In order to reduce the use of chemical fertilizers, the use of biological inoculants has been increased. Beneficial microorganisms are used to increase crop yields by stimulating plant growth through the production of phytohormones. In the present study, Indole Acetic Acid (IAA) production was analyzed in 18 bacterial isolates with Plant Growth-Promoting (PGP) capabilities; 15 of these isolates were Rhizobium, and three were Serratia. All isolates have been characterized morphologically and biochemically, and their IAA production in the presence of tryptophan, a precursor for IAA biosynthesis, has been evaluated. IAA production was detected using the Salkowski reagent with CT-2200 spectrophotometer at 530 nm. The levels of IAA production varied between the different isolates. The top two IAA producers were selected for genetic identification using 16SrRNA primers (27F and 1492R). One of the Rhizobium isolates (NRC-R2) shared 95% sequence similarity with Rhizobium sp., according to a Blastn search in GenBank and Rhizobium leguminosarum, whereas the Serratia isolate (Ain Shams Center for Genetic Engineering and Biotechnology (ACGEB)-S2 was 99.5% similar to Serratia sp. In the near future, it is possible that these two isolates could serve as biological sources for IAA.

In order to reduce the use of chemical fertilizers, the use of biological inoculants has been increased. Beneficial microorganisms are used to increase crop yields by stimulating plant growth through the production of phytohormones. In the present study, Indole Acetic Acid (IAA) production was analyzed in 18 bacterial isolates with Plant Growth-Promoting (PGP) capabilities; 15 of these isolates were Rhizobium, and three were Serratia. All isolates have been characterized morphologically and biochemically, and their IAA production in the presence of tryptophan, a precursor for IAA biosynthesis, has been evaluated. IAA production was detected using the Salkowski reagent with CT-2200 spectrophotometer at 530 nm. The levels of IAA production varied between the different isolates. The top two IAA producers were selected for genetic identification using 16SrRNA primers (27F and 1492R). One of the Rhizobium isolates (NRC-R2) shared 95% sequence similarity with Rhizobium sp., according to a Blastn search in GenBank and Rhizobium leguminosarum, whereas the Serratia isolate (Ain Shams Center for Genetic Engineering and Biotechnology (ACGEB)-S2 was 99.5% similar to Serratia sp. Accordingly, these two isolates could serve as biological sources for IAA.

The dissipation behavior of three pesticides, bifenazate, spirodiclofen and abamectin was studied in strawberry fruits using a modified QuEChERS extraction technique. The residues of the tested acaricides were determined under field conditions after 1 hour (zero days), 1, 3, 7, 14, and 21 days. The maximum residue limits (MRLs) were 2, 2, and 0.15 mg/kg for bifenazate, spirodiclofen and abamectin, respectively. The strawberry fruits could be used safely after 15 days from bifenazate spraying and after 3 days from spirodiclofen spraying. The concentration of abamectin after 21 days did not reach MRL. The half-life values (t1/2) of bifenazate, spirodiclofen, and abamectin in strawberry fruits were 0.99, 0.86, and 5.7 days, respectively.

The dissipation behavior of three pesticides, bifenazate, spirodiclofen and abamectin was studied in strawberry fruits using a modified QuEChERS extraction technique. The residues of the tested acaricides were determined under field conditions after 1 hour (zero days), 1, 3, 7, 14, and 21 days. The maximum residue limits (MRLs) were 2, 2, and 0.15 mg/kg for bifenazate, spirodiclofen and abamectin, respectively. The strawberry fruits could be used safely after 15 days from bifenazate spraying and after 3 days from spirodiclofen spraying. The concentration of abamectin after 21 days did not reach MRL. The half-life values (t1/2) of bifenazate, spirodiclofen, and abamectin in strawberry fruits were 0.99, 0.86, and 5.7 days, respectively.

Machine learning models, Artificial neural network, Tillage performance, Energy needs, draught Tillage as one of the agricultural practices consumes the largest amount of energy, which reflects on the total production cost. The artificial neural network (ANN) technique was utilized in the current study to optimize the performance of the tillage process. The ANN-modeled multilayer perceptron network with a backpropagation learning algorithm and momentum term was used by the PYTHON program. The ANN inputs were the implement type, soil texture, moisture, bulk density, width, speed, and depth. The draught was the output (kN). Five layers composed the ANN model's optimal configuration (13-64-16-4-1). The linear and rectified linear units (ReLU) functions were utilized with hidden layers and the output layer, respectively. Momentum term and learning rate were 0.00003 and 0.9 respectively. The iteration number was 1000 epochs and stopped at 290 epochs. The coefficient of determination in the test datasets was high (0.92) while the difference between actual and predicted output was low (2.08). Bulk density and depth were the main determinants of the draft. The evaluation of the developed model for chisel, moldboard, and disk plow gave satisfactory results of 0.985, 0.924, and 0.917. In comparison to the ANNs, the regression model's correlation coefficient for predicting draught force was the lowest (0.373).

Tillage as one of the agricultural practices consumes the largest amount of energy, which reflects on the total production cost. The artificial neural network (ANN) technique was utilized in the current study to opti-mize the performance of the tillage process. The ANN-modeled multilayer perceptron network with a backpropagation learning algorithm and momen-tum term was used by the PYTHON program. The ANN inputs were: the implement type, soil texture, moisture, bulk density, width, speed, and depth. The draught was the output (kN). Five layers composed the ANN model's optimal configuration (13-64-16-4-1). The linear and rectified linear units (ReLU) functions were utilized with hidden layers and the output layer, re-spectively. Momentum term and learning rate were 0.00003 and 0.9 respec-tively. The iteration number was 1000 epochs and stopped at 290 epochs. The coefficient of determination in the test datasets was high (0.92) while the difference between actual and predicted output was low (2.08). Bulk den-sity and depth were the main determinants of the draft. The evaluation of the developed model for chisel, moldboard, and disk plow gave satisfactory re-sults of 0.985, 0.924, and 0.917. In comparison to the ANNs, the regression model's correlation coefficient for predicting draught force was the lowest (0.373).

Worldwide, potato (Solanum tuberosum L.) is one of the most essential agro-economically food crops. To ensure its presence throughout the year for food processors and to extend its shelf life, it should be stored in cold temperatures. Despite the benefits of storage at low temperatures, it causes undesirable phenomena; one of them is cold-induced sweetening, which reduces the quality and the commercial value of the potato tubers. In this study, the CRISPR technology ″Clustered Regularly Interspaced Short Palindromic Repeats″ has been used in potato cultivar Desiree via Agrobacterium mediated transformation to edit starch phosphorylase gene that is responsible for starch degradation in cold temperature storage, after regeneration steps. The regenerated plants were used in the screening of genome editing by Sanger sequencing and the ICE program. Screening results showed that Desiree 2 (DE2), Desiree 7 (DE7) and Desiree 27 (DE27) lines have mutations in sgRNA sequence that indicated a significant reduction in reduced sugar contents of tubers after cold storage for 90 and 120 days. The reduction mean values were 29.224, 35.078 and 35.862 in DE2, DE7 and DE27 respectively after 90 days and 83.212, 56.674 and 34.109 after 120 days without visible differences in plant morphology and tubers

Worldwide, potato (Solanum tuberosum L.) is one of the most essential agro-economically food crops. To ensure its presence throughout the year for food processors and to extend its shelf life, it should be stored in cold temperatures. Despite the benefits of storage at low temperatures, it causes undesirable phenomena; one of them is cold-induced sweetening, which reduces the quality and the commercial value of the potato tubers. In this study, the CRISPR technology ″Clustered Regularly Interspaced Short Palindromic Repeats″ has been used in potato cultivar Desiree via Agrobacterium mediated transformation to edit starch phosphorylase gene that is responsible for starch degradation in cold temperature storage, after regeneration steps. The regenerated plants were used in the screening of genome editing by Sanger sequencing and the ICE program. Screening results showed that Desiree 2 (DE2), Desiree 7 (DE7) and Desiree 27 (DE27) lines have mutations in sgRNA sequence that indicated a significant reduction in reduced sugar contents of tubers after cold storage for 90 and 120 days. The reduction mean values were 29.224, 35.078 and 35.862 in DE2, DE7 and DE27 respectively after 90 days and 83.212, 56.674 and 34.109 after 120 days without visible differences in plant morphology and tubers

This study aimed to use the organic polymer, chitosan, as a flocculant for harvesting microalgae Chlorella. sp. Various polymer concentrations were tested. Within three min, 50 mg/L of chitosan showed the highest efficiency (98.9±0.5%), at pH 6.3, while the lowest efficiency (86.7±0.5%) was observed at pH 7.5. Harvesting efficiency in this study was chitosan concentration dependent. The present study showed that chitosan can be a promising and sustainable solution as an organic source and environmentally friendly flocculant. Additionally, it has excellent harvest productivity and requires minimum effort for quick outcomes.

This study aimed to use the organic polymer, chitosan, as a flocculant for harvesting microalgae Chlorella. sp. Various polymer concentrations were tested. Within three min, 50 mg/L of chitosan showed the highest efficiency (98.9±0.5%), at pH 6.3, while the lowest efficiency (86.7±0.5%) was observed at pH 7.5. Harvesting efficiency in this study was chitosan concentration dependent. The present study showed that chitosan can be a promising and sustainable solution as an organic source and environmentally friendly flocculant. Additionally, it has excellent harvest productivity and requires minimum effort for quick outcomes.

Dairy cattle in Sudan are traditionally fed on separate concentrate and roughage diets. Because of the high cost of forages, feeding strategies should be attempted to reduce feeding costs. A traditional dairy ration (As-fed), composed of 49% sorghum grains (SG), 29.4% groundnut seed cake (GSC), 19.6% wheat bran (WB), 1% limestone (LS) and 1% salt (NaCl), was used as a control. The test ration was a total mixed ration (TMR) composed of 40% SG, 23% groundnut seed hulls (GSH), 20% GSC, 15% WB, 1% LS and 1 % NaCl. The control traditional ration was fed at 10 Kg/cow/day together with 7 Kg sorghum chaff. Two levels of TMR were used with alfalfa hay (AH); (17 Kg TMR + 1 Kg   AH/cow/day and 15 Kg TMR + 2 Kg AH. Three cross-bred dairy cows (European x Local) were used with the feeding regimes in a 3x3 Latin square design.  Cows consumed similar amounts of DM, CP and ME and produced similar quantities of milk (P > 0.05).  TMR had no effects (P > 0.05) on the composition of milk. The cost for TMR was decreased by 19%.TMR was thus effective in reducing feeding costs without affecting milk production and composition.

Dairy cattle in Sudan are traditionally fed on separate concentrate and roughage diets. Because of the high cost of forages, feeding strategies should be attempted to reduce feeding costs. A traditional dairy ration (As-fed), composed of 49% sorghum grains (SG), 29.4% groundnut seed cake (GSC), 19.6% wheat bran (WB), 1% limestone (LS) and 1% salt (NaCl), was used as a control. The test ration was a total mixed ration (TMR) composed of 40% SG, 23% groundnut seed hulls (GSH), 20% GSC, 15% WB, 1% LS and 1 % NaCl. The control traditional ration was fed at 10 Kg/cow/day together with 7 Kg sorghum chaff. Two levels of TMR were used with alfalfa hay (AH); (17 Kg TMR + 1 Kg   AH/cow/day and 15 Kg TMR + 2 Kg AH. Three cross-bred dairy cows (European x Local) were used with the feeding regimes in a 3x3 Latin square design.  Cows consumed similar amounts of DM, CP and ME and produced similar quantities of milk (P > 0.05).  TMR had no effects (P > 0.05) on the composition of milk. The cost for TMR was decreased by 19%.TMR was thus effective in reducing feeding costs without affecting milk production and composition.

The experiment was carried out on three different vegetable crops, Cucumber Cucumis sativus L. (Cucurbitaceae), eggplant Solanum melongena L. (Solanaceae) and okra Abelmoschus esculentus L. (Malvaceae), during summer 2021, to investigate the effect of vegetation type on spider density and diversity. For this study, the pitfall trap method was used to collect spiders from the soil surface to ensure a comprehensive representation of all spider guilds. During this study, 20 species belonging to 6 families were collected. The results showed that a total of 374, 285 and 194 individuals belonging to 18, 17 and 15 species were recorded in okra, cucumber and eggplant fields respectively. Species diversity was greater in okra cultivation. Results also indicated that the Lycosidae family was the most abundant and dominant, representing 71.75%, followed by the Linyphiidae family of 90 individuals representing 10.55% of the whole obtained population. The most dominant species were Wadicosa fidelis 152, 98 and 67 individuals and Pardosa injucunda 111, 69 and 52 individuals in okra, cucumber and eggplant respectively. It is inferred from this study that the type of plant can have an impact on spider communities.

The experiment was carried out on three different vegetable crops, Cucumber Cucumis sativus L. (Cucurbitaceae), eggplant Solanum melongena L. (Solanaceae) and okra Abelmoschus esculentus L. (Malvaceae), during summer 2021, to investigate the effect of vegetation type on spider density and diversity. For this study, the pitfall trap method was used to collect spiders from the soil surface to ensure a comprehensive representation of all spider guilds. During this study, 20 species belonging to 6 families were collected. The results showed that a total of 374, 285 and 194 individuals belonging to 18, 17 and 15 species were recorded in okra, cucumber and eggplant fields respectively. Species diversity was greater in okra cultivation. Results also indicated that the Lycosidae family was the most abundant and dominant, representing 71.75%, followed by the Linyphiidae family of 90 individuals representing 10.55% of the whole obtained population. The most dominant species were Wadicosa fidelis 152, 98 and 67 individuals and Pardosa injucunda 111, 69 and 52 individuals in okra, cucumber and eggplant respectively. It is inferred from this study that the type of plant can have an impact on spider communities.

The green bean crop (Phaseolus vulgaris) is infested with many insects such as whiteflies (Bemisia tabaci). An investigation was carried out to study the insecticidal activity of whitefly (Bemisia tabaci), five pesticides were used, namely Thiamothoxam, Sulfoxaflor, Spirotetramat, Pymetrozine, and Flonicamid, and three commercial natural pesticides, namely Superrego, Topnine, and Bernastar. Pesticides and natural pesticides were sprayed during the two seasons of 2020 and 2021. The obtained results in terms of the reduction rate of the insects' number were as follows: The highest rate of reduction appeared in Thiamothoxam and Sulfoxaflor treatments, where it reached above 80%, while the other pesticides were in the range of 40% to 60%, and the lowest reduction rate was 34.33% and 36.00 % for Bernastar during season 2020 and 2021 respectively. When evaluating the toxicity of these pesticides and natural pesticides against honeybees (Apis mellifera), the pesticides did not reveal any toxicity to honeybees, except for Thiamothoxam, Sulfoxaflor, and Superrego The LC50 and LD50 values against honeybees were 0.2 ppm and 0.000005µg/one honeybee for Thiamothoxam, 4.5 ppm and 0.0001125 µg/one bee for Sulfoxaflor, and 0.95 ppm and 0.00002375 µg /one bee for Superego respectively.

The green bean crop (Phaseolus vulgaris) is infested with many insects such as whiteflies (Bemisia tabaci). An investigation was carried out to study the insecticidal activity of whitefly (Bemisia tabaci), five pesticides were used, namely Thiamothoxam, Sulfoxaflor, Spirotetramat, Pymetrozine, and Flonicamid, and three commercial natural pesticides, namely Superrego, Topnine, and Bernastar. Pesticides and natural pesticides were sprayed during the two seasons of 2020 and 2021. The obtained results in terms of the reduction rate of the insects' number were as follows: The highest rate of reduction appeared in Thiamothoxam and Sulfoxaflor treatments, where it reached above 80%, while the other pesticides were in the range of 40% to 60%, and the lowest reduction rate was 34.33% and 36.00 % for Bernastar during season 2020 and 2021 respectively. When evaluating the toxicity of these pesticides and natural pesticides against honeybees (Apis mellifera), the pesticides did not reveal any toxicity to honeybees, except for Thiamothoxam, Sulfoxaflor, and Superrego The LC50 and LD50 values against honeybees were 0.2 ppm and 0.000005µg/one honeybee for Thiamothoxam, 4.5 ppm and 0.0001125 µg/one bee for Sulfoxaflor, and 0.95 ppm and 0.00002375 µg /one bee for Superego respectively.

Livestock plays a significant role in food production, income generation, soil quality, transportation and the overall welfare of communities, especially in developing nations. Sheep and goats are vital sources of food, livelihood and urgent financial needs. Researching livestock practices can help optimize production, enhance productivity, and improve market access, ultimately boosting the economic well-being of developing communities. Research is needed to identify climate-resilient livestock practices, develop drought-resistant breeds, and optimize feed management strategies. By enhancing the resilience of livestock systems, research can help safeguard food security and livelihoods in the face of climate change. Climate change, evidenced by temperature changes and increased extreme weather events, negatively impacts traditional farming systems and livestock production by affecting pastures, feeds, water quality and livestock diseases. Breeds of the Coastal Zone of Western Desert (CZWD) such as the Barki sheep and goat as well as the Saidi breed in Upper Egypt (UE), have adapted to these harsh conditions and are crucial for smallholders. However, there's an information gap regarding these breeds' productivity in smallholder systems. This study utilizes the Twelve Month Monitoring (12MO) survey to estimate the productivity and demographic parameters of these breeds from 2018 to 2020.

Source Agritrop Cirad (https://agritrop.cirad.fr/607737/) | International audience | Livestock plays a significant role in food production, income generation, soil quality, transportation and the overall welfare of communities, especially in developing nations. Sheep and goats are vital sources of food, livelihood and urgent financial needs. Researching livestock practices can help optimize production, enhance productivity, and improve market access, ultimately boosting the economic well-being of developing communities. Research is needed to identify climate-resilient livestock practices, develop drought-resistant breeds, and optimize feed management strategies. By enhancing the resilience of livestock systems, research can help safeguard food security and livelihoods in the face of climate change. Climate change, evidenced by temperature changes and increased extreme weather events, negatively impacts traditional farming systems and livestock production by affecting pastures, feeds, water quality and livestock diseases. Breeds of the Coastal Zone of Western Desert (CZWD) such as the Barki sheep and goat as well as the Saidi breed in Upper Egypt (UE), have adapted to these harsh conditions and are crucial for smallholders. However, there's an information gap regarding these breeds' productivity in smallholder systems. This study utilizes the Twelve Month Monitoring (12MO) survey to estimate the productivity and demographic parameters of these breeds from 2018 to 2020.

Livestock plays a significant role in food production, income generation, soil quality, transportation and the overall welfare of communities, especially in developing nations. Sheep and goats are vital sources of food, livelihood and urgent financial needs. Researching livestock practices can help optimize production, enhance productivity, and improve market access, ultimately boosting the economic well-being of developing communities. Research is needed to identify climate-resilient livestock practices, develop drought-resistant breeds, and optimize feed management strategies. By enhancing the resilience of livestock systems, research can help safeguard food security and livelihoods in the face of climate change. Climate change, evidenced by temperature changes and increased extreme weather events, negatively impacts traditional farming systems and livestock production by affecting pastures, feeds, water quality and livestock diseases. Breeds of the Coastal Zone of Western Desert (CZWD)  such as the Barki sheep and goat as well as the Saidi breed in Upper Egypt (UE), have adapted to these harsh conditions and are crucial for smallholders. However, there's an information gap regarding these breeds' productivity in smallholder systems. This study utilizes the Twelve Month Monitoring (12MO) survey to estimate the productivity and demographic parameters of these breeds from 2018 to 2020.

Livestock plays a significant role in food production, income generation, soil quality, transportation and the overall welfare of communities, especially in developing nations. Sheep and goats are vital sources of food, livelihood and urgent financial needs. Researching livestock practices can help optimize production, enhance productivity, and improve market access, ultimately boosting the economic well-being of developing communities. Research is needed to identify climate-resilient livestock practices, develop drought-resistant breeds, and optimize feed management strategies. By enhancing the resilience of livestock systems, research can help safeguard food security and livelihoods in the face of climate change. Climate change, evidenced by temperature changes and increased extreme weather events, negatively impacts traditional farming systems and livestock production by affecting pastures, feeds, water quality and livestock diseases. Breeds of the Coastal Zone of Western Desert (CZWD)  such as the Barki sheep and goat as well as the Saidi breed in Upper Egypt (UE), have adapted to these harsh conditions and are crucial for smallholders. However, there's an information gap regarding these breeds' productivity in smallholder systems. This study utilizes the Twelve Month Monitoring (12MO) survey to estimate the productivity and demographic parameters of these breeds from 2018 to 2020.