirming the feasibility of using zeolitecontaining additives with the objective to optimize the diet of young cattle and horses by the content of minerals in it in order to increase their meat productivity. The research has been conducted in the Republic of Tatarstan. Laboratory studies have confirmed that in terms of hazard the zeolite-containing feed additive belongs to the fourth class of chemicals, specifically, low-toxic compounds in accordance with the requirements of State Standard 12.1.007.76. Scientific and economic experiments have established that the use of a zeolite-containing additive in the diets of young cattle and horses during a store period contributed to an increase in their average daily growth by 10.8 and 12.0 % and slaughter weight by 7.4 and 6.3 % (p<0.05). The slaughter yield in animals of the experimental groups was 54.0 and 58.9 %. The profitability of beef and horse meat production was 17.4 and 19.3 % respectively.

Introduction
One of the most significant issue in present-day conditions is to provide the population with domestic quality livestock products. Thus, the main objective of animal agriculture is to eliminate food shortages through the development and intensification of animal agriculture. It is stipulated by the fact that the consumption of livestock products is one of the most important indicators of people's nutrition quality [1,2].
Cattle meat is the most popular type of meat in Russia. Traditionally high nutritional value, universal consumer qualities and availability of production make beef a very significant component of nutrition in Russia. Compared to meat from animals of other species, beef is characterized by a more favorable ratio of protein and fat. Additionally, it has less cholesterol than lamb and pork. However, its major advantage is that cattle are able to use rough and succulent feed with significantly lower consumption of expensive concentrated feed (30-35 % in the diet) [3,4].
The development of horse breeding for meat production in solving the problem of manufacturing environmentally friendly products including the ones for children and dietetic nutrition is of current importance. Unlike the meat of other animals horse meat contains low cholesterol, which is one of the factors determining its dietary value. This fact is explained by the increase in demand for unique horse breeding products observed in recent years [5,6].
Animals' feeding has a great influence on the meat productivity. Defective feeding is the main reason for the decrease in productivity and efficiency of animal agriculture [2]. Therefore, the use of high-quality feeds and environmentally friendly feed additives is of great importance for the further increase in manufacturing environmentally friendly livestock products.
It is impossible to solve the problem of balanced animal feeding without taking into account the zonal biogeochemical and climatic features of the region while the mineral composition of the feed is subject to significant fluctuations and depends on the type of soil, weather conditions, plant species, vegetation phase, agrochemical measures, harvesting technology, storage and preparation of stuff for feeding [7,8].
The methods aimed to improve feeding systems by means of various feed additives being metabolic regulators that increase feed efficiency are widely used against the background of a decrease in the feed rations' usefulness caused by economic and environmental reasons under the conditions of increased technogenic intoxication and intensive industrial technology [9][10][11][12].
Moreover, feed additives enable to get an additional gain of live weight and reduce animals' mortality without using expensive and time-consuming technologies, thus increasing the profitability of livestock production [13].
The Government of the Russian Federation provides domestic producers with state support with regards to new generation feed additives for farm animals in the context of import substitution. Great attention is paid to environmentally friendly additives based on natural minerals. They contribute to the improvement of animals' digestion and assimilation of nutrients, which provides increased resistance and productivity of animals [14][15][16][17][18].
Currently, organic agricultural products manufactured in certain areas of agricultural industry from raw materials of plant and animal origin, which are grown, produced, processed, certified, labeled, stored and marketed according to the rules of organic production, are of particular demand, have biologically valuable qualities and health-improving properties, and are intended for being consumed by the population in a processed and non-processed form. However, not all Russian citizens can afford eco-products. According to the National Organic Union, only 2 % of Russia's population can currently purchase food under the brands of organic product and biobased product [19].
In accordance with the abovementioned, the development and implementation of effective methods for the production of organic products is of great scientific and practical interest due to the fact that they will expand the market for environmentally friendly products and make it more accessible to consumers.

Materials and methods
Mineral zeolite-containing feed additive is made on the basis of natural zeolite of the Tatar A toxicological assessment of zeolite-containing feed additive was carried out at the Federal Center for the Toxicological and Radiation Safety of Animals (Kazan) as part of a joint collaboration with the head of the Department of Toxicology, Doctor of Biological Sciences, Professor M.Ya. Tremasov.
Scientific and economic experiments were carried out on the basis of Holding Company "Ak Bars" of the Republic of Tatarstan on black-and-white bulls during the period from 12 to 16 months and foals of the Russian heavy draft from 12 to 18 months. Guided by the principle of analogues, they formed two groups of clinically healthy calf bullы and foals [20]. The diets were based on detailed feeding norms [21]. The conditions of keeping and feeding foals during the test period corresponded to the requirements of State Standard R 56508-2015. Farm-produced feed accounted for more than 50 % of the diet. Rough feed accounted for at least 60 % of the daily diet of foals.
Animals of the control group received the basic diet adopted on the farm. Animals of the experimental group received mineral zeolite-containing feed additive in a dose of 3 % of the dry matter of the diet in addition to the basic diet. During the period of scientific and economic experiments, animals were kept under identical conditions in open feedlots.
The animals' growth was controlled by monthly individual weighing before their morning feeding. Thus, it was noted that the average daily and absolute gain of live weight and relative growth rate were determined. The relative growth of animals for the period of the experiment was calculated by the method of S. Brody.
A control slaughter of animals aged 16 and 18 months was carried out with the objective to study the feed additives impact on meat productivity formation.
Veterinary-sanitary inspection of carcasses was carried out in accordance with the "Rules of veterinary inspection of slaughtered animals and veterinary-sanitary examination of meat and meat products." The meat obtained from young cattle and horses was evaluated in accordance with the requirements of State Standard 7269-2015 "Meat. Specimen selection methods and organoleptic methods for determining freshness." Evaluation of economic indicators of animal feeding was carried out by calculating the cost of live weight growth as well as the revenue from sales and profitability of production.
The obtained digital data were processed by the method of variation statistics for the reliability of the difference between the compared indicators with the application of the Student criterion using the Microsoft Excel software package.

Results
Laboratory studies have confirmed that in terms of hazard the mineral zeolite-containing feed additive belongs to the fourth class of chemicals, specifically, to low-toxic compounds, in accordance with the requirements of State Standard 12.1.007.76.
Acute oral toxicity, irritating effects on the skin and conjunctiva, cumulative properties of the drug, violations of the clinical status and internal organs pathologies were not noted while metabolism activation was noted during toxicological evaluation of mineral zeolitecontaining feed additives, biological testing as well as structural and functional studies in white mice and rabbits.
The main criterion for the growth and development of animals characterizing their intravital meat productivity is live weight. It was found in the course of scientific and economic experiments that the use of mineral zeolite-containing feed additives in the diet contributed to an increase in young cattle and horses' growth.
The first scientific and economic experience showed that feeding with a mineral supplement in the diet contributed to an increase in young cattle growth (Table 1).
Calf bulls of the experimental group gained the largest live weight during the feeding period. Specifically, at the age of 16 months, the bulls of the experimental group put on 19.6 kg or 4.7 % (p <0.01), which significantly exceeded the live weight of the bulls in the control group. The average daily increase in bulls during the feeding period in the experimental group was 101.7 g or 10.8 % more (p <0.05) than the bulls in the control group. The change in the average daily gain of the calves during the feeding period is shown in Fig. 1. The indicator of the absolute increase in live weight in the experimental group was 13.4 kg more (p<0.05), while the relative growth rate increased by 7.9 %.
Post-slaughter studies and veterinary-sanitary examination of carcasses and internal organs of calf bulls in the control and experimental groups were carried out, visual pathological changes were not detected, and their satisfactory bleeding was noted. The carcasses were similar in appearance and degree of bleeding. No visible differences between the groups were observed. Assessment of the internal organs condition was carried out by appearance, surface integrity and color. On examination, it was found that the internal organs were without damage, hemorrhage and neoplasms, proportional in size and had a color characteristic of each organ.  According to the organoleptic characteristics, the carcasses of calf bulls in the control and experimental groups did not have visual differences. The crust of drying was pale red, meat was dense and elastic, color and smell were inherent in fresh beef. When assessing the state of fat, it was noted that it had no extraneous odors, was white, had a dense consistency, and crumbled when crushed. The surface of the joints was smooth, shiny, tendons were elastic and dense.
The results of the control slaughter showed that the heavier carcasses were obtained from the bulls of the experimental group, their slaughter mass significantly exceeded the control by 7.4 % (p <0.05) ( Table 2). At the same time, the slaughter yield in the bulls of the experimental group was 54.0 %, while this indicator was equal to 52.9 % in the control group.
Beef production was economically viable in the conditions of scientific and economic experience. Thus, the profitability in the control group was 12.7 % and in the experimental group it was 17.4 %.
According to the results of the second scientific and economic experience, the foals of the experimental group were superior in live weight to their peers of the control group (Table 3). 12.0 % (p<0.05). The relative increase in live weight of foals in the experimental group was 8.8 % more. The dynamics of the average daily growth of foals is shown in Figure 2.

Fig. 2. Dynamics of the average daily gain of foals during the feeding period
Visual pathological changes in the carcasses and internal organs of foals in the control and experimental groups were not detected during the veterinary and sanitary examination. It was established that the internal organs were without damage, hemorrhage and neoplasms, were proportional in size and had a specific color for each organ. Visually, the carcasses of the animals in the experimental group did not differ from the control ones; they had a dark red crust of drying, the muscles on a cut were slightly moist and did not leave a wet spot on the filter paper, the meat consistency was dense, elastic, the color and smell of meat were specific to fresh horse meat. The fat was yellowish in color, had no odors and a dense consistency. The tendons were elastic and dense; the surface of the joints was smooth and shiny.
On the whole, horses are not inferior to meat breeds of cattle in terms of meat productivity. According to the results of the control slaughter, it was found that the use of mineral zeolite-containing feed additives in the diets of young horses had a positive effect on their meat productivity (Table 4). It was found that the carcasses mass was 18.5 kg or 6.3 % more in the experimental group (p <0.05). At the same time, the slaughter yield increased by 2.3 % and amounted to 58.9 %.
Foals' store feeding was economically justified in the conditions of scientific and economic experience. Thus, the profitability of horse meat production in the control group was 13.5 %, and in the experimental group it was equal to 19.3 %. The 5.8 % increase in profitability in the experimental group was due to the large absolute increase in the foals and the additional profit was received when selling on a per head basis.

Conclusion
The research has shown that the use of mineral zeolitecontaining feed additives in the diet enabled to increase: • average daily live weight gain of young cattle and horses by 10.8 and 12.0 %; • slaughter mass of calf bulls and horse foals by 7.4 and 6.3 %, with a slaughter yield of 54.0 and 58.9 %, respectively; • profitability of beef and horse meat production by 4.7 and 5.8 % respectively.
The use of mineral zeolite-containing additives in feeding bulls and foals pose no negative affect on the veterinary and sanitary indicators of beef and horse meat. Organoleptic indicators met the requirements of State Standard 7269-2015 for fresh meat.
The results obtained enable to assess the prospect of using mineral zeolite-containing feed additives in the feeding of young cattle and horses in order to increase meat productivity and profitability of meat production.