Apple Crop Research Articles

Оцінка небезпечності, комплексне гігієнічне нормування сульфоксафлору в сільськогосподарській продовольчій сировині, об’єктах виробничого і навколишнього середовища та обґрунтування регламентів безпечного застосування інсектициду на його основі

ABSTRACT. Sulfoxaflor is recommended for use as an insecticide on wheat, barley, rapeseed, sugar beet, apple and cabbage. In the State Enterprise “L.I. Medved’s Research Center for Preventive Toxicology, Food and Chemical Safety, The Ministry of Health of Ukraine” a study was conducted on the toxicological and hygienic assessment of sulfoxaflor and the insecticide Transform, WG based on it; PDD of sulfoxaflor for humans, hygienic standards of the substance and regulations for safe use of the drug are substantiated. Aim. Toxicological and hygienic assessment of sulfoxaflor and its insecticide, assessment of the risk of exposure to agricultural workers and the population. Methods. Expert-analytical, toxicological, physico-chemical, hygienic. Results. According to the parameters of toxicity, sulfoxaflor and the drug Transform, WG belong to pesticides of the 2nd class of danger according to the limiting criterion of harmfulness – the reproductive toxicity of sulfoxaflor. It has a polytropic effect on the body with predominant damage to the liver and reproductive organs. Mutagenic, carcinogenic and teratogenic activity and embryotoxicity of sulfoxaflor are not limiting when assessing its danger. As a result of field studies, it was established that residual amounts of sulfoxaflor were not detected in the grain of the wheat and barley crops, the seeds of the rape crop and its oil, the roots of the sugar beet crop, the apple crop and their juice, cabbage at the limit level of detection methods. The degree of possible professional risk of exposure to flupyradifurone in case of entering the body of agricultural workers by inhalation and dermal routes does not exceed the permissible level. Conclusions. The use of the insecticide Transform, WG based on sulfoxaflor in the agriculture of Ukraine on wheat, barley, rapeseeds, sugar beetroots, apples and cabbage in compliance with hygienic standards and regulations is not dangerous talking about the sulfoxaflor contamination possibility of agricultural crops and environmental objects. Keywords: insecticide, sulfoxaflor, toxicological properties, hygienic standards and regulations, hazard assessment.

Bee pollination services and the burden of biogeography.

Native bees augment pollination services in the Northern Hemisphere, especially cultivated apple crops, yet Southern Hemisphere contexts are poorly known. We observed the foraging behaviour of 69 354 invertebrate flower visitors in Australian orchards (two regions, 3 years) to assess the efficacy of pollination service (Peff). Native stingless bees and introduced honey bees were the most abundant visitors and most efficacious pollinators (Tetragonula Peff = 6.16; Apis Peff = 13.02), with Tetragonula becoming important service providers above 22°C. However, visits by tree-nesting stingless bees decreased with distance from native forest (less than 200 m) and their tropical/subtropical distribution precludes pollination service in other major Australian apple-producing regions. More broadly distributed native allodapine and halictine bees transferred the most pollen per-visit, but their low abundances reduce efficacies (Exoneura Peff = 0.03; Lasioglossum Peff = 0.06), resulting in a general dependence on honey bees. This reliance is a burden of biogeography, since key Northern Hemisphere pollinators of apple (Andrena, Apis, Bombus, Osmia) do not naturally occur in Australasia-where there is only 15% generic overlap with Central Asian bees sympatric with wild apple distributions (cf. Palaearctic 66% and Nearctic 46% generic overlaps). The historical biogeography of bees therefore drives an extreme dependence on one introduced species for apple pollination in Australia.

MhCLC-c1, a Cl channel c homolog from Malus hupehensis, alleviates NaCl-induced cell death by inhibiting intracellular Cl– accumulation

BackgroundOveraccumulation of chloride (Cl) when plants suffer NaCl causes cell damage and death, and is regulated by Cl– channel protein (CLC). Apple roots are very sensitive to Cl–, but information associated with CLC is limited in apple crop that widely cultivated in the world.ResultsWe identified 9 CLCs from the apple genome and divided them into two subclasses. Among them, MdCLC-c1 promoter contained the largest number of cis-acting elements associated with NaCl stress, and only the MdCLC-c1, MdCLC-d, and MdCLC-g were predicted that may be Cl– antiporters or channels. Expression analysis of MdCLCs homologs in the roots of Malus hupehensis showed that most of the MhCLCs expression were response to NaCl stress, especially MhCLC-c1 expression was upregulated continuously and rapidly expressed during NaCl treatment. Therefore, we isolated MhCLC-c1 and observed it was a plasma membrane-localized protein. The MhCLC-c1 suppression significantly increased sensitivity, reactive oxygen species content, and cell death of apple calli; while MhCLC-c1 overexpression decreased sensitivity, reactive oxygen species content, and cell death of apple calli and Arabidopsis by inhibiting intracellular Cl– accumulation under NaCl stress.ConclusionsThe study selected and isolated a CLC-c gene MhCLC-c1 from Malus hupehensis based on identification of CLCs gene family in apple, and their homologs MhCLCs expression patterns during NaCl treatments, revealing that MhCLC-c1 alleviates NaCl-induced cell death by inhibiting intracellular Cl– accumulation. Our findings confer the comprehensive and in-depth upstanding of the mechanism that plants resist salt stress, and might also confer genetic improvement of salt tolerance in horticultural crops and the development and utilization of saline–alkali land.

Queer subtext in The Wicker Man (1973)

ABSTRACT There is surprisingly scant research on queer subtext in The Wicker Man (1973). I suggest Lord Summerisle, who was portrayed by Christopher Lee, is a queer-coded villain. On the night Willow MacGregor deflowers an adolescent named Ash Buchanan, Summerisle observes a pair of copulating snails, quotes Walt Whitman, and envisions Howie alone in his bedroom. Most terrestrial snails are considered hermaphrodites and liking Whitman, who was probably queer, was historically a code for homosexuality. Summerisle recites Whitman’s poem celebrating animals that ‘do not lie awake in the dark and weep for their sins’ or make him ‘sick’ discussing their ‘duty’ to the Christian God. The scene implies Summerisle wishes to deflower Howie the way Willow deflowers Ash, and mate with him like the snails. Summerisle resents Howie because his conservative Christianity prevents them from becoming lovers. Summerisle wants to believe Howie will reincarnate as his apple crops; he and his followers intend to consume his flesh and drink his blood in the form of fruit. Like Dracula, whom Lee was famous for playing, Summerisle seeks to penetrate Howie with his teeth in a metaphor for sex.

Analyzing the Quality Parameters of Apples by Spectroscopy from Vis/NIR to NIR Region: A Comprehensive Review.

Spectroscopic methods deliver a valuable non-destructive analytical tool that provides simultaneous qualitative and quantitative characterization of various samples. Apples belong to the world's most consumed crops and with the current challenges of climate change and human impacts on the environment, maintaining high-quality apple production has become critical. This review comprehensively analyzes the application of spectroscopy in near-infrared (NIR) and visible (Vis) regions, which not only show particular potential in evaluating the quality parameters of apples but also in optimizing their production and supply routines. This includes the assessment of the external and internal characteristics such as color, size, shape, surface defects, soluble solids content (SSC), total titratable acidity (TA), firmness, starch pattern index (SPI), total dry matter concentration (DM), and nutritional value. The review also summarizes various techniques and approaches used in Vis/NIR studies of apples, such as authenticity, origin, identification, adulteration, and quality control. Optical sensors and associated methods offer a wide suite of solutions readily addressing the main needs of the industry in practical routines as well, e.g., efficient sorting and grading of apples based on sweetness and other quality parameters, facilitating quality control throughout the production and supply chain. This review also evaluates ongoing development trends in the application of handheld and portable instruments operating in the Vis/NIR and NIR spectral regions for apple quality control. The use of these technologies can enhance apple crop quality, maintain competitiveness, and meet the demands of consumers, making them a crucial topic in the apple industry. The focal point of this review is placed on the literature published in the last five years, with the exceptions of seminal works that have played a critical role in shaping the field or representative studies that highlight the progress made in specific areas.

Effects of a realistic pesticide spraying sequence for apple crop on stream communities in mesocosms: negligible or notable?

BackgroundSeveral large-scale studies revealed impacts and risks for aquatic communities of small rural lakes and streams due to pesticides in agricultural landscapes. It appears that pesticide risk assessment based on single products does not offer sufficient protection for non-target organisms, which are exposed repeatedly to pesticide mixtures in the environment. Therefore, a comprehensive stream mesocosm study was conducted in order to investigate the potential effects of a realistic spraying sequence for conventional orchard farmed apples on a stream community using pesticides at their regulatory acceptable concentrations (RACs). Eight 74-m-long stream mesocosms were established with water, sand, sediment, macrophytes, plankton and benthic macroinvertebrates. In total, nine fungicidal, four herbicidal and four insecticidal pesticides were applied in four of the eight stream mesocosms on 19 spraying event days in the period from April to July while the remaining four stream mesocosms served as controls. The community composition, the abundance of benthos, periphyton and macrophytes, the emergence of insects, physico-chemical water parameters, and drift measurements of aquatic invertebrates were measured.ResultsThe pesticide spraying sequence induced significant effects on invertebrates, periphyton, and macrophytes as well as on the water ion composition especially in the second half of the experiment. It was not possible to relate the observed effects on the community to specific pesticides applied at certain time points and their associated toxic pressure using the toxic unit approach. The most striking result was the statistically significant increase in variation of population response parameters of some taxa in the treated mesocosms compared to the controls. This inter-individual variation can be seen as a general disturbance measure for the ecosystem.ConclusionsThe pesticide spraying sequence simulated by using RAC values had notable effects on the aquatic stream community in the conducted mesocosm study. The results indicate that the current risk assessment for pesticides may not ensure a sufficient level of protection to the field communities facing multiple pesticide entries due to spraying sequences and other combined stress. Hence, there is still room for improvement regarding the prospective risk assessment of pesticides to further reduce negative effects on the environment.

Identification of Fungal Species Associated with Apple Canker in Tarim Basin, China.

Apple canker has decreased yields of the economically important apple (Malus domestica) crop in China in recent years. Pathogen identity is highly challenging and the disease is poorly understood. Specimens of 339 fungi were isolated from apple trees in the primary apple-producing region in the Tarim Basin during the current study. In total, nine species of Cytospora and five species of the family Botryosphaeriaceae were identified by morphological observation and multilocus phylogenetic analyses: internal transcribed spacer (ITS), actin, translation elongation factor (TEF), and β-tubulin (TUB) gene regions for Cytospora and ITS, TEF, and TUB for Botryosphaeriaceae. Cytospora pyri from the Cytospora genus was the dominant species causing apple canker in the Tarim Basin. C. melnikii, C. tritici, C. euonymina, Diplodia seriata, and Botryosphaeria dothidea have been described as the cause of apple canker in China. Apple (Red Fuji) branches were utilized to assess the pathogenicity of 24 representative fungal isolates from the 14 species, and branches from seven distinct woody plants (Korla pear, walnut, Chinese date, Xinjiang poplar, sand jujube, Populus euphratica, and willow) were utilized to analyze the host range. The main pathogenic fungal species of apple canker around the Tarim Basin were identified and biological characteristics explored. Pathogen diversity and regional source diversity were assessed with host range and pathogenicity. The aim was to provide a theoretical foundation for the prevention and treatment of apple canker.

How Machine Learning is Redefining Agricultural Sciences: An Approach to Predict Apple Crop Production of Kashmir Province

How Machine Learning is Redefining Agricultural Sciences: An Approach to Predict Apple Crop Production of Kashmir Province

Cascading effects of management and landscape on insect pollinators, pollination services and yield in apple orchards

Recent insect pollinator declines, mainly due to the expansion and intensification of agricultural land use, are jeopardizing ecosystem service provisioning in agroecosystems. Organic farming has been suggested as a biodiversity-friendly alternative to conventional farming, but additional insights evaluating its effectiveness in perennial cropping systems are needed. Here, we provide a comprehensive analysis of local and landscape effects on the provided pollination services and yield in apple crops. We first used mixed models to disentangle effects of agricultural management and landscape effects on both taxonomic and functional diversity of wild bees and hoverflies during bloom in both organic and integrated pest management (IPM) apple orchards in Belgium, and then compared these biodiversity indicators with semi-natural grasslands as a benchmark. Next, we applied piecewise structural equation modeling to quantify the direct and indirect effects of orchard management type and landscape on fruit set, seed set and ultimately on crop yield. Orchards, regardless of their type of management, hosted lower taxonomic and functional pollinator diversity compared to the semi-natural benchmark. Yet, pollinator abundance and diversity were higher in orchard edges and increased with small-scale landscape diversity, which was positively associated with the presence of semi-natural habitat, as well as arable and urban land. Investigating the cascading effects on apple yield, we found that yield levels were not shaped by the observed pollinator diversity or by the measured pollination services, but were lower in organic orchards. Overall, we conclude that apple yield was likely not pollinator limited in our study system, but that conserving and restoring semi-natural habitats, maintaining and expanding orchard edges through reducing field sizes and promoting landscape diversity are the most promising avenues for pollinator conservation in orchard landscapes.

Artificial Neural Network Based Apple Yield Prediction Using Morphological Characters

The yield of the crop is a complex function of a number of dependent traits, which makes yield prediction a statistically difficult task. A number of work on yield prediction using morphological characters already exists in the literature. Most of the work used statistical techniques such as linear regression and crop yield models, which assume a linear relationship between yield and the morphological traits; in actual practice, such a linear relationship is seldom achieved. With the advancement in the field of machine learning techniques, these methods can provide a viable alternative for dealing with nonlinear relationships for yield prediction. Globally, apples are the most consumed fruit. In this paper, attempts have been made to predict the yield of the apple crop using morphological traits. PCA was used for selection of the significant variables. These variables were later used as input variables in the ANN model with different hidden layers for predicting crop yield. The predictive performance of the model was evaluated using standard statistical tests. Sensitivity analysis was performed to find out the individual effects of each character on the apple yield. The study contributes to a better understanding of the complex relationships between crop yield and morphological traits.

Machine learning and IoT-based smart farming for enhancing the crop yield

The lack of favourable atmospheric conditions leads to the loss of many crops each year. In India alone, over 11 billion dollars are lost. By combining IoT and machine learning technologies, this team has created a system that integrates agriculture’s three primary operations: crop selection, autonomous watering, and fertiliser suggestion. The following crops—Apple, Rice, Maize, Grape, Banana, Orange, Cotton, and Coffee—were considered in the study. Three systems are covered in the paper: The crop recommendation system employs machine learning to examine factors including nitrogen (N), phosphorous (P), potassium (K), pH, and weather before recommending a crop. The crop type and the current levels of soil nutrients are the two main determinants on which the fertiliser recommendation method bases its recommendation. When employing an automatic irrigation system, the crop is irrigated automatically while taking current soil moisture levels and weather forecasts into consideration. This paper attempted to implement the mentioned systems. The paper discusses the successes of the crop recommendation system, the automatic watering system, and the fertiliser recommendation system. In this paper, we report the results of simulations of the mentioned systems.

Comparative transcriptome analysis reveals key genes and pathways in response to Alternaria alternata apple pathotype infection

Apple leaf spot, caused by the Alternaria alternata apple pathotype (AAAP), is an important fungal disease of apple. To understand the molecular basis of resistance and pathogenesis in apple leaf spot, the transcriptomes of two apple cultivars ‘Hanfu’ (HF) (resistant) and ‘Golden Delicious’(GD) (susceptible) were analyzed at 0, 6, 18, 24 and 48 h after AAAP inoculation by RNA-Seq. At each time point, a large number of significantly differentially expressed genes (DEGs) were screened between AAAP-inoculated and uninoculated apple leaves. Analysis of the common DEGs at four time points revealed significant differences in the resistance of ‘HF’ and ‘GD’ apple to AAAP infection. RLP, RNL, and JA signal-related genes were upregulated in both cultivars to restrict AAAP development. However, genes encoding CNLs, TNLs, WRKYs, and AP2s were only activated in ‘HF’ as part of the resistance response, of which, some play major roles in the regulation of ET and SA signal transduction. Further analysis showed that many DEGs with opposite expression trends in the two hosts may play important regulatory roles in response to AAAP infection. Transient expression of one such gene MdERF110 in ‘GD’ apple leaves improved AAAP resistance. Collectively, this study highlights the reasons for differential resistance to AAAP infection between ‘HF’ and ‘GD’ apples which can theoretically assist the molecular breeding of disease-resistant apple crops.

Climate trends of a typical apple growing mid- hill district of Himachal Pradesh.

For four sample decades, the study examined the long-term climate trends along with the area and production changes in Chamba district of Himachal Pradesh. A database was collected for maximum temperature (Tmax ), minimum temperature (Tmin), and rainfall, and for the area and production of apple for the four representative decades of Chamba region of Himachal Pradesh. It has been observed that trends indicated that temperature in this district showed an increasing trend and precipitation (rainfall) showed decreasing trend. Temperature, rainfall was the main parameters collected along with other meteorological parameters. The minimum and maximum temperature & rainfall data were collected from the records of government departments for the period of at-least 25-30 years. Long term trends were generated to check the change detection. The minimum temperature in Chamba district has shown an increase of 0.36°C and maximum temperature increase by 0.3°C and annual rainfall decreased by 117.95 mm in 36 years. It has also been observed that many farmers are now opting for industrial crops like mushroom, flowers, off season vegetables because of climate change. Due to an increase in temperature, apple crop is getting less chilling hours, which is somehow affecting the quality of fruit. More long term research efforts are required to be conducted in Free Air Temperature Enrichment (FATE) which can enhance this study. This study also indicates that there is an increase in area and production in Chamba district but fluctuation is seen in productivity. Shifting to higher elevation might be temporary solution to meet the chilling requirement but a proper measures need to be taken. The area under apple cultivation has increased substantially from a mere 400 hectares in 1950s to 11. 4 lakhs hectares in 2020s but fluctuation is observed in the productivity of the crop. Considering the vital role that apple has in the economy of Himachal Pradesh, there is a need to study the production and productivity of the apple crop

Ekonomski aspekti voćarske proizvodnje u Srbiji na primeru zasada jabuke

Apple is one of the most important fruits in the world and in Europe. In the Republic of Serbia, it is grown on 27,034 ha of agricultural land and, judging by this criterion, is in second place, right behind plum. The paper analyzes the production of Golden Delicious apple cultivar on a family farm in the region of Šumadija and Western Serbia, on an area of 1 ha, with a 3.2 x 0.8 m planting distance. The apple crop is in full bloom, with all agrotechnical measures necessary for proper cultivation applied in production, including irrigation. The recorded production value is from the yield of 45.0 t/ha of apples. Total variable costs amount to RSD 687,445.00/ha or EUR 5,864.83/ha. Ratio of total costs and income from apple production in 2022 gives a contribution margin of RSD 1,337,555.00/ ha or €11,411.15/ha, i.e. RSD 29.72/kg or €0.25/kg, at apple selling price of 45 din/kg, i.e. 0.38 €/kg. The efficiency of apple production is 2.95. Results point to the conclusion that apple production can be profitable and that it is a moderately risky production line.

Detection of Apple Plant Diseases Using Leaf Images Through Convolutional Neural Network

Plant diseases are a severe cause of crop losses in the agriculture globally. Detection of diseases in plants is difficult and challenging due to the lack of expert knowledge. Deep learning-based models provide promising ways to identify plant diseases using leaf images. However, need of larger training sets, computational complexity, and overfitting, etc. are the major issues with these techniques that still need to be addressed. In this work, a convolutional neural network (CNN) is developed that consists of smaller number of layers leading to lower computational burden. Some augmentation techniques such as shift, shear, scaling, zoom, and flipping are applied to generate additional samples increasing the training set without actually capturing more images. The CNN model is trained for apple crop using a publicly available dataset PlantVillage to identify Scab, Black rot, and Cedar rust diseases in apple leaves. The rigorous experimental results revealed that the proposed model is well fit to identify apple leaf diseases and achieves 98% classification accuracy. It is also evident from the results that it needs lesser amount of storage and takes smaller execution time than several existing deep CNN models. Although, there exist several CNN models for crop disease detection with comparable accuracy, but the proposed model needs lower storage and computational resources. Therefore, it is highly suitable for deploying in handheld devices.

An economic analysis of organic apple cultivation in the Foothills of Saramati mountain range: A case study of Thanamir village of Kiphire district, Nagaland

A study was carried out to assess the production and marketing condition of apple (Malus domestica L.) in the Thanamir village of Nagaland. With diverse agro-climatic condition, varied soil and low temperature with wide regional variation, this region is highly suitable for cultivation of apple. This article focuses on the importance of apple fruit, its utilization and the economic profitability from apple crop based farming system. Research survey of farmers producing apple was conducted in 2022. Total of one hundred thirty (132) apple producers were selected using random sampling methods. The result shows BCR was estimated to be 1.95, which was found greater than unity. This showed that the apple farming is quite profitable in Thanamir. The finding shows that Cobb-Douglas production function exhibits increasing return to scale. The study concluded that apple cultivation can be made viable enterprise with increased focus on investment climate by subsidising farm input, providing affordable loans to the farmers for a sustainable production and strengthening rural infrastructure. The study pointed out that the apple cultivation could be a highly beneficial and market-oriented activity in Thanamir.

IoT-Smart Agriculture: Comparative Study on Farming Applications and Disease Prediction of Apple Crop using Machine Learning

Recently, the Internet of Things has emerged as an encouraging technology that is scaling up new heights towards the modernization of real word physical objects into smarter devices in several domains. Internet of Things (IoT) based solutions in agriculture drives farming into a smart way through the proliferation of smart devices to enhanced production with minimal human involvement. This paper presents a comprehensive study of the role of IoT in prominent applications of farming, wireless communication protocols, and the role of sensors in precision farming. In this research article, the existing frameworks in IoT-based agriculture systems with relevant technologies are presented. Furthermore, the comparative analysis of the apple disease prediction system concerning different types of disease found in the apple crop are discussed. In addition, this paper presents the contributions made by numerous researchers over the past few years in the apple disease prediction system. The aim of this research is to support the development of smart agriculture applications that would be helpful in precision farming for the optimization of resources with the help of IoT in agriculture and early disease prediction in apple crops.

Impact of the B-Plus white pearl (Belyi Zhemchug) preparation on the spring frost tolerance, yield and quality of apple crops

In 2021–2022, experiments were conducted at the Laboratory of Fruit Crop Resistance Physiology, All-Russia Institute for Fruit Crops Breeding (VNIISPK), to investigate the action of the “White Pearl Antifreeze” (Belyi Zhemchug Antifriz) phytomodulator and the “White Pearl Drip Ca + Mg” (Belyi Zhemchug Drip Ca+Mg) phytocorrector produced by the AgroPlus Group of Companies, LLC. Experimental and control plots were characterized by dark-gray forest soils with a humus content of 3-4 % and a humus horizon thickness of 30–35 cm. Apple trees cv. Sinap Orlovsky (VNIISPK) grafted on semi-dwarf rootstock 54-118 were planted in 2013 according to a 6 x 3 m scheme. Natural grassing was used in row spacings; herbicides were applied around the seedlings. The experimental design included: 1) control (water treatment) and 2) foliar treatment with a 1 % solution of “White Pearl Antifreeze” + a 1 % solution of “White Pearl Drip Ca+Mg”. The experiment was conducted in three replications with five observed trees in each. Our aim was to assess the effect of the mentioned preparations on the spring frost tolerance, yield, and quality of apple fruit under the weather conditions of 2021. Foliar treatments with the studied preparations reduced the frost damage to Sinap Orlovsky apple buds by 6.3 % at -3.5 °С and by 10.4 % at -4 °С. The conducted summer foliar treatments with the organomineral mixture under study intensified the growth and ripening of apple fruit. The improved protein-carbohydrate metabolism, water regime, photosynthetic activity, and donor-acceptor leaf–fruit relations increased the fruit weight by 10 g and the yield by 1.8 times. The conclusion is made that the B-PLUS “White Pearl Antifreeze” preparation exhibits a complex effect in terms of increasing plant tolerance to low-temperature spring damage, thus improving the yield and quality of apple crops.

Effect of Agroforestry System on Soil Properties in an Acid Inceptisol under Tropical Climatic Situation of Eastern India

An experiment was carried out using the existing Field of AICRP on Agroforestry Project in Central Research Station of O.U.A.T, Bhubaneswar at a Latitude 20015’ N and longitude of 850 52’ E in order to study the effect of agroforestry system on soil properties in the surface soil. In the year 2013, the system had two tree species Dalbergia sissoo and Gmelina arborea along with 4 intercrops such as pineapple, mango ginger, turmeric and arrowroot. Soil samples were collected after 13 years of agroforestry system in the post harvest period during 2014-15 for soil properties study. With Agro forestry system there was improvement in soil bulk density, organic matter and available nutrients as compared to open field where there was loss of nutrients. Between the trees, Gmelina arborea maintained higher level of soil organic carbon, available N, available P and available K on top soil than Dalbergia sissoo. Inclusion of intercrops maintained significantly higher organic carbon and available status of NPK on the surface soil than non inter cropped system. Pine apple crop recycled a major part of the absorbed N and K causing more accumulation of N and K in all the treated plots. Among the eight combinations of tree and intercrop, Gmelina arborea +pine apple combination is considered the best agroforestry system for maintaining better soil health and sustaining the system in acidic Inceptisols under humid tropical climatic situation.

In-hive learning of specific mimic odours as a tool to enhance honey bee foraging and pollination activities in pear and apple crops

The areas devoted to agriculture that depend on pollinators have been sharply increased in the last decades with a concomitant growing global demand for pollination services. This forces to consider new strategies in pollinators’ management to improve their efficiency. To promote a precision pollination towards a specific crop, we developed two simple synthetic odorant mixtures that honey bees generalized with their respective natural floral scents of the crop. We chose two commercial crops for fruit production that often coexist in agricultural settings, the apple (Malus domesticus) and the pear trees (Pyrus communis). Feeding colonies with sucrose solution scented with the apple mimic (AM) or the pear mimic (PM) odour enabled the establishment of olfactory memories that can bias bees towards the flowers of these trees. Encompassing different experimental approaches, our results support the offering of scented food to improve foraging and pollination activities of honey bees. The circulation of AM-scented sucrose solution inside the hive promoted higher colony activity, probably associated with greater activity of nectar foragers. The offering of PM-scented sucrose solution did not increase colony activity but led to greater pollen collection, which is consistent with pear flowers offering mainly pollen as resources for the bees. Results obtained from apple and pear crops suggest that the offering of AM- and PM-scented sucrose solution increased fruit yields. This preliminary study highlights the role of in-hive olfactory learning to bias foraging preferences within pome fruit crops.