Search

As a consequence of fresh water shortage, non-conventional water resources have become increasingly demandable in semi-arid and arid areas due to the increase in population and urbanization. In Egypt, the reuse of drainage water provides a demanding supplement to irrigation water. This research aims to present natural treatment process for drainage wastewater to be reused in irrigation to support water resources and water quality control. Two biological and chemical wastewater treatment techniques (Algae and Zeolite), under different conditions, were applied to allow the reuse of wastewater to be utilized in the agriculture of very economically important crop which is maize, and comparing the production and the chemical components of the crop with the one irrigated by fresh Nile water. Water, soil and plant analyses were performed. Zeolite was characterized by XRD, SEM and FTIR. Enzymes activities were assigned also (dehydrogenase, phosphatase and nitrogenase activities) and finally the statistical analysis was determined by CoStat software. The treated wastewater chemical and biological analyses showed much better results than El-Rahawy drain wastewater analyses. The plants growth parameters results showed the higher ones with plants subjected to the chemical and biological treatments. Protein and carbohydrate levels, which are the most important plant quality indicators, showed higher concentrations in the treated ones than that irrigated with Nile water. NPK concentration of both seeds and leaves also recorded better levels. The results of the enzymes activities in cases of T4, dehydrogenase, phosphatase, and nitrogenase enzyme activity were 127.66, 40.89, and 79.58, respectively, which increased when compared with control treated with Nile water which were (112.44, 28.4, and 41.39) for dehydrogenase, phosphatase and nitrogenase enzymes respectively.

Copyright of Journal of Agricultural Economics & Social Sciences is the property of Egyptian National Agricultural Library (ENAL) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Soil contamination by pesticide residues is associated with agricultural intensification in tropical regions and endangers human health and the environment. A mixture of pesticide residues and their degradation products persist in agricultural soils and represent a risk to soil organisms. In this study, we aimed to investigate the concentration and distribution of organochlorine (OC) and organophosphate (OP) pesticide residues in agricultural soils where the industrial cultivation of maize and soybeans is intensively carried out, at three depths (0–5, 5–15, and 15–30 cm) and during two seasons (rainy and dry). Likewise, we performed the ecological risk assessment of those found pesticide residues on two earthworm species, Eisena fetida, and Aporrectoda calagionsa. We calculated the Toxicity-Exposure Ratio (TER) using Predicted no Effect Concentrations (PNEC) and measured concentrations in soils, for identifying the risk of pesticide residues separately. The Risk Quotient (RQ) method was used to evaluate the ecological risk of pesticide residue mixtures in soils from each cropping system. Endrin ketone and dieldrin were the pesticide residues with the highest frequency of detection. The highest concentration in the study was found in a soil sample from maize crops in the dry season at 15–30 cm depth (2917 ng/g). The pesticide mixture from soil samples belonging to maize (0–5 cm) and soybean (5–15 cm) crops in dry season posed the highest ecological risk for A. caliginosa with 100 %, and a maximum RQ of 82.2. Endrin ketone is the OC that contributed most to the overall toxicity of the pesticide mixture in soil samples from maize crop and dieldrin in soil samples from soybean crop. Among OP, disulfoton contributed most to RQsite in soybean crop and methyl parathion in maize crop. Results pointed out the need to apply alternatives to remediate obsolete pesticide residues and restrict the use of methyl parathion and disulfoton in maize and soybean crops, to reduce the ecological risk that represent for earthworms.

Abstract Biochar (BC) is an organic compound formed by the pyrolysis of organic wastes. Application of BCs as soil amendments has many benefits including carbon sequestration, enhanced soil fertility and sustainable agriculture production. In the present study, we acidified the different BCs prepared from rice straw, rice husk, wheat straw, cotton stalk, poultry manure, sugarcane press mud and vegetable waste; following which, we applied them in a series of pot experiments. Comparisons were made between acidified and non- acidified BCs for their effects on seed germination, soil properties (EC, pH) nutrient contents (P, K, Na) and organic matter. The treatments comprised of a control, and all above-described BCs (acidified as well as non-acidified) applied to soil at the rate of 1% (w/w). The maize crop was selected as a test crop. The results showed that acidified poultry manure BC significantly improved germination percentage, shoot length, and biomass of maize seedlings as compared to other BCs and their respective control plants. However, acidified BCs caused a significant decrease in nutrient contents (P, K, Na) of soil,maize seedlings, and the soil organic matter contents as compared to non- acidified BCs. But when compared with control treatments, all BCs treatments (acidified and non-acidified) delivered higher levels of nutrients and organic matter contents. It was concluded that none of the BCs (acidified and non-acidified) had caused negative effect on soil conditions and growth of maize. In addition, the acidification of BC prior to its application to alkaline soils might had altered soil chemistry and delivered better maize growth. Moving forward, more research is needed to understand the long-term effects of modified BCs on nutrient dynamics in different soils. In addition, the possible effects of BC application timings, application rates, particle size, and crop species have to be evaluated systemtically.

The maize crop is one of the most important strategic grain crops in Egypt due to its economic and nutritional significance, with multiple uses in the country for both non-human and human consumption. Despite the increased area cultivated with maize in Egypt and the rising local production, domestic output does not meet consumption needs. According to statistics from the average period of 2017-2021, local production is approximately 7.32 million tons, while domestic consumption is estimated at around 17.079 million tons, distributed among several uses, including 11.888 million tons for non-human consumption and 2.329 million tons for human consumption. This research aims to measure the extent to which Egyptian demand for maize imports and local consumption are influenced by positively impactful variables, which will assist agricultural policymakers in making decisions that contribute to meeting the required import quantities. During the period from 2017 to 2021, the quantity of maize consumed in Egypt reached its lowest in 2007 at approximately 11.392 million tons and its highest in 2019 at around 18.322 million tons, with an average of about 14.393 million tons during this period. The quantity of Egyptian maize imports reached its lowest in 2008 at approximately 3.022 million tons, while it peaked in 2013 at about 13.034 million tons, with an average of around 7.396 million tons. The value of Egyptian maize imports was at its lowest in 2009 at approximately 836.599 million dollars and peaked in 2022 at around 2500.913 million dollars, with an average of about 1758.948 million dollars during the period. From 2018 to 2022, maize imports were primarily concentrated from Brazil, Argentina, and Ukraine, with the average quantity of Egyptian maize imports from these countries during the study period being approximately 7.397 million tons, accounting for 86.22% of the average quantity of Egyptian maize imports during this period. To identify the factors influencing the quantity of Egyptian maize imports, it was found that the most impactful variables include the Egyptian import price of maize in dollars per ton, the import price of maize from Brazil in dollars per ton, and the average per capita share of gross domestic product at current U.S. dollar prices. Additionally, the gap in maize supply and the quantity of maize for animal feed were significant factors. Meanwhile, the variables affecting Egyptian consumption of maize included the gap in maize supply in million tons, the quantity of maize consumed in the previous year in million tons, and the average per capita share of gross domestic product at current U.S. dollar prices. The economic and statistical significance of these variables was confirmed, as was the statistical significance of the mathematical model used. [ABSTRACT FROM AUTHOR]

The development of surface irrigation using gated pipes technique canreduce the irrigation water losses and improve the irrigation water use efficiency. This study was carried out during two successive summer seasons of 2021 and 2022 on maize (Zea mays L.) crop, grown in sandy loam under modified surface irrigation system by gated pipes to evaluate the performance of using gated pipes compared to traditional surface irrigation method on water application efficiency, water distribution efficiency, water deep percolation percent and maize production under different furrows irrigation lengths 30 m (L30) and 60 m (L60) at three levels of cut-off irrigation as Q1: when the applied water was reached the end of furrow, Q2: when the applied water was reached 90% of furrow length and Q3: when the applied water was reached 80% of furrow length. The results summarized thatthe maximum average value of maize yield was 3565 kg/fed., achieved by using a gated pipes irrigation system under 60 m furrow length when cut-off irrigation 90% of furrow length. On the other hand, the minimum average value was 2589 kg/fed., which achieved by traditional irrigation method at 60 m furrow length when cut-off irrigation 80 % of furrow length. The maximum average value of the saved irrigation water was 35.04% of the average values of the total water applied, achieved in the case of using a gated pipes irrigation system at 30 m furrow length when cut-off irrigation 80% of furrow length. [ABSTRACT FROM AUTHOR]

Water deficiency has been recognized as a major abiotic stress that causes losses in maize crops around the world. The maize crop is very important due to the range of products that are derived from this plant. A potential way to reduce the damages caused by water deficiency in maize crops is through the association with plant growth-promoting bacteria (PGPB) and arbuscular mycorrhizal fungi (AMF). To define the mechanisms developed by associative PGPB and AMF in maize that are involved in protection against moderate drought (MD), this study evaluated the biometrical, anatomical, biochemical, and physiological parameters of maize grown under MD and inoculated with different PGPB (Azospirillum brasilense strain Ab-V5 and Bacillus sp. strain ZK) and with AMF. The relative water content did not change in the treatments. The association with ZK increased the shoot:total ratio, total dry weight, maximum quantum yield of photosystem II, vascular cylinder thickness, and vascular cylinder area. The Ab-V5 inoculation led to an increment in root dry weight, the area of metaxylem vessel elements, and nitrate reductase activity. The AMF association did not lead to changes in the measured parameters. The results indicate that the association with PGPB is a relevant alternative to contribute to reducing losses in maize crops under drought. However, AMF is not indicated for this crop under drought. [ABSTRACT FROM AUTHOR]

Biochar (BC) is an organic compound formed by the pyrolysis of organic wastes. Application of BCs as soil amendments has many benefits including carbon sequestration, enhanced soil fertility and sustainable agriculture production. In the present study, we acidified the different BCs prepared from rice straw, rice husk, wheat straw, cotton stalk, poultry manure, sugarcane press mud and vegetable waste; following which, we applied them in a series of pot experiments. Comparisons were made between acidified and non- acidified BCs for their effects on seed germination, soil properties (EC, pH) nutrient contents (P, K, Na) and organic matter. The treatments comprised of a control, and all above-described BCs (acidified as well as non-acidified) applied to soil at the rate of 1% (w/w). The maize crop was selected as a test crop. The results showed that acidified poultry manure BC significantly improved germination percentage, shoot length, and biomass of maize seedlings as compared to other BCs and their respective control plants. However, acidified BCs caused a significant decrease in nutrient contents (P, K, Na) of soil,maize seedlings, and the soil organic matter contents as compared to non- acidified BCs. But when compared with control treatments, all BCs treatments (acidified and non-acidified) delivered higher levels of nutrients and organic matter contents. It was concluded that none of the BCs (acidified and non-acidified) had caused negative effect on soil conditions and growth of maize. In addition, the acidification of BC prior to its application to alkaline soils might had altered soil chemistry and delivered better maize growth. Moving forward, more research is needed to understand the long-term effects of modified BCs on nutrient dynamics in different soils. In addition, the possible effects of BC application timings, application rates, particle size, and crop species have to be evaluated systemtically. [ABSTRACT FROM AUTHOR]

Abstract The production of crops depending on many factors including water, nutrient, soil types, climate and crops types, water stress and drought is in one of the important factors affecting crop productivity. The experiment was conducted in pots to evaluate the effect of biofertilizers (Bacillus simplex) with deficit irrigations on the early development and growth of maize crop under greenhouse condition. Pre sowing seed was inoculated with strain of bacteria (B+/B-) and different irrigation levels (no stress: 100% (I1) and deficit irrigation: 75 (I2), 50 (I3), 25 (I4) % of required water amount to reach pot capacity) was performed. Data was collected on different morphological characteristics and root characteristic of maize crop. Highest plant height (125 cm), stem diameter (18.02 mm), leaf area (350 cm− 2), plant weight (180.42 g in fresh, 73.58 g in dry), root length (92.83 cm) root ((91.70 g in fresh, (28.66 g in dry) weight were recorded in pots applied with 100% irrigation followed by 75%. Bacillus treated plants showed significant increase in leaf area (214.20 cm− 2), plant fresh weight (91.65 g) and dry weight (42.05 g), root length (79.20 cm), root fresh (53.52 g) and dry weight (16.70 g) compared with control (without bacteria). Likewise highest relative water content of leaf was observed with I3 followed by I2 and I1 respectively. Highest water use efficiency was recorded as 0.67 g pot− 1 mm− 1 in I1 with B + treatment. Likewise, Bacillus inoculated pots resulted in increased water use efficiency (0.44 g pot− 1 mm− 1) compared with no application (0.36 g pot− 1 mm− 1). It can be endorsed from the outcome that Bacillus inoculation increased plant biomass, root biomass of maize and water use efficiency during early growth stage of maize despite of water stress and can be used under limited water condition for crop combating during moderate to lower stress conditions.

Field experiment was conducted during kharif 2018, rabi 2018-19 and kharif 2019 at Dr. NTR College of Agricultural Engineering, Bapatla, Andhra Pradesh to study the influence of drip fertigation on maize growth parameters. The experiment was laid out in split plot design consisting of three irrigation levels (0.6 ETc (I1), 0.8 ETc (I2) and 1.0 ETc (I3)) and four nitrogen levels consisting of fertigation levels (80% RDN (N1), 100% RDN (N2), 120% RDN (N3) and Manual application (N4) on sandy clay loam soil. A drip fertigation system with venturi assembly was designed and fertigation date and quantity of nitrogen in each fertigation were calculated and applied. The results shown that, in all the seasons, the plant height at all the stages of observation, drip fertigation at 120% RDN (N3) recorded tallest plant height followed by N2, N4 and N1. The lowest days for maturity was observed in I1 treatment followed by I2 and I3 during kharif 2018. During rabi 2018-19, the lowest days for maturity was observed in I1 treatment followed by I2 and I3. During kharif 2019, the lowest days for maturity was observed in I1 treatment followed by I2 and I3. [ABSTRACT FROM AUTHOR]

Research on nanoparticles (NPs) is gaining great attention in modulating abiotic stress tolerance and improving crop productivity. Therefore, this investigation was carried out to evaluate the effects of copper oxide nanoparticles (CuO-NPs) on growth and biochemical characteristics in two maize hybrids (YH-5427 and FH-1046) grown under normal conditions or subjected to saline stress. A pot-culture experiment was carried out in the Botanical Research Area of "the University of Lahore", Lahore, Pakistan, in a completely randomized design. At two phenological stages, both maize hybrids were irrigated with the same amount of distilled water or NaCl solution (EC = 5 dS m−1) and subjected or not to foliar treatment with a suspension of CuO-NPs. The salt stress significantly reduced the photosynthetic parameters (photosynthetic rate, transpiration, stomatal conductance), while the sodium content in the shoot and root increased. The foliar spray with CuO-NPs improved the growth and photosynthetic attributes, along with the N, P, K, Ca, and Mg content in the roots and shoots. However, the maize hybrid YH-5427 responded better than the other hybrid to the saline stress when sprayed with CuO-NPs. Overall, the findings of the current investigation demonstrated that CuO-NPs can help to reduce the adverse effects of salinity stress on maize plants by improving growth and physio-biochemical attributes. [ABSTRACT FROM AUTHOR]

Direct measurement of carbon and water fluxes at high frequency makes eddy covariance (EC) as the most preferred technique to characterize water use efficiency (WUE). However, reliability of EC fluxes is hinged on energy balance ratio (EBR) and inclusion of low-frequency fluxes. This study is aimed at investigating the role of averaging period to represent EC fluxes and its propagation into WUE dynamics. Carbon and water fluxes were monitored in a drip-irrigated Maize field at 10 Hz frequency and are averaged over 1, 5, 10, 15, 30, 45, 60, and 120 minutes considering daytime unstable conditions. Optimal averaging period to simulate WUE fluxes for each growth stage is obtained by considering cumulative frequency (ogive) curves. A clear departure of EBR from unity was observed during dough stage of the crop due to ignorance of canopy heat storage. Error in representing water (carbon) fluxes relative to the conventional 30 min. average is within ± 3 % (± 10 %) for 10-120 min. averaging and is beyond ± 3 % (± 10 %) for other time-averages. Ogive plots conclude that optimal averaging period to represent carbon and water fluxes is 15-30 min. for 6th leaf and silking stages, and is 45-60 min. for dough and maturity stages. Dynamics of WUE considering optimal averaging periods are in the range of 1.49 ± 0.95, 1.37 ± 0.74, 1.39 ± 0.79, and 3.06 ± 0.69 µmol mmol-1 for the 6th leaf, silking, dough, and maturity stages respectively. Error in representing WUE with conventional 30 min. averaging is marginal (< 1.5 %) except during the dough stage (12.12 %). Our findings can help in developing efficient water management strategies by accurately characterizing WUE fluxes from the EC measurements. [ABSTRACT FROM AUTHOR]

Although the Internet of Things (IoT) has been considered one of the most promising technologies to automate various daily life activities, that is, monitoring and prediction, it has become extremely useful for problem solving with the introduction and integration of artificial intelligence (AI)‐enabled smart learning methodologies. Therefore, due to their overwhelming characteristics, AI‐enabled IoTs have been used in different application environments, such as agriculture, where detection, prevention (if possible), and prediction of crop diseases, especially at the earliest possible stage, are desperately required. Bacterial stalk root is a common disease of tomatoes that severely affects its production and yield if necessary measures are not taken. In this article, AI and an IoT‐enabled decision support system (DSS) have been developed to predict the possible occurrence of bacterial stalk root diseases through a sophisticated technological infrastructure. For this purpose, Arduino agricultural boards, preferably with necessary embedded sensors, are deployed in the agricultural field of maize crops to capture valuable data at a certain time interval and send it to a centralized module where AI‐based DSS, which is trained on an equally similar data set, is implemented to thoroughly examine captured data values for the possible occurrence of the disease. Additionally, the proposed AI‐ and IoT‐enabled DSS has been tested on benchmark data sets, that is, freely available online, along with real‐time captured data sets. Both experimental and simulation results show that the proposed scheme has achieved the highest accuracy level in timely prediction of the underlined disease. Finally, maize crop plots with the proposed system have significantly increased the yield (production) ratio of crops. [ABSTRACT FROM AUTHOR]

Taxonomic identification of arbuscular mycorrhizal (AM) fungal spores extracted directly from the field is sometimes difficult because spores are often degraded or parasitized by other organisms. Single-spore inoculation of a suitable host plant allows for establishing monosporic cultures of AM fungi. This study aimed to propagate AM fungal spores isolated from maize soil using single spores for morphological characterization. First, trap cultures were established to trigger the sporulation of AM fungal species. Second, trap cultures were established with individual morphotypes by picking up only one spore under a dissecting microscope and transferring it to a small triangle of sterilized filter paper, which was then carefully inoculated below a root from germinated sorghum seeds in each pot and covered with a sterile substrate. All pots were placed in sunbags and maintained in a plant growth room for 120 days. Spores obtained from single spore trap cultures from each treatment, maize after oats (MO), maize after maize (MM), maize after peas (MP), and maize after soybean (MS), were extracted using the sieving method. Healthy spores were selected for morphological analysis. Direct PCR was conducted by crushing spores in RNAlater and applying three sets of primer pairs: ITS1 × ITS4, NS31 × AML2, and SSUmcf and LSUmBr. Nucleotide sequences obtained from Sanger sequencing were aligned on MEGA X. The phylogenetic tree showed that the closest neighbors of the propagated AM fungal species belonged to the genera Claroideoglomus, Funneliformis, Gigaspora, Paraglomus, and Rhizophagus. The morphological characteristics were compared to the descriptive features of described species posted on the INVAM website, and they included Acaulospora cavernata, Diversispora spurca, Funneliformis geosporus, Funneliformis mosseae, Gigaspora clarus, Gigaspora margarita, Glomus macrosporum, Paraglomus occultum, and Rhizophagus intraradices. These findings can provide a great contribution to crop productivity and sustainable management of the agricultural ecosystem. Also, the isolate analyzed could be grouped into efficient promoters of growth and mycorrhization of maize independent of their geographical location.

To study the state of potassium in the soil using the intensity and capacitance relationships, and to find out the effect of adding mineral fertilizers NPK and biochar on the dry weight of the vegetative part and seeds, as well as on the potassium content in the vegetative part and seeds of corn crops, we chose the field of the College of Agriculture and Forestry at the University of Mosul. The field was divided into nine blocks with three replications according to a randomized complete block design. Urea was used as a source of nitrogen at three levels (0, 160, 320) kg h-1, while potassium sulfate was added as a source of potassium at three levels (0, 40, 80) kg K2O h-1, and also tri-superphosphate fertilizer was used as a source of phosphorus at three levels (0, 100, 200) kg ha-1, noting that nitrogen was added in two batches, the first before planting and the second batch a month after germination. Biochar was added at three levels: %0, %1, and %2. The results indicated that the values of the ionic activity ratio ranged between (0.056 -0.141) mol. L-0.5, while the values of labile potassium ranged between (2.980-7.852) Cmolc.kg-1, and the free energy values ranged between (-1705.371) cal. mole kelvin-1 and (-1160.957) cal. mole kelvin-1, whereas the values of the Potential Buffering Capacity ranged between (45.346 -55.737) Cmolc.kg-1/mol-1.L0.5.

In the recent era of globalization and climatic uncertainties, farmers are continuously adopting new strategies and crops to ensure substantial production and income. However, these adaptations always need to be based on systematic decisions; otherwise, the entire environment may degrade. The present study is one of such attempts to understand where to adopt an emerging crop (Maize) in lower Gangetic West Bengal. The decision on suitable sites was taken based on the analysis of fourteen important indicators in a GIS integrated fuzzy-MCE environment aided with different geostatistical interpolation models. The output shows that 18 and 30% of the total agricultural area of the study region is highly suitable and suitable for Maize cultivation following the FAO-based suitability classification arena. Spatially, it can be said that the farmers from a few blocks of the study area, namely Chanchal-I, II, Harishchandrapur I, II, Lalgola, Bamangola, Ratua-I, II, Suti, Burwan, etc., can ensure a sustainable profit by adopting Maize cultivation. [ABSTRACT FROM AUTHOR]

Water deficiency has been recognized as a major abiotic stress that causes losses in maize crops around the world. The maize crop is very important due to the range of products that are derived from this plant. A potential way to reduce the damages caused by water deficiency in maize crops is through the association with plant growth-promoting bacteria (PGPB) and arbuscular mycorrhizal fungi (AMF). To define the mechanisms developed by associative PGPB and AMF in maize that are involved in protection against moderate drought (MD), this study evaluated the biometrical, anatomical, biochemical, and physiological parameters of maize grown under MD and inoculated with different PGPB (Azospirillum brasilense strain Ab-V5 and Bacillus sp. strain ZK) and with AMF. The relative water content did not change in the treatments. The association with ZK increased the shoot:total ratio, total dry weight, maximum quantum yield of photosystem II, vascular cylinder thickness, and vascular cylinder area. The Ab-V5 inoculation led to an increment in root dry weight, the area of metaxylem vessel elements, and nitrate reductase activity. The AMF association did not lead to changes in the measured parameters. The results indicate that the association with PGPB is a relevant alternative to contribute to reducing losses in maize crops under drought. However, AMF is not indicated for this crop under drought.

Copyright of Journal of Agricultural Economics & Social Sciences is the property of Egyptian National Agricultural Library (ENAL) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In the agricultural sector, identifying plant diseases at their earliest possible stage of infestation still remains a huge challenge with respect to the maximization of crop production and farmers’ income. In recent years, advanced computer vision techniques like Vision Transformers (ViTs) are being successfully applied to identify plant diseases automatically. However, the MLP module in existing ViTs is computationally expensive as well as inefficient in extracting promising features from diseased images. Therefore, this study proposes a comparatively lightweight and improved vision transformer network, also known as “TrIncNet” for plant disease identification. In the proposed network, we introduced a modified encoder architecture a.k.a. Trans-Inception block in which the MLP block of existing ViT was replaced by a custom inception block. Additionally, each Trans-Inception block is surrounded by a skip connection, making it much more resistant to the vanishing gradient problem. The applicability of the proposed network for identifying plant diseases was assessed using two plant disease image datasets viz: PlantVillage dataset and Maize disease dataset (contains in-field images of Maize diseases). The comparative performance analysis on both datasets reported that the proposed TrIncNet network outperformed the state-of-the-art CNN architectures viz: VGG-19, GoogLeNet, ResNet-50, Xception, InceptionV3, and MobileNet. Moreover, the experimental results also showed that the proposed network had achieved 5.38% and 2.87% higher testing accuracy than the existing ViT network on both datasets, respectively. Therefore, the lightweight nature and improved prediction performance make the proposed network suitable for being integrated with IoT devices to assist the stakeholders in identifying plant diseases at the field level. [ABSTRACT FROM AUTHOR]

This study investigates the issues that affect market access among smallholder maize farmers from a supply chain perspective. A cross-sectional questionnaire survey was used to test the relevance of access theory in assessing the effect of supply chain issues on market access. A total of 359 smallholder maize farmers were sampled randomly from Mbozi district in Tanzania for analysis. The effect of supply chain issues on market access were estimated by using marginal effects based on binary logit model. The study’s findings indicate that supply chain-related issues are significant predictors of market access among smallholder maize farmers in the surveyed area. Issues like long marketing and distribution channels, deficient supply chain infrastructure and intensive competition between the supply chains revealed a negative and significant effect on market access among smallholder maize farmers. Besides, better collaborations and networking, appropriate marketing skills and smallholders’ ability in meeting customers’ requirements revealed a positive and significant effect. Based on these results, authors recommend streamlined coordination and collaboration among agricultural multi-tiers, improve supply chain infrastructure and better quality of agricultural products as the important drivers toward enhanced market access among smallholder maize farmers. More specifically, this study enriches scholars and policymakers with information on the supply issues that affect market access among smallholder farmers, offers some managerial implications and direction for further studies.

While in the atmosphere nitrogen is abundant, this element plays a limited role as nutrient for plants. Cereal crops, as an example, are uncapable to directly use freely available nitrogen gas. As a consequence, their optimal growing and, in general, the productivity of such crops relies mainly on the use of chemical fertilizers, which, under the European Green Deal and the Farm to Fork Strategy are under scrutiny with plans of reduction of their use. As increasing crop production is a vital target for agriculture and food systems, the role of nitrogen fixers could play a fundamental role to match the targets of increasing the food production by decreasing the use of chemical fertilizers. Also, such approach is very appropriate from the perspective of sustainable production and conservative agriculture. The present work has the objective to examine the role of nitrogen fixers on the maize yield, respectively the productivity in harvested maize crop treated with Azotobacter chrococcum, Azotobacter vinelandii and Bacillus megaterium, three different nitrogen-fixing bacteria. The investigations were based on field tests. Thus, there at the beginning the seeds were inoculated before seeding; and during the vegetation the crops were treated with the three bacteria species. The fields experiment was organized in four variants (one non-treated variant and three with the bacteria Azotobacter chrococcum, Azotobacter vinelandii and Bacillus megaterium) and three replicates. The examination of collected samples revealed a general increase in productivity in the variants treated with Azotobacter vinelandii. [ABSTRACT FROM AUTHOR]

The profitability of maize cultivation depends on the production yield of this crop. This paper presents the analysis of the yield and profitability of maize cultivation in three crop farms of different sizes in Romania. From the analysis carried out, a number of results are obtained, which lead to the conclusion that in order to reach the profitability threshold, the production in the 60 ha farm would have to be at least 133.26 tons of maize in 2019, at least 85.83 tons of maize in 2020, and at least 165.56 tons of maize in 2021; in the 600 ha farm, the production in 2019 would have to be at least 2.350.23 tons of maize in 2019, 2,198.44 tons of maize in 2020, and 3,172.33 tons of maize in 2021; and in the 3,000 ha farm, the production should have been at least 4,157.75 tons of maize in 2019, 4,424.70 tons of maize in 2020, and 6,284.46 tons of maize in 2021. These productions were made only by the farm of 3,000 ha, which had a constant profitability of the maize crop, exceeding the profitability threshold every year, as follows: in 2019 with 2,216.85 tons of maize, in 2020 with 2,738.60 tons of maize and in 2021 with 3,887.34 tons. On farms of 60 ha and 600 ha, the profitability threshold could not be reached, in most cases, the major causes being of agropedoclimatic and economic nature. The conclusion of the analysis carried out was that, in order to have a constant profitability of the maize crop, it is necessary to counteract the drought by introducing irrigation to this crop, reducing production expenses and increasing the value of subsidies, so that the gross product highlights the profitability of the maize crop. [ABSTRACT FROM AUTHOR]

A field experiment was conducted in Al-Muthanna Governorate on the banks of the Al-Suwer River in Iraq in the spring of 2017. The objective of this study was to know the effect of adding humic and fulvic fertilizers and zinc sulfate fertilizers on the availability of zinc and phosphorous in the soil and plants and the yield of maize crops. Four treatments of humic and fulvic fertilizers were used: Without adding acid (H0), spraying at a concentration of 10 mL/L after 40 and 80 days of planting (H1), soaking the seeds at a concentration of 20 mL/L24 h before planting (H2), and soaking seeds at a concentration of 20 mL/Lplus spraying at a concentration of 10 mL/L(H3). Furthermore, three levels of zinc sulfate fertilizer were used after 40 and 80 days of planting: 0 mL/L (Z0), 30 mL/L (Z1), and 60 mL/L (Z2). The experimental design of this study was a Randomized Complete Block Design (RCBD) with three replicates/treatments. Soil and plant samples were collected at the end of the experiment. The results showed the superiority of the treatments H3Z2 and H3Z1, suggesting the dependence on the availability of zinc and phosphorus in the soil that impacted its content in the plant, dry matter, and grain weight. The H3Z2 and H3Z1 treatments achieved 0.683 and 0.678 mg Zn/kg soil and 0.241 and 0.230 kg Zn/ha and 26.25, 24.02 mg P/kg soil and 22.49 and 21.51 kg P/ha and 10.19 and 9.75 mg Mg/kg soil, and 7.712 and 7.632 kg Mg/ha, respectively. [ABSTRACT FROM AUTHOR]

Phytoavailable cadmium (Cd) refers to the fraction of total cadmium in soil that is easily taken up by plants, which degrades the environmental quality and can cause contamination in the food chain. Cd contamination causes high carcinogenicity and toxicities, which harm both the environment and human health, including damage to the kidneys, bones, and respiratory system. In this study, seven extracting agents like ammonium bicarbonate diethylene triamine penta acetic acid (ABDTPA) and neutral salts having low and higher concentrations were used for the determination of phytoavailable Cd in sandy clay loam (SCL) and clay loam (CL) soils contaminated with Cd at naturally-Cd, Cd-20, Cd-40, and Cd-60 mg kg-1 and correlate it with Cd contents in roots, shoots, and grains of maize crop. Extraction efficiency of extractants remains in order: 10 M NH4AOc > ABDTPA > 1 M NH4AOc > 0.1 M CaCl2 > 0.01 M CaCl2 > 1 M NaNO3 > 0.1 M NaNO3. ABDTPA showed significantly the highest positive correlation with maize roots, shoots, and grains Cd contents in naturally Cd contaminated SCL and CL soils. While for artificially contaminated SCL and CL soils contaminated with Cd at Cd-20, Cd-40, and Cd-60 contamination levels, 0.1 M CaCl2 extractable Cd showed a stronger positive significant correlation with Cd contents in roots, shoots, and grains of maize crop. Overall results concluded that 10 M NH4AOc has the highest efficiency to extract Cd and 0.1 M NaNO3 has the lowest Cd extraction efficiency. Correlation results showed that ABDTPA and 0.1 M CaCl2 were found to be the most suitable extractants for predicting the bioavailability of Cd. Highly concentrated extractants give a stronger positive correlation as compared to low concentrated extractants. SCL soil showed stronger positive correlations as compared to CL soil. [ABSTRACT FROM AUTHOR]

Research on nanoparticles (NPs) is gaining great attention in modulating abiotic stress tolerance and improving crop productivity. Therefore, this investigation was carried out to evaluate the effects of copper oxide nanoparticles (CuO-NPs) on growth and biochemical characteristics in two maize hybrids (YH-5427 and FH-1046) grown under normal conditions or subjected to saline stress. A pot-culture experiment was carried out in the Botanical Research Area of “the University of Lahore”, Lahore, Pakistan, in a completely randomized design. At two phenological stages, both maize hybrids were irrigated with the same amount of distilled water or NaCl solution (EC = 5 dS m−1) and subjected or not to foliar treatment with a suspension of CuO-NPs. The salt stress significantly reduced the photosynthetic parameters (photosynthetic rate, transpiration, stomatal conductance), while the sodium content in the shoot and root increased. The foliar spray with CuO-NPs improved the growth and photosynthetic attributes, along with the N, P, K, Ca, and Mg content in the roots and shoots. However, the maize hybrid YH-5427 responded better than the other hybrid to the saline stress when sprayed with CuO-NPs. Overall, the findings of the current investigation demonstrated that CuO-NPs can help to reduce the adverse effects of salinity stress on maize plants by improving growth and physio-biochemical attributes.

This research aims to comprehend the current situation of maize production and consumption in Egypt by studying production, and consumer indicators across the years (2003-2020), to determine the marketing problems that face farmers and find out their thoughts on the government agricultural policy. The results showed that from 2003 to 2020, the amount of land planted with maize in Egypt varied between two limits, with the lowest amounting to roughly 1657.8 thousand acres in 2003 and the highest amounting to roughly 2335.63 thousand acres in 2018, with the overall average of the cultivated area being about 2010.03 thousand acres during that time. When we looked at the production costs, we discovered that they had taken on an increasing and significant trend at a statistically significant level of 0.01, where the yearly increase in costs was equal to about 372.17 pounds/acre, at an increasing rate of about 10.84% of the average production costs during that time. By analyzing the relative importance of the marketing problems that maize growers in Egypt's ancient lands face, it was discovered that the problems of not receiving the crop's price right away takes the top spot, accounting for approximately 14.18% of the total, with the problems of market distance from the production sites and risk from price fluctuation coming in second and third, respectively.

In the agricultural sector, identifying plant diseases at their earliest possible stage of infestation still remains a huge challenge with respect to the maximization of crop production and farmers’ income. In recent years, advanced computer vision techniques like Vision Transformers (ViTs) are being successfully applied to identify plant diseases automatically. However, the MLP module in existing ViTs is computationally expensive as well as inefficient in extracting promising features from diseased images. Therefore, this study proposes a comparatively lightweight and improved vision transformer network, also known as “TrIncNet” for plant disease identification. In the proposed network, we introduced a modified encoder architecture a.k.a. Trans-Inception block in which the MLP block of existing ViT was replaced by a custom inception block. Additionally, each Trans-Inception block is surrounded by a skip connection, making it much more resistant to the vanishing gradient problem. The applicability of the proposed network for identifying plant diseases was assessed using two plant disease image datasets viz: PlantVillage dataset and Maize disease dataset (contains in-field images of Maize diseases). The comparative performance analysis on both datasets reported that the proposed TrIncNet network outperformed the state-of-the-art CNN architectures viz: VGG-19, GoogLeNet, ResNet-50, Xception, InceptionV3, and MobileNet. Moreover, the experimental results also showed that the proposed network had achieved 5.38% and 2.87% higher testing accuracy than the existing ViT network on both datasets, respectively. Therefore, the lightweight nature and improved prediction performance make the proposed network suitable for being integrated with IoT devices to assist the stakeholders in identifying plant diseases at the field level.

Disease attack on crops is one of the most serious threats to the global food supply chain. A proper, comprehensive and systematic solution is required for the early recognition of diseases and to reduce the overall crop loss. In this regard, deep learning techniques (especially convolutional neural networks (CNNs/ConvNets)) are being successfully applied for automatically recognizing the diseases of crops using digital images. This study proposes a novel 15-layer deep convolutional neural network (CNN) model for recognizing the diseases of maize crop. Around 3852 images of maize crop were collected from the PlantVillage data-repository. This dataset contains leaf images of three diseases viz. gray Leaf Spot (GLS), Common Rust (CR) and Northern Corn Leaf Blight (NCLB) as well as the healthy ones. The proposed model showed significant results for recognizing the unseen diseased images of the maize crop. We also employed a few popular pre-trained networks in the transfer learning approach for training on the maize dataset. We presented the comparative performance analysis between the proposed model and the pre-trained models in the result section of the manuscript. The experimental findings reported that our proposed model showed 3.2% higher prediction performance with 3 × lesser trainable parameters than the best-performing pre-trained network (i.e., DenseNet121). The overall performance analysis reported that the proposed CNN model is very effective in identifying the images of maize diseases and also performs quite better than the popular pre-trained models. [ABSTRACT FROM AUTHOR]

This study investigates the issues that affect market access among smallholder maize farmers from a supply chain perspective. A cross-sectional questionnaire survey was used to test the relevance of access theory in assessing the effect of supply chain issues on market access. A total of 359 smallholder maize farmers were sampled randomly from Mbozi district in Tanzania for analysis. The effect of supply chain issues on market access were estimated by using marginal effects based on binary logit model. The study's findings indicate that supply chain-related issues are significant predictors of market access among smallholder maize farmers in the surveyed area. Issues like long marketing and distribution channels, deficient supply chain infrastructure and intensive competition between the supply chains revealed a negative and significant effect on market access among smallholder maize farmers. Besides, better collaborations and networking, appropriate marketing skills and smallholders' ability in meeting customers' requirements revealed a positive and significant effect. Based on these results, authors recommend streamlined coordination and collaboration among agricultural multi-tiers, improve supply chain infrastructure and better quality of agricultural products as the important drivers toward enhanced market access among smallholder maize farmers. More specifically, this study enriches scholars and policymakers with information on the supply issues that affect market access among smallholder farmers, offers some managerial implications and direction for further studies. [ABSTRACT FROM AUTHOR]

Abstract Background The fall armyworm Spodoptera frugiperda is one of the major pests in maize crops, causing important production losses. The pest has rapidly spread worldwide, generating an urgent need to develop efficient and sustainable strategies for its control. In this work, the potential of integrating nucleopolyhedrovirus- (NPV) and the fungus Metarhizium rileyi to control S. frugiperda larvae was evaluated under laboratory, greenhouse, and field conditions. Methods The mortality of S. frugiperda larvae was evaluated after the application of NPV and M. rileyi alone or in combination using three concentrations (high, medium and low) under laboratory conditions. Then, two greenhouse trials using maize plants were carried out to evaluate the effect of individual or combined applications of NPV and M. rileyi on S. frugiperda mortality (first trial) and fresh damage (second trial). Finally, a trial under field conditions was conducted to evaluate the performance of the treatment selected in the greenhouse assay. Results The combined use of NPV: M. rileyi applied simultaneously showed an additive effect in laboratory, causing higher larval mortality than the biocontrol agents used separately. This effect was evident in the mixtures using the concentration levels high:medium, medium:medium, and medium:high. Under greenhouse conditions, the use of a 50:50 ratio of the two entomopathogens also caused higher larval mortality and a significantly reduced insect damage to plants. Finally, under field conditions, the individual or sequential application of NPV and M. rileyi using 100% of their recommended doses, and the simultaneous application of both entomopathogens at 50% of their recommended doses, significantly reduced the recent foliar damage to levels under the threshold for economic losses (30% fresh damage) while the damage reached 43% when control measures were not used. Conclusion The combined application of NPV and M. rileyi (two biocontrol agents with different mode of action) demonstrated an additive effect that allows to reduce to half their recommended application doses. In this context, the integration of both entomopathogens is a promising strategy to manage S. frugiperda, contributing to improve the economic feasibility of biological control tools for the sustainable fall armyworm management.

Maydis leaf blight (MLB) of maize (Zea Mays L.), a serious fungal disease, is capable of causing up to 70% damage to the crop under severe conditions. Severity of diseases is considered as one of the important factors for proper crop management and overall crop yield. Therefore, it is quite essential to identify the disease at the earliest possible stage to overcome the yield loss. In this study, we created an image database of maize crop, MDSD (Maydis leaf blight Disease Severity Dataset), containing 1,760 digital images of MLB disease, collected from different agricultural fields and categorized into four groups viz. healthy, low, medium and high severity stages. Next, we proposed a lightweight convolutional neural network (CNN) to identify the severity stages of MLB disease. The proposed network is a simple CNN framework augmented with two modified Inception modules, making it a lightweight and efficient multi-scale feature extractor. The proposed network reported approx. 99.13% classification accuracy with the f1-score of 98.97% on the test images of MDSD. Furthermore, the class-wise accuracy levels were 100% for healthy samples, 98% for low severity samples and 99% for the medium and high severity samples. In addition to that, our network significantly outperforms the popular pretrained models, viz. VGG16, VGG19, InceptionV3, ResNet50, Xception, MobileNetV2, DenseNet121 and NASNetMobile for the MDSD image database. The experimental findings revealed that our proposed lightweight network is excellent in identifying the images of severity stages of MLB disease despite complicated background conditions. [ABSTRACT FROM AUTHOR]

Maize crop lodging is a recurrent phenomenon which results in significant reduction of grain yield and quality in addition to the impediment of mechanical harvesting. The large-scale monitoring of maize crop lodging is important for production policy adjustment and agricultural insurance compensation. In this article, we derived a variety of features from multitemporal GaoFen-1 (GF-1) images before and after maize crop lodging. We screened the most sensitive features of the spectrum, texture, and vegetation index to monitor maize crop lodging. The recursive feature elimination method based on cross-validation and mutual information were compared to obtain the optimal feature combination for monitoring the lodging extents of maize crop. The random forest classifier was used to classify the lodging extents. The results showed that the most sensitive features of the spectrum, texture, and vegetation indices of lodging extents included the difference of reflectance in blue, green, and red bands, the difference of normalized difference vegetation index, the difference of ratio vegetation index, the difference of enhanced vegetation index difference, the difference of mean value of blue band, the difference of mean value of green band, and the difference of mean value of red band. The total accuracy of lodging extents classification was 87.50%, and the Kappa coefficient was 0.83 for testing samples. Based on multiple features derived from GF-1 images before and after lodging, the lodging extents of maize crop can be monitored on a large scale.

Maydis leaf blight (MLB) of maize (Zea Mays L.), a serious fungal disease, is capable of causing up to 70% damage to the crop under severe conditions. Severity of diseases is considered as one of the important factors for proper crop management and overall crop yield. Therefore, it is quite essential to identify the disease at the earliest possible stage to overcome the yield loss. In this study, we created an image database of maize crop, MDSD (Maydis leaf blight Disease Severity Dataset), containing 1,760 digital images of MLB disease, collected from different agricultural fields and categorized into four groups viz. healthy, low, medium and high severity stages. Next, we proposed a lightweight convolutional neural network (CNN) to identify the severity stages of MLB disease. The proposed network is a simple CNN framework augmented with two modified Inception modules, making it a lightweight and efficient multi-scale feature extractor. The proposed network reported approx. 99.13% classification accuracy with the f1-score of 98.97% on the test images of MDSD. Furthermore, the class-wise accuracy levels were 100% for healthy samples, 98% for low severity samples and 99% for the medium and high severity samples. In addition to that, our network significantly outperforms the popular pretrained models, viz. VGG16, VGG19, InceptionV3, ResNet50, Xception, MobileNetV2, DenseNet121 and NASNetMobile for the MDSD image database. The experimental findings revealed that our proposed lightweight network is excellent in identifying the images of severity stages of MLB disease despite complicated background conditions.

Elevated atmospheric carbon dioxide (eCO2) concentrations can alter the carbon:nitrogen ratio and palatability of host plants for herbivorous insects, but rhizobacteria likely mitigate the alteration and influence physiological adaptation of insects. In this study, we conducted transcriptomic analysis of maize (Zea mays) response to Azotobacter chroococcum (AC) inoculation under eCO2 conditions in contrast to ambient CO2 (aCO2), and studied the effects of plant-defense change of maize under eCO2 on the oriental armyworm, Mythimna separata. Results showed that there were 16, 14, 16 and 135 differentially expressed genes that were associated with plant-defense response in maize leaves between aCO2-CK and aCO2-AC, eCO2-CK and eCO2-AC, aCO2-CK and eCO2-CK, aCO2-AC and eCO2-AC, respectively. Moreover, A. chroococcum inoculation and eCO2 influenced plant hormone signal transduction of maize. Interestingly, A. chroococcum inoculation significantly decreased the contents of JA (jasmonic acid) and JA-Ile (isoleucine conjugate of JA) in leaves, but eCO2 markedly increased contents of JA-Ile, JA and SA (salicylic acid). Compared to aCO2, eCO2 significantly decreased activity of protective enzyme (catalase), and increased activities of digestive (lipase and protease), protective (peroxidase) and detoxifying enzymes (carboxylesterase, Mixed-functional oxidase and glutathione s-transferase), prolonged developmental time, and decreased survival rate and body weight of larvae (P

The fall armyworm (FAW), Spodoptera frugiperda (J. E. Smith), was first detected in India in 2018 and seriously threatened the maize crop. In South India, we studied the population dynamics of FAW moths and the damage caused by the larvae in maize fields from 2019 to 2020. In the kharif season, the highest male moth catches occurred in July while in rabi season, the highest catches occurred in November. It was found that the early whorl stage (EV-V6) of maize crop was susceptible to FAW due to its high larval load, whereas the late whorl stage (V7-VT) of the crop showed greater leaf damage in both years. [ABSTRACT FROM AUTHOR]

Predicting maize crop yields especially in maize production is paramount in order to alleviate poverty and contribute towards food security. Many regions experience food shortage especially in Africa because of uncertain climatic changes, poor irrigation facilities, reduction in soil fertility and traditional farming techniques. Therefore, predicting maize crop yields helps policymakers to make timely import and export decisions to strengthen national food security. However, none of the published work has been done to predict maize crop yields using machine learning in Eswatini, Africa. This paper aimed at applying machine learning (ML) to predict maize yields for a single season in Eswatini. A ML model was trained and tested using open-source data and local data. This is done by using three different data splits with the opensource predictor data consisting of 48 data points each with 7 attributes and open-source response data consisting of 48 data points each with a single attribute, adjusted R² values were 0.784 (at 70:30), 0.849 (at 80:20), and 0.878 (at 90:10) before being normalized, 1.00 across the board after normalization, and 0.846 (at 70:30), 0.886 (at 80:20), and 0.885 (at 90:10) after backward elimination. At the second attempt, it is done by using the combined predictor data of 68 data points with 7 attributes each and combined response data of 68 data points with a single attribute each, with the same data splits and methods adjusted R² values were 0.966 (at 70:30), 0.972 (at 80:20), and 0.978 (at 90:10) before being normalized, 1.00 across the board after normalization, and 0.967 (at 70:30), 0.973 (at 80:20), and 0.978 (at 90:10) after backward elimination.

There is an urgent need for innovative strategies to raise the performance of environmentally stressed plants. The seeds of single-cross yellow Zea mays (L.) hybrid Giza-168 were soaked in Cis-(c-Z-Ck) or trans-zeatin-type cytokinin (t-Z-Ck) solutions at a concentration of 50 or 40 µM, respectively. Salinity stress was imposed at 0, 75 or 150 mM NaCl in the Hoagland nutrient solution (full strength) used for irrigation. The total carotenoids content was negatively affected by only 150 mM NaCl, while both 75 and 150 mM NaCl negatively affected the growth and yield components, relative water content, membrane stability index, photochemical activity, gas exchange, K+ and chlorophyll contents, K+/Na+ ratio, and photosynthetic efficiency. However, all of these traits were significantly improved by c-Z-Ck pretreatment and further enhanced by t-Z-Ck pretreatment compared with the corresponding controls. Furthermore, the contents of proline, soluble sugars, ascorbate, and glutathione, as well as enzymatic antioxidant activities, were significantly elevated by both salt stress concentrations and increased more by both biostimulators compared to the control. Compared to c-Z-Ck, t-Z-Ck was superior in mitigating the harmful effects of the high H2O2 levels caused by salt stress on the levels of malondialdehyde and ion leakage compared to the control. Under normal or stress conditions, t-Z-Ck pretreatment was better than c-Z-Ck pretreatment, while both positively affected maize hormonal contents. As a result, t-Z-Ck is recommended to enhance the growth and productivity of maize plants by suppressing the effects of oxidative stress caused by saline water irrigation. [ABSTRACT FROM AUTHOR]

Intensive conventional tillage practice has deteriorated soil quality and decreased potassium (K) availability in soil under maize-based growing areas in eastern India. Consequently, maize productivity has declined over the years demonstrating the need for sustainable alternatives. A field study was carried out in 2018 in the eighth year of an on-going long-term experiment initiated in the year 2011 to understand the impact of different tillage practices in maize-based cropping systems on soil properties and K dynamics in Inceptisols of eastern India. The experiment was laid out in split plot design with three levels of tillage practice as main plots: zero tillage, permanent raised bed and conventional tillage and in subplots as three different cropping systems viz. maize-maize, maize-wheat, and maize-chickpea. The result showed that under tillage practices, soil parameters were improved in zero tillage over the permanent raised bed and conventional tillage and among cropping systems, maize-chickpea had more nutrient availability in compared with maize-maize and maize-wheat. Soil organic carbon was built up by 10.2% in zero tillage over the initial soil measured at the time of the start of the experiment. The maximum content of water-soluble K, exchangeable K, and nonexchangeable K were recorded in zero tillage and maize-chickpea as compared to other tillage practices and cropping systems. Among Q/I parameters, potential buffering capacity (PBCK) was maximum and activity ratio (ARK) and labile K (KL) were minimum under zero tillage and maize-chickpea cropping system than the other tillage practices and cropping systems. Therefore, zero tillage and maize-chickpea could be better practices over the other tillage practices and cropping systems for improving soil quality and K availability in soil. [ABSTRACT FROM AUTHOR]

Zinc (Zn) is an important micronutrient for plant physiology, including the activation of various enzymes, nitrogen metabolism, cell-membrane integrity, and carbonic anhydrase activity. Its deficiency is reported in plants grown in poor soils worldwide including Pakistan. Exogenous application of Zn fertilizers is not efficient due to fixation into the soil. Thus, Zn solubilizing bacteria have a stronger power to chelates the insoluble Zn compounds which may increase Zn availability for plant uptake. Therefore, a pot trial was conducted to evaluate the effects of four products of bio-activated zinc oxide (ZnO) formulated using bio augmented-organic matter coated with zinc oxide (BOZ) on the physiological attributes of maize. Four different products viz. BOZ1, BOZ2, BOZ3, and BOZ4 were prepared using Bacillus sp. AZ6 strain augmented orange peel and ZnO. The results revealed that BOZ4 formulation performed outclass by exhibiting 85%, 31%, and 108% higher photosynthetic rate, stomatal conductance, and transpiration rate, respectively, compared to control. Likewise, it showed a maximum increase in carbonic anhydrase activity, vapor pressure deficit, electrolyte leakage, and SPAD value by 74%, 44%, 45%, and 66%, respectively, over control. Hence, it is concluded that bio-activation of ZnO by Bacillus sp. AZ6 and orange-peel waste could serve as an effective strategy to improve the physiology of maize. [ABSTRACT FROM AUTHOR]

Maize crop (Zea mays) is one of the staple foods in the East African (EA) region. However, the suitability of its production area is threatened by projected climate change. The Multimodel Ensemble (MME) from eight Coupled Model Intercomparison Project 5 (CMIP5) models was used in this paper to show climate change between the recent past (1970–2000) and the future (2041–2060), i.e., the mid-twenty-first century. The climatic suitability of maize crop production areas is evaluated based on these climate datasets and the current maize crop presence points using Maximum entropy models (MaxEnt). The MME projection showed a slight increase in precipitation under both RCP4.5 and RCP8.5 in certain places and a reduction in most of southern Tanzania. The temperature projection showed that the minimum temperature would increase by 0.3 to 2.95 °C and 0.3 to 3.2 °C under RCP4.5 and 8.5, respectively. Moreover, the maximum temperature would increase by 1.0 to 3.0 °C and 1.2 to 3.6 °C under RCP4.5 and 8.5 respectively. The impacts of these projected changes in climate on maize production areas are the reduction in the suitability of the crop, especially around central and western Tanzania, mid-northern and western Uganda, and parts of western Kenya by 20–40%, and patches of EA will experience a reduction of as high as 40–60%, especially in northern Uganda, and western Kenya. The projected changes in temperature and precipitation present a significant negative change in maize crop suitability. Thus, food security and the efforts towards the elimination of hunger in EA by the mid-twenty-first century will be hampered significantly. We recommend crop diversification to suit the new future environments, modernizing maize farming programs through the adoption of new technologies including irrigation, and climate-smart agricultural practices, etc. [ABSTRACT FROM AUTHOR]

For small and marginal farmers the affordable weeding option is either hand weeding or simple manual operated mechanical weeder in crop production for qualitative as well as quanlitative yield. Irrespective of weeding options the efficiency of weeding plays an importatnt role in overall performance of of the crop. This research paper presents a new prototype manual mechanical weeder designed and developed to take into account the anthropometric parameters of farm workers in Eastern region of India. Unlike other available manually operated mechanical weeders, this new weeder facilitates weeding in close proximity of plants and therefore improves overall wedding efficiency. The weeder was evaluated in maize crop and its weeding efficiency in maize crop was found to be 85% with operating field capacity 0.0120 ha/h. The design components of this weeder are simple and therefore can be manufactured locally at affordable and comparable with peers at cost of ₹1200-1400.

BACKGROUND: Due to the rapid increase in world population, the demand for freshwater is increasing day by day. There is also immense pressure on the agriculture sector to produce more food with limited supplies of water. About 75% of freshwater is used in crop production out of which 63% is lost due to poor farm practices and evapotranspiration. Enhancement of crop water productivity for sustainable agriculture production especially in areas having water scarcity plausibly contributes towards the solution of water scarcity. RESULTS: The combined application of biochar and compost has a highly significant impact on maize yield with increased grain production, i.e. 6.44 and 6.52 t ha-1 at 60% irrigation level with combined application of biochar and compost as compared with control at 6.39 and 6.44 t ha-1 at 100% irrigation level in autumn and spring seasons, respectively, by saving 40% of water. Furthermore, the highest value of water productivity (1.51 and 1.16 kg m-3) was achieved at 60% irrigation level with combined application of soil amendments. Also, cost--benefit analysis has shown highest values of net benefit with soil organic amendments. CONCLUSIONS: It is concluded that addition of biochar and compost to soil has the potential to increase crop yield and growth even at low irrigation levels by enhancing water use efficiency. [ABSTRACT FROM AUTHOR]

Rice husk biochar and compost application are expected to improve soil chemical properties such as pH, organic carbon, and available P in Ultisol, which in turn improves crop growth and P uptake by plants. The purpose of this research was to analyze the effect of the combination of rice husk biochar and compost on the soil chemical properties (pH, organic carbon, and available P), maize growth, and P uptake by maize in an Ultisol. The research used a Randomized Block Design with six treatments (P0: control; P1: 4 t biochar ha-1; P2: 30 t compost ha-1; P3: 4 t biochar ha-1 and 30 t compost ha-1; P4: 8 t biochar ha-1 and 30 t compost ha-1; P5: 4 t biochar ha-1 and 60 t compost ha-1) and four replications. The result showed that the combination of 8 t rice husk biochar ha-1 and 30 t compost ha-1 showed a significant effect on increasing pH, organic carbon, and available P in an Ultisol, increasing the height of maize crops at 4 and 6 WAP (weeks after planting). However, it had no effect on the number of leaves and showed an effect on the increase in P uptake of maize crop.