Alfalfa Crop Research Articles

Effect of biopesticides on the spotted alfalfa aphid, Therioaphis trifolii Monell, and its predator, Coccinella septempunctata L.

The spotted alfalfa aphid Therioaphis trifolii Monell (Hemiptera: Aphididae) is one of the most commonly found insect pests, affecting alfalfa crops and causing severe damage in Bulgaria. Natural products, such as botanical insecticides, serve as an excellent alternative to synthetic counterparts for pest management. The combined application of the biological insecticide pyrethrins (40 g L−1) and organic fertilizer phosphorus pentoxide + potassium oxide (30 and 20%, cumulative insect days of T. trifolii and an overall efficacy of 68.3%. The toxic effect was close to that of the synthetic insecticide thiacloprid (240 g L−1), although there was a significant difference. Plants treated with pyrethrins and organic fertilizer, followed by biofertilizer alone, exhibited the best physiological condition and a high content of plastid pigments, as the interaction between these two products was additive. The use of botanical products had a positive impact on the plant’s vegetative development. Among the bioproducts, the combined application of organic fertilizer and pyrethrins resulted in the highest productivity, with a 22.6% increase. Botanical products were harmless by toxicity not exceeding 25% against Coccinella septempunctata larvae. Their essential role is highlighted due to the numerous benefits. The combined use of pyrethrins and organic fertilizer is an approach to organic farming crucial for sustainable and environmentally friendly agricultural development. Botanical products are considered safe, eco-friendly alternatives that contribute to insect pest control and promote increased agricultural production.

Onfield estimation of quality parameters in alfalfa through hyperspectral spectrometer data

Alfalfa is a forage of vast importance around the world. In the past, near-infrared spectroscopy (NIRS) technique have been explored in the lab to determine quality traits such as fibre content in dried and ground material. During the last decade, portable hyperspectral devices have emerged as a tools for in-field prediction, of not only crop yield but also a large range of quality and physiological markers. The objective of this study was to estimate quality parameters in an alfalfa crop using hyperspectral data acquired from a full-range (350–2500 nm) spectrometer under field conditions. Reflected spectra were measured in single leaves as well as at the canopy level, then reflectance was related to target parameters such as biomass, leaf pigments, sugars, protein, and mineral contents. Due to their large effect on crop quality parameters, meteorological conditions and phenological stages were included as predictors in the models. We found that meteorological and phenological variables improved the accuracies and percentage of variance explained (R2) for most of the parameters evaluated. Based on R2 values, the best prediction models were obtained for biomass (0.71), sucrose (0.65), flavonoids (Flav) (0.56) and nitrogen (0.70) with normalized root mean squared errors of 0.196, 0.32, 0.087 and 0.08, respectively. These parameters were associated mainly with visible (VIS) (approx. 350–700 nm) and near infrared (NIR) (700–1250 nm) regions of the spectrum. Regarding mineral composition, the best prediction models were developed for P (0.51), B (0.50) and Zn (0.44), associated with the short-wave infra-red (SWIR) region (1250–2500 nm). The results of this study demonstrated the potential of hyperspectral techniques to be used as a base for performing initial evaluations in the field of quality traits in alfalfa crops.

مقارنة الكفاءة الاقتصادية لنظم الري التقليدي والحديث لإنتاج علف البرسيم

مقارنة الكفاءة الاقتصادية لنظم الري التقليدي والحديث لإنتاج علف البرسيم

Utilization of treated municipal effluent for irrigating agricultural land in Palestine: The driving factors and existing practices

This article investigates the motivations and practices of using treated wastewater (TWW) to irrigate crop fields in Jenin, Palestine. Around 40 farmers were surveyed for data collection. The results showed that 66% of the farmers grew alfalfa crops while 30% grew fruit trees. The main obstacles the farmers faced before starting to use TWW were disgust (68.2%), worries about the quality of TWW (68.2%), health concerns (63.6%), and concerns about adverse effects on the soil (63.6%). All interviewed farmers considered the establishing and funding of an irrigation project to be the cornerstone for any reuse project. The second most important driving factor was the price of TWW that is 10–25% of the fresh water prices. After reusing TWW for irrigation, 59% of the farmers did not use any fertilizer, but they were not sufficiently aware of the crops’ water needs, nor the nutrients in the TWW. All the fodder-growing farmers abstained from selling their crops before drying. The farmers used the TWW for five to nine months annually. After the TWW was reused, the main positive impacts of the TWW reuse were increased crop yields (77.3%), crops quality (50.0%), and crops marketing (47.7%). On the other hand, the main negative impacts were blocking of the irrigation systems (77.3%) and release of odors (54.5%). After practicing TWW use in crops irrigation, the key factors contributed to the “no difference” index were the effects on human health (100%), soil quality (56.8%), and insects spread (54.5%). Therefore, the results of the study support the decision makers to implement TWW reuse policies for crop irrigation in arid regions with scarce water resources. Monitoring TWW reuse and training farmers and helping them overcome obstacles is essential.

A Machine Learning Approach for the Estimation of Alfalfa Hay Crop Yield in Northern Nevada

Increasing pressure over water resources in the western U.S. is currently forcing alfalfa (Medicago sativa L.) producers to adopt water-saving irrigation techniques. Crop yield forecasting tools can be used to develop smart irrigation scheduling methods that can be used to estimate the future effects of a given irrigation amount applied during a current irrigation event on yield. In this work, a linear model and a random forest model were used to estimate the yield of irrigated alfalfa crops in northern Nevada. It was found that water (rain + irrigation), the occurrence of extreme temperatures, and wind have a greater effect on crop yield. Other variables that accounted for the photoperiod and the dormant period were also included in the model and are also important. The linear model had the best performance with an R2 of 0.854. On the other hand, the R2 value for the random forest was 0.793. The linear model showed a good response to water variability; therefore, it is a good model to consider for use as an irrigation decision support system. However, unlike the linear model, the random forest model can capture non-linear relationships occurring between the crop, water, and the atmosphere, and its results may be enhanced by including more data for its training.

Effects of Alfalfa Crop Rotation on Soil Nutrients and Loss of Soil and Nutrients in Semi-Arid Regions

Soil desertification is an important factor leading to soil degradation and environmental problems such as atmospheric or water pollution. Conservation agriculture, such as crop rotation and conservation tillage, can reduce soil erosion and nutrient loss caused by wind in semi-arid regions. However, the relationships between the loss of soil and nutrients and surface vegetation characteristics are frequently obtained according to a short-term simulation experiment, which makes the application of the conclusions limited. In this study, we conducted a 4-year field experiment continuously with three crop rotations, i.e., spring wheat (Triticum aestivum L.) cropping, alfalfa (Medicago sativa L.) cropping, and fallow when previous rapeseed crops (Brassica napus L.) were being harvested; measured the surface vegetation characteristics, soil nutrients, and loss of soil and nutrients caused by wind; and analyzed their variations and quantitative relations. The findings of this study indicated that the coverage, height, and biomass of the aboveground vegetation in three rotations in the spring and autumn had significant differences, and the rank order was fallow field < wheat field < alfalfa field. With the extension of growing years, the soil organic carbon (SOC) and total nitrogen (TN) of a 0–5 cm soil layer all increased to varying degrees and had significant differences among the rotations during the late stages of the experiment (p < 0.05), while the changes in the total phosphorus (TP) and total potassium (TK) were small, and their values had decreasing trends. The available nitrogen (AN) and available phosphorus (AP) decreased first and then increased during the experimental period, while the available potassium (AK) had an increasing tendency. The increase in soil nutrients in the alfalfa field was the highest during the whole experiment period, while the loss of soil and nutrients (SOC, TN, TP, and TK) was the lowest, followed by the wheat and fallow fields. There were significant negative correlations between the surface vegetation characteristics and the loss of soil and nutrients (p < 0.01), while the correlations between soil loss and the loss of soil nutrients were significantly positive. In summary, alfalfa crop rotation can obviously reduce the loss of soil and nutrients in semi-arid areas, which is conducive to the sustainability of agroecosystems.

Effects of harvest period and mixed ratio on the characteristic and quality of mixed silage of alfalfa and maize

In order to improve the silage quality and rationally develop and utilize feed resources, the experiment will explore the effects of harvest periods and the ratios on silage characteristics and quality of silage maize (Zea mays L.) and alfalfa (Medicago sativa L.). Results showed that dry matter (DM) content, neutral detergent fiber (NDF), acid detergent fiber (ADF) of whole silage maize increased significantly (P < 0.05), water soluble carbohydrate (WSC) content of in 3/4 milk line stage was significantly lower than that in other harvesting stages (P < 0.05), and the CP content of 1/4 milk line stage and relative feed value (RFV) of late milk stage were the maximum, respectively; With the delay of the mowing period, the content of DM, NDF and ADF in the third crop of alfalfa increased significantly (P < 0.05), while the CP content decreased significantly (P < 0.05), the harvest period with the highest RFV was at the early flowering period. To sum up, silage corn can be harvested at the end of milk maturity to early wax maturity, and the third crop of alfalfa can be harvested at the early flowering stage, so that silage materials with high nutritional value can be obtained. The corn silage harvested in late september the best harvest period was mixed with alfalfa at the ratio of 10:0, 8:2, 6:4, 5:5, 4:6, 2:8, 0:10, and the mixed silage was fermented for 60 days, then proceeded determination of silage quality, and the principal component analysis (PCA) was used to analyze 10 nutritional quality indicators of 7 different mixed ratios. The results showed that compared with alfalfa silage alone, in the mixed silage of alfalfa and corn silage, with the increase of the proportion of corn silage, the fermentation quality of silage was gradually improved. Sensory evaluation scores and RFV values were higher, WSC and lactic acid (LA) contents were significantly increased (P < 0.05), and pH and ammonia nitrogen (AN) content were significantly decreased (P < 0.05). The in vitro gas productions ( IVGP, at 0, 2, 4, 6, 8, 12, 24, 36, 48 and 72 h) were measured, the results showed that IVGP increased with the increase of silage corn mixed ratio. In summary, the effects of the harvest period of silage corn and alfalfa and different mixing ratios of silage on the quality of silage provide a theoretical basis for improving the quality of silage and rationally developing and utilizing feed resources, so as to be better applied to actual production.

Assessment of Crop-Water Requirement of Alfalfa Using FAO-CROPWAT Model-8.0

The current study was conducted at the Farming System Research Station, situated within the Department of Agronomy at the College of Agriculture, Junagadh Agricultural University in Junagadh, Gujarat, India. This research took place during the winter cycle (Rabi season) 2021 to 2022 and 2022 to 2023. In this study, the CROPWAT crop irrigation schedule provides an overall Evapotranspiration (ETc) value of 549.6 millimeters as the optimal water requirement for achieving maximum crop production with sufficient water supply. The actual water use by the crop during its growth period amounted to 544.2 millimeters and total net irrigation applied was 507.9 millimeters, while the gross irrigation amounted to 725.6 millimeters. The irrigation efficiency was 100%. Comparing this approach to irrigation scheduling based on the Irrigation Water to Crop Potential Evapotranspiration (IW/CPE) ratio, using CROPWAT enabled the precise management of irrigation water. It ensured that the alfalfa crop received the appropriate amount of water according to its specific growth stage requirements. The CROPWAT model data indicates that there was no yield reduction, even with a 100% critical depletion of available soil moisture. Additionally, the seasonal yield response factor was calculated to be 0.80%. These findings emphasize the effectiveness of the irrigation strategy employed, resulting in optimal crop yields without yield losses due to critical soil moisture depletion.

Relationships of the gall midge, Asphondylia miki Wachtl (Diptera, Cecidomyiidae), with the host plant, alfalfa (Medicago sativa) and ectoparasites of its larvae and pupae (Hymenoptera, Eulophidae) in the forest-steppe of the middle volga region

The studies were carried out in crops of alfalfa ( Medicago sativa ssp. × varia ) in 2018-2022 in the forest-steppe of Samara Province. Asphondylia miki galls were taken into account in alfalfa crops from the beginning of their formation to the end of the growing season on sites from 0.1 to 1 m2 in 10-fold repetition. Statistical processing of the obtained data was carried out by methods of variance analysis. At spring sowing of alfalfa, as well as in its perennial crops, gall midge A. miki develops in two, and during summer sowing in the rst year of the culture’s life in one generation per year, pupae overwinter in galls, the imago of the wintering generation occurs in April. The greatest damage to alfalfa by the larvae of A. miki (40-68% of generative shoots) and the number of its galls (500-830 copies/m2) were observed in the rst year of the culture’s life when it was sown in summer, with the coincidence of the greatest ight of imago with the budding of the culture, which led to signi cant losses in the yield of alfalfa seeds (13-81%). In summer alfalfa crops of the rst year of development without the use of chemical plant protection agents, parasitic hymenopterans contribute to the death of larvae and pupae of A. miki in on average 60% of its galls. Among them, a gregarious ectoparasite Sigmophora brevicornis (Eulophidae) mainly preying on A. miki larvae accounted for about 77% of the individuals of the identi ed parasites. In the S. brevicornis population, males and females had similar body coloration and belonged to three phenotypes: the lightest brownish yellow, yellowish brown, and dark coloration, which accounted for 53, 28 and 19% of parasite individuals, respectively.

Use of a combination of two clustering and tree algorithms for investigating and predicting alfalfa yield under different conditions of deficit irrigation

The largest amount of water consumption in Iran is related to agriculture. Considering that Iran has suffered a drought in recent years, the optimal use of water is necessary, especially in the agricultural sector. For this reason, in this research, the deficit irrigation regarding alfalfa crop was investigated. Alfalfa was cultivated in three years with four replications. Deficit irrigation methods including 40 %, 70 % and 100 % full irrigation (FI) were employed at different stages of alfalfa growth. First, crop per drop (CPD), benefit per drop (BPD) and net benefit per drop (NBPD) values related to alfalfa were clustered. The results of clustering were introduced to the tree algorithm as target data. The tree algorithm predicted the target data according to the factors of 1) the type of cropping year, 2) the time of harvest and 3) the level of deficit irrigation at different stages of alfalfa growth. According to the results of the combination of two algorithms, it was found that The lowest values of CPD, BPD and NBPD are equal to 1.2 (kg/m3), 125 (1000 Rial/m3) and 115 (1000 Rial/m3) respectively in the second harvest and deficit irrigation which was predicted in the two regrowth (RG) and budding (BU) stages. The highest values of CPD, BPD and NBPD are equal to 1.8 (kg/m3), 185 (1000 Rial/m3) and 175 (1000 Rial/m3) respectively in the third harvest and deficit irrigation which was predicted in the branching stage (BR). Thus, to increase the yield, it is better not to perform severe deficit irrigation at RG and BU stages. Also, according to the predictor importance of the software, it was found that the three factors of harvest time, BU and the type of cropping year had the greatest effect on the prediction, respectively.

Assessing perennial alfalfa yield by incorporating physiologically-lucid function into DeNitrification-DeComposition model

Reliable, rapid and timely assessments of forage crop biomass are crucial for managing feed supply and animal husbandry. While process-based models are regularly promulgated in modeling crop and pasture growth and development, the reliability and functionality of such models in simulating alfalfa (Medicago sativa L.) growth remains limited. The purpose of this study was to address deficits associated with simulation of long-term growth dynamics in perennial alfalfa; to assess potential alfalfa yield across the Loess Plateau and dissect key abiotic factors constraining alfalfa yields. We undertook an extensive review of the literature to collate and analyze existing alfalfa biomass data across the entire Loess Plateau in China. We then developed an alfalfa multi-year growth curve using a Gauss-amplitude function; when enacted this algorithm reliably reproduced the rise, peaks and declines in biomass with crop development. To assess the performance of our new function as part of an integrated system, we incorporated a multi-year growth curve into the DeNitrification-DeComposition (DNDC) model to assess longitudinal yields under rain-fed and irrigation conditions. Our adapted model reproduced aboveground trends in biomass more accurately than the original model. The regional simulation results show that alfalfa yield was less than 8000 kg ha–1 in most areas with an annual precipitation lower than 500 mm under rain-fed condition, while the alfalfa yield in most areas was above 8000 kg ha–1 under irrigation condition. Compared with rain-fed alfalfa, there is an increased 69% of yield after irrigation in irrigated areas of the Loess Plateau. The rain-fed alfalfa yield was severely constrained by drought when the aridity index fell below 0.31. Our new model development paves the way for additional refinement of alfalfa crops in process-based models, and provides opportunities for adoption of alfalfa crops in new regions by adjusting the parameters in the Gauss-amplitude function.

Biological features and distribution of nectarophage &lt;i&gt;Timia (Empyelocera) abstersa&lt;/i&gt; Loew (Diptera, Ulidiidae)

The distribution and spatial structure of the range of Timia abstersa (Ulidiidae) were analyzed for the first time. The map of this species distribution is based on the materials of the collection of the Zoological Institute of the Russian Academy of Sciences. It served as the basis for the analysis of the zonal landscape conditions of the distribution of the adult flies of T. abstersa and the cultivation of alfalfa its main fodder plant. The nectarophagy of T. abstersa flies on alfalfa was first established on the basis of our laboratory and field studies in alfalfa crops in the forest-steppe of the Samara Region and according to literary data on the fodder nutrition of adult flies of this species in the southwestern part of Iran. The distribution of T. abstersa in forest-steppes, typical and dry steppes in lowland, foothill and on mountain plateaus from 28 to 92 east longitude and from 29 to 53 north latitude in the temperate and subtropical zones of Eurasia was noted. Two mountain centers of its formation have been identified in the area of T. abstersa: Transcaucasian-North Iranian and Central Asian. From the Transcaucasian-North Iranian mountain center, this species spread to flat landscapes in the north and northeast direction to Europe, western and northern Kazakhstan, Western Siberia, and from the Central Asian mountain center in the east: along the foothills and mountains of southern Kazakhstan, northern China to Western Mongolia. The formation of T. abstersa centers is due to the greatest diversity of perennial wild alfalfa species in them, and the expansion of the range of T. abstersa is due to the increase in the territories of widespread cultivation of this crop.

Nesting Traps to Collect Solitary Cavity-Nesting Hymenoptera

The aim of this study to survey the bees species using nesting traps, determine the diameter and material of which the nests were made. This study was conducted at the Researches and experiments Station of the Faculty of Agriculture, University of Tripoli, using nesting traps. Traps were designed with diameters of 5,8,10 mm paper and 5 mm plastic drinking straws(tubes) with 20 cm long), the traps were mounted on trees that surrounding alfalfa field. The results showed that the percentage of occupied nests, were as follows: The paper nests strews 60% of 5 mm, 5% of 8 mm, (zero) of 10 mm, and only 5% of 5 mm plastic strews. Bees identification reveled one species as alfalfa leaf-cutter bee (Megachile rotundata, F: Megachilidae - Hymenoptera).The diameter of the straw was crucial in determining the sexual ratio, straws with 5 mm of diameter as the ratio of males to females was 1♀:1♂, whether paper or plastic strews, while 8 mm was 2♀:1♂.The research recommend reusing the nests made of paper tubes with 5 mm of diameter to collect the largest number of alfalfa leaf-cutter bees to get their benefits in pollinating the alfalfa crop.

Glyphosate‐resistant alfalfa can exhibit injury after glyphosate application in the Intermountain West

AbstractGlyphosate‐resistant (GR) alfalfa (Medicago sativa L.) has been widely adopted in the United States. Exceptional tolerance of GR alfalfa to glyphosate application has been reported as a strength of this technology; however, growers have recently reported potential crop injury under specific environmental conditions. The purpose of this study was to document and characterize the injury and determine best management practices for avoiding injury to GR alfalfa in the Intermountain West. The effects of glyphosate rate and application timing during various seasons were investigated at 24 sites over 5 years, measuring the impact on alfalfa crop height and biomass yield. Summer glyphosate applications did not injure alfalfa. However, spring applications reduced crop height at 76% of sites and biomass yield at 62% of sites. At responsive sites, low (869 g ae ha−1) and high (1739 g ae ha−1) glyphosate rates reduced yield by 0.53 and 1.06 Mg ha−1, respectively. Alfalfa treated with high rates in the late spring, when 15–20 cm tall, had mean yield reductions of 16%–17% compared with untreated alfalfa. These results suggest that glyphosate applications made at tall crop heights or high rates on GR alfalfa are more likely to reduce crop height and yield in the Intermountain West compared with earlier applications at lower rates. We recommend that spring applications using low glyphosate rates occur before alfalfa is 10 cm tall to mitigate the risk of injury. If a high glyphosate rate is necessary, then an application should be made before alfalfa is greater than 5 cm tall.

Cultivation of festulolium mixed with alfalfa foraging purposes in the forest-steppe of Western Siberia

Festulolium is a promising but little-studied fodder crop. The authors found that in the year of laying the herbage of Festulolium in mixtures, the height of plants increased by 6–11% compared with singlespecies sowing. However, the number of shoots per plant decreased from 3 to 2, and the root length decreased by 20%. The survival rate of plants was 84.9–97.4% after winter, depending on the year of sowing. Survival decreased to 46–92% for alfalfa in mixtures, and it was as low as 46–84% when sown with mixture seeds. This was affected by a decrease in reserve nutrients - sugars in the roots of plants. The sugar content decreased by 26%, from 5.14% to 3.77%. No positive effect was observed when sowing with alternating 1–3 rows of festulolium and 1 row of alfalfa. The introduction of nitrogen at a dose of 30 kg a.i. (active ingredient)/ha increased the efficiency of skip-row planting and sowing with a mixture of seeds by 21% due to the positive responsiveness of the components to fertiliser. An increase in the nitrogen dose to 60 kg/ha harmed alfalfa, reducing its share in the herbage to 7% by the third year of use. This decrease was due to the displacement of the more nitrogen-responsive festulolium. The efficiency of crops increases with a reduction in the share of the cereal component and an increase in the percentage of legumes with an alternation of rows of 1:3. The yield was 35.7–42.7 t/ha of green mass, which is higher than that of the single-species sowing of festulolium by 19–53%. The increase is due to an increase in the leaf coverage of alfalfa plants up to 46–49% (against 44% in control) due to the optimisation of layering in the herbage. The introduction of nitrogen at a dose of 30 kg/ha contributes to an increase in yield by 14% (0.43–5.0 t/ ha) due to the increased share of the cereal component in the mixture, an increase in the number of shoots on the plant by 11.1% and their mass by 12.5–17.8%. The introduction of N60 in the joint crops of festulolium and alfalfa is not advisable since it does not give a significant increase in yield and does not pay off the costs incurred.

Developing a Crop Water Production Function for Alfalfa under Deficit Irrigation: A Case Study in Eastern Colorado

Recent Colorado, USA water law provisions allow a portion of irrigation water to be leased between agricultural and other users. Reducing consumptive use (CU) through deficit irrigation while maintaining some crop production could allow farmers to earn revenue from leasing water rights. This observational study aimed to determine if deficit irrigation of alfalfa (Medicago sativa L.) can be used to reduce CU, provide parameters for an alfalfa crop water production function (WPF), and evaluate the potential for improved farm income by leasing water. Soil water balance, evapotranspiration (ET), and dry matter yield from eight commercial fields (1.70 to 2.14 ha zones), growing subsurface drip-irrigated alfalfa, were monitored for five seasons (2018–2022) at Kersey, Colorado. Four irrigation treatments [Standard Irrigation (SI) = irrigate when soil water deficit (D) exceeds management allowed depletion (MAD); Moderate Deficit Irrigation (MDI) = 70% of SI; Severe Deficit Irrigation (SDI) = 50% of SI; and Over Irrigation (OI) = 120% of SI] were applied, with two zones per treatment. Reductions in CU ranged from 205 to 260 mm per season. The shape of the alfalfa WPF (dry biomass yield vs. ET) was concave, indicating that water use efficiency (WUE) could be optimized through deficit irrigation. The average WUE was 0.17 Mg ha−1 cm−1 and tended to increase with greater deficits. Deficit irrigation also increased the relative feed value. If conserved CU from deficit irrigation can be leased into a transfer water market, farmers could profit when the water lease revenue exceeds the forgone profit from alfalfa production. We found incremental profit from deficit irrigation and water leasing to be positive, assuming 2020 prices for hay ($230 bale−1) and water prices above $0.50 m−3.

Factors affecting host plant selection in alfalfa aphids.

Alfalfa (Medicago sativa L.) hosts several species of aphid, Acyrthosiphon pisum (Harris), Aphis craccivora Koch and Therioaphis trifolii (Monell). The preference of the aphids of alfalfa plants for dense assemblies or individual plants, as well as for healthy or infested plants, was investigated in the field as in the laboratory. Years of field research have revealed the specific preferences of all three species of aphid. A. pisum and T. trifolii are most commonly found in alfalfa crops, while A. craccivora is mostly found on alfalfa weeds. Also, a single species of aphid alone is usually present on a plant. In order to determine the reason for this clear preference and to establish whether at the very beginning, i.e. at the stage of choosing a host, aphid species distance themselves from each other, we tested the effect of the volatiles of healthy and infested plants on their attractiveness to aphids. A. craccivora is repelled by the volatiles of dense crops and plants previously infested with one of the other two species. A. pisum and T. trifolii choose a dense assembly of plants, repelled by the volatiles of plants previously infested with A. craccivora. A. pisum displays the weakest competitive traits, and A. craccivora the strongest. This research showed that competition between aphid species does not occur only when they find themselves on the same plant at the same time, fighting for resources, but also in the choice of plant, in order to avoid later competition.

Ensifer meliloti denitrification is involved in infection effectiveness and N2O emissions from alfalfa root nodules

PurposeAlfalfa is one of the most valuable forage crops in temperate climate zones. Ensifer meliloti, the endosymbiont of alfalfa, contains all the denitrification genes but the capacity of alfalfa root nodules to produce nitrous oxide (N2O) is not known. In this work, N2O emissions as well as the influence of bacteroidal denitrification on nodulation competitiveness and N2O release from alfalfa nodules has been investigated.MethodsMedicago sativa cv. Victoria plants were inoculated with E. meliloti 1021, a periplasmic nitrate reductase (Nap) defective mutant, a Nap overexpressing strain and a nitrous oxide reductase defective mutant. Plants were grown in the presence of different nitrate and copper treatments and subjected to flooding during one week before harvesting. N2O production by the nodules was analysed by using gas chromatography. Methyl viologen-dependent nitrate reductase (MV+-NR), nitrite reductase (MV+-NIR) and nitrous oxide reductase (N2OR) enzymatic activities were measured in isolated bacteroids.ResultsAlfalfa root nodules produce N2O in response to nitrate and flooding. Overexpression of Nap improved nodulation competitiveness and induced N2O emissions from nodules. Copper is required for an effective symbiosis as well as triggered a reduction of N2O production due to the induction of the N2OR and a reduction of NIR activities in the bacteroids.ConclusionAlfalfa root nodules emit N2O. Nap is involved in nodulation competitiveness and in N2O emissions by the nodules. Bacteroidal N2OR and NIR activities are modulated by Cu and may be considered as effective targets for the mitigation strategies of N2O emissions derived from alfalfa crops.

Assessment of Irrigation Efficiency by Coupling Remote Sensing and Ground-Based Data: Case Study of Sprinkler Irrigation of Alfalfa in the Saratovskoye Zavolgie Region of Russia.

Nowadays, the leading role of data from sensors to monitor crop irrigation practices is indisputable. The combination of ground and space monitoring data and agrohydrological modeling made it possible to evaluate the effectiveness of crop irrigation. This paper presents some additions to recently published results of field study at the territory of the Privolzhskaya irrigation system located on the left bank of the Volga in the Russian Federation, during the growing season of 2012. Data were obtained for 19 crops of irrigated alfalfa during the second year of their growing period. Irrigation water applications to these crops was carried out by the center pivot sprinklers. The actual crop evapotranspiration and its components being derived with the SEBAL model from MODIS satellite images data. As a result, a time series of daily values of evapotranspiration and transpiration were obtained for the area occupied by each of these crops. To assess the effectiveness of irrigation of alfalfa crops, six indicators were used based on the use of data on yield, irrigation depth, actual evapotranspiration, transpiration and basal evaporation deficit. The series of indicators estimating irrigation effectiveness were analyzed and ranked. The obtained rank values were used to analyze the similarity and non-similarity of indicators of irrigation effectiveness of alfalfa crops. As a result of this analysis, the opportunity to assess irrigation effectiveness with the help of data from ground and space-based sensors was proved.

Effectiveness landscape of crop pollinator assemblages: Implications to pollination service management

There is a growing consensus that the world is facing a pollination crisis. To mitigate crop pollination deficits, some management strategies include the massive introduction of managed bee species, yet quite often they are applied blindly, as information on crop pollination effectiveness for each single pollinator species of assemblages is usually not available. Therefore, the introduction on managed species is not always the best option to improve crop yields. Here, by using the highly pollinator-dependent alfalfa crop (Medicago sativa L.) as a case study, we propose the use of the effectiveness landscape framework to identify key crop pollinator species. According to this framework, in a mutualistic interaction, each species´ effectiveness is represented by the product of a quantitative component and a qualitative one, these being measures of the outcomes of this interaction. We applied this framework for two managed and four wild bee species that visit alfalfa in fields southwest of Buenos Aires province, Argentina. We dissected the quantity components of the pollinator effectiveness landscape by estimating two quantitative subcomponents: visitation rate and flower tripping rate. Also, we estimate pod set as a qualitative component without dissecting it in subcomponents. Our results showed that the contribution of both components and the resulting pollinator effectiveness varied among pollinator species, indicating a contrasting effectiveness of different bee species on alfalfa pollination. For example, pollinator effectiveness was higher for managed than for wild bees, as consequence of their very high visitation rate, however, wild bee flower tripping rate and pod set were as high as managed ones. In fact, wild bees were more effective in promoting flower tripping than one of the managed bees (A. mellifera). This approach allowed us to assess which effectiveness components and subcomponents make pollinator species more or less effective, thus providing valuable information to identify key species to be enhanced to help in closing yield gaps. We suggest that the application of the effectiveness landscape framework would be useful to develop strategies to improve crop pollination service in pollinator-dependent crop systems.